The roles of the trading time risks on stock investment return and risks in stock price crashes

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Dong, Zhi-Wei; Yang, Guo-Hui; Long, Chao

2017-03-01

The roles of the trading time risks (TTRs) on stock investment return and risks are investigated in the condition of stock price crashes with Hushen300 data (CSI300) and Dow Jones Industrial Average (ˆDJI), respectively. In order to describe the TTR, we employ the escape time that the stock price drops from the maximum to minimum value in a data window length (DWL). After theoretical and empirical research on probability density function of return, the results in both ˆDJI and CSI300 indicate that: (i) As increasing DWL, the expectation of returns and its stability are weakened. (ii) An optimal TTR is related to a maximum return and minimum risk of stock investment in stock price crashes.

The overnight effect on the Taiwan stock market

NASA Astrophysics Data System (ADS)

Tsai, Kuo-Ting; Lih, Jiann-Shing; Ko, Jing-Yuan

2012-12-01

This study examines statistical regularities among three components of stocks and indices: daytime (trading hour) return, overnight (off-hour session) return, and total (close-to-close) return. Owing to the fact that the Taiwan Stock Exchange (TWSE) has the longest non-trading periods among major markets, the TWSE is selected to explore the correlation among the three components and compare it with major markets such as the New York Stock Exchange (NYSE) and the National Association of Securities Dealers Automated Quotation (NASDAQ). Analysis results indicate a negative cross correlation between the sign of daytime return and the sign of overnight return; possibly explaining why most stocks feature a negative cross correlation between daytime return and overnight return [F. Wang, S.-J. Shieh, S. Havlin, H.E. Stanley, Statistical analysis of the overnight and daytime return, Phys. Rev. E 79 (2009) 056109]. Additionally, the cross correlation between the magnitude of returns is analyzed. According to those results, a larger magnitude of overnight return implies a higher probability that the sign of the following daytime return is the opposite of the sign of overnight return. Namely, the predictability of daytime return might be improved when a stock undergoes a large magnitude of overnight return. Furthermore, the cross correlations of 29 indices of worldwide markets are discussed.

Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of portfolio management in stock market investment. Enhanced index tracking aims to construct an optimal portfolio to generate excess return over the return achieved by the stock market index without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using mixed-integer programming model which adopts regression approach in order to generate higher portfolio mean return than stock market index return. In this study, the data consists of 24 component stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2012. The results of this study show that the optimal portfolio of mixed-integer programming model is able to generate higher mean return than FTSE Bursa Malaysia Kuala Lumpur Composite Index return with only selecting 30% out of the total stock market index components.

Essays on the effects of oil price shocks on the U.S. stock returns

NASA Astrophysics Data System (ADS)

Alsalman, Zeina N.

This research investigates the effect of changes in oil prices and oil price volatility on the U.S. stock returns. The first essay tests whether the sign and the size of oil price shocks matter for the U.S. stock returns. The results suggest a linear model provides a good approximation to the response of real stock returns to real oil price innovations. However, this is not the case when the model is specified in terms of the nominal price of crude oil. Using a modified structural VAR to accommodate GARCH-in-Mean errors, the second essay studies the direct effects of oil price uncertainty on the U.S. stock returns at the aggregate and sectoral levels. We also simulate the response of U.S. stock returns to positive and negative oil price shocks, to examine whether the responses to positive and negative shocks are symmetric. Estimation results suggest that there is no statistically significant effect of oil price volatility on the U.S. stock returns. Moreover, the impulse responses indicate that oil price increases and decreases have symmetric effects on the U.S. stock returns. Using high frequency data, the third essay addresses the issue of uncertainty in oil prices and its effect on U.S. stock returns, taking into account the day of the week effect. The results suggest that the-day-of-the-week effect is present in both the mean and volatility equations. The results also show that the U.S. stock market is sensitive to oil price variations not only at the aggregate level but also across some industries, such as chemicals, entertainment, and retail, where uncertainty in oil prices proves to have positive and statistically significant effect.

Combinatorial Algorithms for Portfolio Optimization Problems - Case of Risk Moderate Investor

NASA Astrophysics Data System (ADS)

Juarna, A.

2017-03-01

Portfolio optimization problem is a problem of finding optimal combination of n stocks from N ≥ n available stocks that gives maximal aggregate return and minimal aggregate risk. In this paper given N = 43 from the IDX (Indonesia Stock Exchange) group of the 45 most-traded stocks, known as the LQ45, with p = 24 data of monthly returns for each stock, spanned over interval 2013-2014. This problem actually is a combinatorial one where its algorithm is constructed based on two considerations: risk moderate type of investor and maximum allowed correlation coefficient between every two eligible stocks. The main outputs resulted from implementation of the algorithms is a multiple curve of three portfolio’s attributes, e.g. the size, the ratio of return to risk, and the percentage of negative correlation coefficient for every two chosen stocks, as function of maximum allowed correlation coefficient between each two stocks. The output curve shows that the portfolio contains three stocks with ratio of return to risk at 14.57 if the maximum allowed correlation coefficient between every two eligible stocks is negative and contains 19 stocks with maximum allowed correlation coefficient 0.17 to get maximum ratio of return to risk at 25.48.

Multifractal analysis of Moroccan family business stock returns

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2017-11-01

In this paper, long-range temporal correlations at different scales in Moroccan family business stock returns are investigated. For comparison purpose, presence of multifractality is also investigated in Casablanca Stock Exchange (CSE) major indices: MASI which is the all shares index and MADEX which is the index of most liquid shares. It is found that return series of both family business companies and major stock market indices show strong evidence of multifractality. In particular, empirical results reveal that short (long) fluctuations in family business stock returns are less (more) persistent (anti-persistent) than short fluctuations in market indices. In addition, both serial correlation and distribution characteristics significantly influence the strength of the multifractal spectrums of CSE and family business stocks returns. Furthermore, results from multifractal spectrum analysis suggest that family business stocks are less risky. Thus, such differences in price dynamics could be exploited by investors and forecasters in active portfolio management.

What stock market returns to expect for the future?

PubMed

Diamond, P A

2000-01-01

In evaluating proposals for reforming Social Security that involve stock investments, the Office of the Chief Actuary (OCACT) has generally used a 7.0 percent real return for stocks. The 1994-96 Advisory Council specified that OCACT should use that return in making its 75-year projections of investment-based reform proposals. The assumed ultimate real return on Treasury bonds of 3.0 percent implies a long-run equity premium of 4.0 percent. There are two equity-premium concepts: the realized equity premium, which is measured by the actual rates of return; and the required equity premium, which investors expect to receive for being willing to hold available stocks and bonds. Over the past two centuries, the realized premium was 3.5 percent on average, but 5.2 percent for 1926 to 1998. Some critics argue that the 7.0 percent projected stock returns are too high. They base their arguments on recent developments in the capital market, the current high value of the stock market, and the expectation of slower economic growth. Increased use of mutual funds and the decline in their costs suggest a lower required premium, as does the rising fraction of the American public investing in stocks. The size of the decrease is limited, however, because the largest cost savings do not apply to the very wealthy and to large institutional investors, who hold a much larger share of the stock market's total value than do new investors. These trends suggest a lower equity premium for projections than the 5.2 percent of the past 75 years. Also, a declining required premium is likely to imply a temporary increase in the realized premium because a rising willingness to hold stocks tends to increase their price. Therefore, it would be a mistake during a transition period to extrapolate what may be a temporarily high realized return. In the standard (Solow) economic growth model, an assumption of slower long-run growth lowers the marginal product of capital if the savings rate is constant. But lower savings as growth slows should partially or fully offset that effect. The present high stock prices, together with projected slow economic growth, are not consistent with a 7.0 percent return. With a plausible level of adjusted dividends (dividends plus net share repurchases), the ratio of stock value to gross domestic product (GDP) would rise more than 20-fold over 75 years. Similarly, the steady-state Gordon formula--that stock returns equal the adjusted dividend yield plus the growth rate of stock prices (equal to that of GDP)--suggests a return of roughly 4.0 percent to 4.5 percent. Moreover, when relative stock values have been high, returns over the following decade have tended to be low. To eliminate the inconsistency posed by the assumed 7.0 percent return, one could assume higher GDP growth, a lower long-run stock return, or a lower short-run stock return with a 7.0 percent return on a lower base thereafter. For example, with an adjusted dividend yield of 2.5 percent to 3.0 percent, the market would have to decline about 35 percent to 45 percent in real terms over the next decade to reach steady state. In short, either the stock market is overvalued and requires a correction to justify a 7.0 percent return thereafter, or it is correctly valued and the long-run return is substantially lower than 7.0 percent (or some combination). This article argues that the "overvalued" view is more convincing, since the "correctly valued" hypothesis implies an implausibly small equity premium. Although OCACT could adopt a lower rate for the entire 75-year period, a better approach would be to assume lower returns over the next decade and a 7.0 percent return thereafter.

Twitter sentiment around the Earnings Announcement events

PubMed Central

Grčar, Miha

2017-01-01

We investigate the relationship between social media, Twitter in particular, and stock market. We provide an in-depth analysis of the Twitter volume and sentiment about the 30 companies in the Dow Jones Industrial Average index, over a period of three years. We focus on Earnings Announcements and show that there is a considerable difference with respect to when the announcements are made: before the market opens or after the market closes. The two different timings of the Earnings Announcements were already investigated in the financial literature, but not yet in the social media. We analyze the differences in terms of the Twitter volumes, cumulative abnormal returns, trade returns, and earnings surprises. We report mixed results. On the one hand, we show that the Twitter sentiment (the collective opinion of the users) on the day of the announcement very well reflects the stock moves on the same day. We demonstrate this by applying the event study methodology, where the polarity of the Earnings Announcements is computed from the Twitter sentiment. Cumulative abnormal returns are high (2–4%) and statistically significant. On the other hand, we find only weak predictive power of the Twitter sentiment one day in advance. It turns out that it is important how to account for the announcements made after the market closes. These after-hours announcements draw high Twitter activity immediately, but volume and price changes in trading are observed only on the next day. On the day before the announcements, the Twitter volume is low, and the sentiment has very weak predictive power. A useful lesson learned is the importance of the proper alignment between the announcements, trading and Twitter data. PMID:28235103

Twitter sentiment around the Earnings Announcement events.

PubMed

Gabrovšek, Peter; Aleksovski, Darko; Mozetič, Igor; Grčar, Miha

2017-01-01

We investigate the relationship between social media, Twitter in particular, and stock market. We provide an in-depth analysis of the Twitter volume and sentiment about the 30 companies in the Dow Jones Industrial Average index, over a period of three years. We focus on Earnings Announcements and show that there is a considerable difference with respect to when the announcements are made: before the market opens or after the market closes. The two different timings of the Earnings Announcements were already investigated in the financial literature, but not yet in the social media. We analyze the differences in terms of the Twitter volumes, cumulative abnormal returns, trade returns, and earnings surprises. We report mixed results. On the one hand, we show that the Twitter sentiment (the collective opinion of the users) on the day of the announcement very well reflects the stock moves on the same day. We demonstrate this by applying the event study methodology, where the polarity of the Earnings Announcements is computed from the Twitter sentiment. Cumulative abnormal returns are high (2-4%) and statistically significant. On the other hand, we find only weak predictive power of the Twitter sentiment one day in advance. It turns out that it is important how to account for the announcements made after the market closes. These after-hours announcements draw high Twitter activity immediately, but volume and price changes in trading are observed only on the next day. On the day before the announcements, the Twitter volume is low, and the sentiment has very weak predictive power. A useful lesson learned is the importance of the proper alignment between the announcements, trading and Twitter data.

Equity prices as a simple harmonic oscillator with noise

NASA Astrophysics Data System (ADS)

Ataullah, Ali; Tippett, Mark

2007-08-01

The centred return on the London Stock Exchange's FTSE All Share Index is modelled as a simple harmonic oscillator with noise over the period from 1 January, 1994 until 30 June 2006. Our empirical results are compatible with the hypothesis that there is a period in the FTSE All Share Index of between two and two and one half years. This means the centred return will on average continue to increase for about a year after reaching the minimum in its oscillatory cycle; alternatively, it will continue on average to decline for about a year after reaching a maximum. Our analysis also shows that there is potential to exploit the harmonic nature of the returns process to earn abnormal profits. Extending our analysis to the low energy states of a quantum harmonic oscillator is also suggested.

Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph

PubMed Central

Zhao, Shuai; Tong, Yunhai; Wang, Zitian; Tan, Shaohua

2016-01-01

In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks’ price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds. PMID:27893780

Range-based volatility, expected stock returns, and the low volatility anomaly

PubMed Central

2017-01-01

One of the foundations of financial economics is the idea that rational investors will discount stocks with more risk (volatility), which will result in a positive relation between risk and future returns. However, the empirical evidence is mixed when determining how volatility is related to future returns. In this paper, we examine this relation using a range-based measure of volatility, which is shown to be theoretically, numerically, and empirically superior to other measures of volatility. In a variety of tests, we find that range-based volatility is negatively associated with expected stock returns. These results are robust to time-series multifactor models as well as cross-sectional tests. Our findings contribute to the debate about the direction of the relationship between risk and return and confirm the presence of the low volatility anomaly, or the anomalous finding that low volatility stocks outperform high volatility stocks. In other tests, we find that the lower returns associated with range-based volatility are driven by stocks with lottery-like characteristics. PMID:29190652

Range-based volatility, expected stock returns, and the low volatility anomaly.

PubMed

Blau, Benjamin M; Whitby, Ryan J

2017-01-01

One of the foundations of financial economics is the idea that rational investors will discount stocks with more risk (volatility), which will result in a positive relation between risk and future returns. However, the empirical evidence is mixed when determining how volatility is related to future returns. In this paper, we examine this relation using a range-based measure of volatility, which is shown to be theoretically, numerically, and empirically superior to other measures of volatility. In a variety of tests, we find that range-based volatility is negatively associated with expected stock returns. These results are robust to time-series multifactor models as well as cross-sectional tests. Our findings contribute to the debate about the direction of the relationship between risk and return and confirm the presence of the low volatility anomaly, or the anomalous finding that low volatility stocks outperform high volatility stocks. In other tests, we find that the lower returns associated with range-based volatility are driven by stocks with lottery-like characteristics.

On fractality and chaos in Moroccan family business stock returns and volatility

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2017-05-01

The purpose of this study is to examine existence of fractality and chaos in returns and volatilities of family business companies listed on the Casablanca Stock Exchange (CSE) in Morocco, and also in returns and volatility of the CSE market index. Detrended fluctuation analysis based Hurst exponent and fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) model are used to quantify fractality in returns and volatility time series respectively. Besides, the largest Lyapunov exponent is employed to quantify chaos in both time series. The empirical results from sixteen family business companies follow. For return series, fractality analysis show that most of family business returns listed on CSE exhibit anti-persistent dynamics, whilst market returns have persistent dynamics. Besides, chaos tests show that business family stock returns are not chaotic while market returns exhibit evidence of chaotic behaviour. For volatility series, fractality analysis shows that most of family business stocks and market index exhibit long memory in volatility. Furthermore, results from chaos tests show that volatility of family business returns is not chaotic, whilst volatility of market index is chaotic. These results may help understanding irregularities patterns in Moroccan family business stock returns and volatility, and how they are different from market dynamics.

Statistical analysis of bankrupting and non-bankrupting stocks

NASA Astrophysics Data System (ADS)

Li, Qian; Wang, Fengzhong; Wei, Jianrong; Liang, Yuan; Huang, Jiping; Stanley, H. Eugene

2012-04-01

The recent financial crisis has caused extensive world-wide economic damage, affecting in particular those who invested in companies that eventually filed for bankruptcy. A better understanding of stocks that become bankrupt would be helpful in reducing risk in future investments. Economists have conducted extensive research on this topic, and here we ask whether statistical physics concepts and approaches may offer insights into pre-bankruptcy stock behavior. To this end, we study all 20092 stocks listed in US stock markets for the 20-year period 1989-2008, including 4223 (21 percent) that became bankrupt during that period. We find that, surprisingly, the distributions of the daily returns of those stocks that become bankrupt differ significantly from those that do not. Moreover, these differences are consistent for the entire period studied. We further study the relation between the distribution of returns and the length of time until bankruptcy, and observe that larger differences of the distribution of returns correlate with shorter time periods preceding bankruptcy. This behavior suggests that sharper fluctuations in the stock price occur when the stock is closer to bankruptcy. We also analyze the cross-correlations between the return and the trading volume, and find that stocks approaching bankruptcy tend to have larger return-volume cross-correlations than stocks that are not. Furthermore, the difference increases as bankruptcy approaches. We conclude that before a firm becomes bankrupt its stock exhibits unusual behavior that is statistically quantifiable.

The time-varying correlation between policy uncertainty and stock returns: Evidence from China

NASA Astrophysics Data System (ADS)

Xiong, Xiong; Bian, Yuxiang; Shen, Dehua

2018-06-01

In this paper, we use a new policy uncertainty index to investigate the time-varying correlation between economic policy uncertainty (EPU) and Chinese stock market returns. The correlation is examined in the period from January 1995 to December 2016. We show that absolute changes in EPU have a significant impact on stock market returns. Specifically, empirical results based on the DCC-GARCH model reveal that the correlation between EPU and stock returns has large fluctuations, especially during a financial crisis; in addition, the impact of EPU on the Shanghai stock market is greater than on the Shenzhen stock market. Robustness results reveal that the impact of EPU on state-owned enterprises is larger than on non-state enterprises. All of these results highlight the important role of EPU in the Chinese stock market, and shed light on such issues for future research.

Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model

NASA Astrophysics Data System (ADS)

Rounaghi, Mohammad Mahdi; Nassir Zadeh, Farzaneh

2016-08-01

We investigated the presence and changes in, long memory features in the returns and volatility dynamics of S&P 500 and London Stock Exchange using ARMA model. Recently, multifractal analysis has been evolved as an important way to explain the complexity of financial markets which can hardly be described by linear methods of efficient market theory. In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, it has been suggested that self-similar processes be employed to capture these characteristics in return volatility modeling. The present study applies monthly and yearly forecasting of Time Series Stock Returns in S&P 500 and London Stock Exchange using ARMA model. The statistical analysis of S&P 500 shows that the ARMA model for S&P 500 outperforms the London stock exchange and it is capable for predicting medium or long horizons using real known values. The statistical analysis in London Stock Exchange shows that the ARMA model for monthly stock returns outperforms the yearly. ​A comparison between S&P 500 and London Stock Exchange shows that both markets are efficient and have Financial Stability during periods of boom and bust.

Distribution, stock composition and timing, and tagging response of wild Chinook Salmon returning to a large, free-flowing river basin

USGS Publications Warehouse

Eiler, John H.; Masuda, Michele; Spencer, Ted R.; Driscoll, Richard J.; Schreck, Carl B.

2014-01-01

Chinook Salmon Oncorhynchus tshawytscha returns to the Yukon River basin have declined dramatically since the late 1990s, and detailed information on the spawning distribution, stock structure, and stock timing is needed to better manage the run and facilitate conservation efforts. A total of 2,860 fish were radio-tagged in the lower basin during 2002–2004 and tracked upriver. Fish traveled to spawning areas throughout the basin, ranging from several hundred to over 3,000 km from the tagging site. Similar distribution patterns were observed across years, suggesting that the major components of the run were identified. Daily and seasonal composition estimates were calculated for the component stocks. The run was dominated by two regional components comprising over 70% of the return. Substantially fewer fish returned to other areas, ranging from 2% to 9% of the return, but their collective contribution was appreciable. Most regional components consisted of several principal stocks and a number of small, spatially isolated populations. Regional and stock composition estimates were similar across years even though differences in run abundance were reported, suggesting that the differences in abundance were not related to regional or stock-specific variability. Run timing was relatively compressed compared with that in rivers in the southern portion of the species’ range. Most stocks passed through the lower river over a 6-week period, ranging in duration from 16 to 38 d. Run timing was similar for middle- and upper-basin stocks, limiting the use of timing information for management. The lower-basin stocks were primarily later-run fish. Although differences were observed, there was general agreement between our composition and timing estimates and those from other assessment projects within the basin, suggesting that the telemetry-based estimates provided a plausible approximation of the return. However, the short duration of the run, complex stock structure, and similar stock timing complicate management of Yukon River returns.

Variety and volatility in financial markets

NASA Astrophysics Data System (ADS)

Lillo, Fabrizio; Mantegna, Rosario N.

2000-11-01

We study the price dynamics of stocks traded in a financial market by considering the statistical properties of both a single time series and an ensemble of stocks traded simultaneously. We use the n stocks traded on the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days with the exception of crash and rally days and of the days following these extreme events. We analyze each ensemble return distribution by extracting its first two central moments. We observe that these moments fluctuate in time and are stochastic processes, themselves. We characterize the statistical properties of ensemble return distribution central moments by investigating their probability density functions and temporal correlation properties. In general, time-averaged and portfolio-averaged price returns have different statistical properties. We infer from these differences information about the relative strength of correlation between stocks and between different trading days. Last, we compare our empirical results with those predicted by the single-index model and we conclude that this simple model cannot explain the statistical properties of the second moment of the ensemble return distribution.

Effects of daylight savings time changes on stock market volatility.

PubMed

Berument, M Hakan; Dogan, Nukhet; Onar, Bahar

2010-04-01

The presence of daylight savings time effects on stock returns and on stock volatility was investigated using an EGARCH specification to model the conditional variance. The evidence gathered from the major United States stock markets for the period between 1967 and 2007 did not support the existence of the daylight savings time effect on stock returns or on volatility. Returns on the first business day following daylight savings time changes were not lower nor was the volatility higher, as would be expected if there were an effect.

Capital Structure and Stock Returns

ERIC Educational Resources Information Center

Welch, Ivo

2004-01-01

U.S. corporations do not issue and repurchase debt and equity to counteract the mechanistic effects of stock returns on their debt-equity ratios. Thus over one- to five-year horizons, stock returns can explain about 40 percent of debt ratio dynamics. Although corporate net issuing activity is lively and although it can explain 60 percent of debt…

Daily happiness and stock returns: Some international evidence

NASA Astrophysics Data System (ADS)

Zhang, Wei; Li, Xiao; Shen, Dehua; Teglio, Andrea

2016-10-01

In this paper, we examine the relations between the daily happiness sentiment extracted from Twitter and the stock market performance in 11 international stock markets. By partitioning this happiness sentiment into quintiles from the least to the happiest days, we first show that the contemporary correlation coefficients between happiness sentiment and index return in the 4 and most-happiness subgroups are higher than that in least, 2 and 3-happiness subgroups. Secondly, the happiness sentiment can provide additional explanatory power for index return in the most-happiness subgroup. Thirdly, the daily happiness can granger-cause the changes in index return for the majority of stock markets. Fourthly, we find that the index return and the range-based volatility of the most-happiness subgroup are larger than those of other subgroups. These results highlight the important role of social media in stock market.

Earnings Quality Measures and Excess Returns

PubMed Central

Perotti, Pietro; Wagenhofer, Alfred

2014-01-01

This paper examines how commonly used earnings quality measures fulfill a key objective of financial reporting, i.e., improving decision usefulness for investors. We propose a stock-price-based measure for assessing the quality of earnings quality measures. We predict that firms with higher earnings quality will be less mispriced than other firms. Mispricing is measured by the difference of the mean absolute excess returns of portfolios formed on high and low values of a measure. We examine persistence, predictability, two measures of smoothness, abnormal accruals, accruals quality, earnings response coefficient and value relevance. For a large sample of US non-financial firms over the period 1988–2007, we show that all measures except for smoothness are negatively associated with absolute excess returns, suggesting that smoothness is generally a favorable attribute of earnings. Accruals measures generate the largest spread in absolute excess returns, followed by smoothness and market-based measures. These results lend support to the widespread use of accruals measures as overall measures of earnings quality in the literature. PMID:26300582

Earnings Quality Measures and Excess Returns.

PubMed

Perotti, Pietro; Wagenhofer, Alfred

2014-06-01

This paper examines how commonly used earnings quality measures fulfill a key objective of financial reporting, i.e., improving decision usefulness for investors. We propose a stock-price-based measure for assessing the quality of earnings quality measures. We predict that firms with higher earnings quality will be less mispriced than other firms. Mispricing is measured by the difference of the mean absolute excess returns of portfolios formed on high and low values of a measure. We examine persistence, predictability, two measures of smoothness, abnormal accruals, accruals quality, earnings response coefficient and value relevance. For a large sample of US non-financial firms over the period 1988-2007, we show that all measures except for smoothness are negatively associated with absolute excess returns, suggesting that smoothness is generally a favorable attribute of earnings. Accruals measures generate the largest spread in absolute excess returns, followed by smoothness and market-based measures. These results lend support to the widespread use of accruals measures as overall measures of earnings quality in the literature.

Portfolio optimization for index tracking modelling in Malaysia stock market

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Ismail, Hamizun

2016-06-01

Index tracking is an investment strategy in portfolio management which aims to construct an optimal portfolio to generate similar mean return with the stock market index mean return without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using the optimization model which adopts regression approach in tracking the benchmark stock market index return. In this study, the data consists of weekly price of stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2013. The results of this study show that the optimal portfolio is able to track FBMKLCI Index at minimum tracking error of 1.0027% with 0.0290% excess mean return over the mean return of FBMKLCI Index. The significance of this study is to construct the optimal portfolio using optimization model which adopts regression approach in tracking the stock market index without purchasing all index components.

Statistical properties of short-selling and margin-trading activities and their impacts on returns in the Chinese stock markets

NASA Astrophysics Data System (ADS)

Gao, Yan; Gao, Yao

2015-11-01

We investigate the collective behaviors of short-selling and margin-trading between Chinese stocks and their impacts on the co-movements of stock returns by cross-correlation and partial correlation analyses. We find that the collective behaviors of margin-trading are largely attributed to the index cohesive force, while those of short-selling are mainly due to some direct interactions between stocks. Interestingly, the dominant role the finance industry plays in the collective behaviors of short-selling could make it more important in affecting the co-movement structure of stock returns by strengthening its relationship with the market index. By detecting the volume-return and volume-volatility relationships, we find that the investors of the two leverage activities are positively triggered by individual stock volatility first, and next, at the return level, margin-buyers show trend-following properties, while short-sellers are probably informative traders who trade on the information impulse of specific firms. However, the return predictability of the two leverage trading activities and their impacts on stock volatility are not significant. Moreover, both tails of the cumulative distributions of the two leverage trading activities are found following the stretched exponential law better than the power-law.

Cross-sectional test of the Fama-French three-factor model: Evidence from Bangladesh stock market

NASA Astrophysics Data System (ADS)

Hasan, Md. Zobaer; Kamil, Anton Abdulbasah

2014-09-01

Stock market is an important part of a country's economy. It supports the country's economic development and progress by encouraging the efficiency and profitability of firms. This research was designed to examine the risk-return association of companies in the Dhaka Stock Exchange (DSE) market of Bangladesh by using the Fama-French three-factor model structure. The model is based on three factors, which are stock beta, SMB (difference in returns of the portfolio with small market capitalisation minus that with big market capitalisation) and HML (difference in returns of the portfolio with high book-to-market ratio minus that with low book-to-market ratio). This study focused on the DSE market as it is one of the frontier emerging stock markets of South Asia. For this study, monthly stock returns from 71 non-financial companies were used for the period of January 2002 to December 2011. DSI Index was used as a proxy for the market portfolio and Bangladesh government 3-Month T-bill rate was used as the proxy for the risk-free asset. It was found that large capital stocks outperform small capital stocks and stocks with lower book-to-market ratios outperform stocks with higher book-to-market ratios in the context of Bangladesh stock market.

The Tail Exponent for Stock Returns in Bursa Malaysia for 2003-2008

NASA Astrophysics Data System (ADS)

Rusli, N. H.; Gopir, G.; Usang, M. D.

2010-07-01

A developed discipline of econophysics that has been introduced is exhibiting the application of mathematical tools that are usually applied to the physical models for the study of financial models. In this study, an analysis of the time series behavior of several blue chip and penny stock companies in Main Market of Bursa Malaysia has been performed. Generally, the basic quantity being used is the relative price changes or is called the stock price returns, contains daily-sampled data from the beginning of 2003 until the end of 2008, containing 1555 trading days recorded. The aim of this paper is to investigate the tail exponent in tails of the distribution for blue chip stocks and penny stocks financial returns in six years period. By using a standard regression method, it is found that the distribution performed double scaling on the log-log plot of the cumulative probability of the normalized returns. Thus we calculate α for a small scale return as well as large scale return. Based on the result obtained, it is found that the power-law behavior for the probability density functions of the stock price absolute returns P(z)˜z-α with values lying inside and outside the Lévy stable regime with values α>2. All the results were discussed in detail.

Analysis of Realized Volatility for Nikkei Stock Average on the Tokyo Stock Exchange

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya; Watanabe, Toshiaki

2016-04-01

We calculate realized volatility of the Nikkei Stock Average (Nikkei225) Index on the Tokyo Stock Exchange and investigate the return dynamics. To avoid the bias on the realized volatility from the non-trading hours issue we calculate realized volatility separately in the two trading sessions, i.e. morning and afternoon, of the Tokyo Stock Exchange and find that the microstructure noise decreases the realized volatility at small sampling frequency. Using realized volatility as a proxy of the integrated volatility we standardize returns in the morning and afternoon sessions and investigate the normality of the standardized returns by calculating variance, kurtosis and 6th moment. We find that variance, kurtosis and 6th moment are consistent with those of the standard normal distribution, which indicates that the return dynamics of the Nikkei Stock Average are well described by a Gaussian random process with time-varying volatility.

The Index cohesive effect on stock market correlations

NASA Astrophysics Data System (ADS)

Shapira, Y.; Kenett, D. Y.; Ben-Jacob, E.

2009-12-01

We present empirical examination and reassessment of the functional role of the market Index, using datasets of stock returns for eight years, by analyzing and comparing the results for two very different markets: 1) the New York Stock Exchange (NYSE), representing a large, mature market, and 2) the Tel Aviv Stock Exchange (TASE), representing a small, young market. Our method includes special collective (holographic) analysis of stock-Index correlations, of nested stock correlations (including the Index as an additional ghost stock) and of bare stock correlations (after subtraction of the Index return from the stocks returns). Our findings verify and strongly substantiate the assumed functional role of the index in the financial system as a cohesive force between stocks, i.e., the correlations between stocks are largely due to the strong correlation between each stock and the Index (the adhesive effect), rather than inter-stock dependencies. The Index adhesive and cohesive effects on the market correlations in the two markets are presented and compared in a reduced 3-D principal component space of the correlation matrices (holographic presentation). The results provide new insights into the interplay between an index and its constituent stocks in TASE-like versus NYSE-like markets.

Modeling the stock price returns volatility using GARCH(1,1) in some Indonesia stock prices

NASA Astrophysics Data System (ADS)

Awalludin, S. A.; Ulfah, S.; Soro, S.

2018-01-01

In the financial field, volatility is one of the key variables to make an appropriate decision. Moreover, modeling volatility is needed in derivative pricing, risk management, and portfolio management. For this reason, this study presented a widely used volatility model so-called GARCH(1,1) for estimating the volatility of daily returns of stock prices of Indonesia from July 2007 to September 2015. The returns can be obtained from stock price by differencing log of the price from one day to the next. Parameters of the model were estimated by Maximum Likelihood Estimation. After obtaining the volatility, natural cubic spline was employed to study the behaviour of the volatility over the period. The result shows that GARCH(1,1) indicate evidence of volatility clustering in the returns of some Indonesia stock prices.

41 CFR 101-27.501 - Eligibility for return.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 2 2010-07-01 2010-07-01 true Eligibility for return. 101-27.501 Section 101-27.501 Public Contracts and Property Management Federal Property Management...-Return of GSA Stock Items § 101-27.501 Eligibility for return. GSA stock items for which no current or...

Dynamics of bid-ask spread return and volatility of the Chinese stock market

NASA Astrophysics Data System (ADS)

Qiu, Tian; Chen, Guang; Zhong, Li-Xin; Wu, Xiao-Run

2012-04-01

The bid-ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation function and the Detrended Fluctuation Analysis (DFA), we find that the spread return is the lack of long-range memory, while the spread volatility is long-range time correlated. Besides, the spread volatilities of different stocks present long-range cross-correlations. Moreover, by applying the Multifractal Detrended Fluctuation Analysis (MF-DFA), the spread return is observed to possess a strong multifractality, which is similar to the dynamics of a variety of financial quantities. Different from the spread return, the spread volatility exhibits a weak multifractal nature.

Sign realized jump risk and the cross-section of stock returns: Evidence from China's stock market.

PubMed

Chao, Youcong; Liu, Xiaoqun; Guo, Shijun

2017-01-01

Using 5-minute high frequency data from the Chinese stock market, we employ a non-parametric method to estimate Fama-French portfolio realized jumps and investigate whether the estimated positive, negative and sign realized jumps could forecast or explain the cross-sectional stock returns. The Fama-MacBeth regression results show that not only have the realized jump components and the continuous volatility been compensated with risk premium, but also that the negative jump risk, the positive jump risk and the sign jump risk, to some extent, could explain the return of the stock portfolios. Therefore, we should pay high attention to the downside tail risk and the upside tail risk.

A quantum anharmonic oscillator model for the stock market

NASA Astrophysics Data System (ADS)

Gao, Tingting; Chen, Yu

2017-02-01

A financially interpretable quantum model is proposed to study the probability distributions of the stock price return. The dynamics of a quantum particle is considered an analog of the motion of stock price. Then the probability distributions of price return can be computed from the wave functions that evolve according to Schrodinger equation. Instead of a harmonic oscillator in previous studies, a quantum anharmonic oscillator is applied to the stock in liquid market. The leptokurtic distributions of price return can be reproduced by our quantum model with the introduction of mixed-state and multi-potential. The trend following dominant market, in which the price return follows a bimodal distribution, is discussed as a specific case of the illiquid market.

Traders' behavioral coupling and market phase transition

NASA Astrophysics Data System (ADS)

Ma, Rong; Zhang, Yin; Li, Honggang

2017-11-01

Traditional economic theory is based on the assumption that traders are completely independent and rational; however, trading behavior in the real market is often coupled by various factors. This paper discusses behavioral coupling based on the stock index in the stock market, focusing on the convergence of traders' behavior, its effect on the correlation of stock returns and market volatility. We find that the behavioral consensus in the stock market, the correlation degree of stock returns, and the market volatility all exhibit significant phase transitions with stronger coupling.

HMO behavior and stock market valuation: what does Wall Street reward and punish?

PubMed

Pauly, M V; Hillman, A L; Furukawa, M F; McCullough, J S

2001-01-01

This article analyzes the variation in returns to owning stock in investor-owned health maintenance organizations (IOHMOs) for the period 1994-1997. The average return (measured by the change in the market value of the stock plus dividends) was close to zero, but returns were positive and high for firms operating in local markets that were and remained less competitive, with large nationwide scope, and with less rapidly growing panels of contracted physicians. Indicators of a firm's strategic direction were abstracted from their annual reports; firms pursuing a merger or acquisition strategy, and those emphasizing a utilization review strategy, showed lower returns than those that did not. Other strategy and market variables were not related to stock market returns over this period, and were also generally not related to price-earnings ratios. This analysis supports the view that competitive HMO markets best constrain profits to investor-owned firms.

Dynamic structure of stock communities: a comparative study between stock returns and turnover rates

NASA Astrophysics Data System (ADS)

Su, Li-Ling; Jiang, Xiong-Fei; Li, Sai-Ping; Zhong, Li-Xin; Ren, Fei

2017-07-01

The detection of community structure in stock market is of theoretical and practical significance for the study of financial dynamics and portfolio risk estimation. We here study the community structures in Chinese stock markets from the aspects of both price returns and turnover rates, by using a combination of the PMFG and infomap methods based on a distance matrix. An empirical study using the overall data set shows that for both returns and turnover rates the largest communities are composed of specific industrial or conceptional sectors and the correlation inside a sector is generally larger than the correlation between different sectors. However, the community structure for turnover rates is more complex than that for returns, which indicates that the interactions between stocks revealed by turnover rates may contain more information. This conclusion is further confirmed by the analysis of the changes in the dynamics of community structures over five sub-periods. Sectors like banks, real estate, health care and New Shanghai take turns to comprise a few of the largest communities in different sub-periods, and more interestingly several specific sectors appear in the communities with different rank orders for returns and turnover rates even in the same sub-period. To better understand their differences, a comparison between the evolution of the returns and turnover rates of the stocks from these sectors is conducted. We find that stock prices only had large changes around important events while turnover rates surged after each of these events relevant to specific sectors, which shows strong evidence that the turnover rates are more susceptible to exogenous shocks than returns and its measurement for community detection may contain more useful information about market structure.

Sign realized jump risk and the cross-section of stock returns: Evidence from China's stock market

PubMed Central

Chao, Youcong; Liu, Xiaoqun; Guo, Shijun

2017-01-01

Using 5-minute high frequency data from the Chinese stock market, we employ a non-parametric method to estimate Fama-French portfolio realized jumps and investigate whether the estimated positive, negative and sign realized jumps could forecast or explain the cross-sectional stock returns. The Fama-MacBeth regression results show that not only have the realized jump components and the continuous volatility been compensated with risk premium, but also that the negative jump risk, the positive jump risk and the sign jump risk, to some extent, could explain the return of the stock portfolios. Therefore, we should pay high attention to the downside tail risk and the upside tail risk. PMID:28771514

Price returns efficiency of the Shanghai A-Shares

NASA Astrophysics Data System (ADS)

Long, Wang Jiang; Jaaman, Saiful Hafizah; Samsudin, Humaida Banu

2014-06-01

Beta measured from the capital asset pricing model (CAPM) is the most widely used risk to estimate expected return. In this paper factors that influence Shanghai A-share stock return based on CAPM are explored and investigated. Price data of 312 companies listed on Shanghai Stock Exchange (SSE) from the year 2000 to 2011 are investigated. This study employed the Fama-MacBeth cross-sectional method to avoid weakness of traditional CAPM. In addition, this study improves the model by adjusting missing data. Findings of this study justifies that systematic risk can explain the portfolios' returns of China SSE stock market.

Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market

PubMed Central

Qiao, Haishu; Xia, Yue; Li, Ying

2016-01-01

This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk. PMID:27257816

Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market.

PubMed

Qiao, Haishu; Xia, Yue; Li, Ying

2016-01-01

This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk.

Tests of nonuniversality of the stock return distributions in an emerging market

NASA Astrophysics Data System (ADS)

Mu, Guo-Hua; Zhou, Wei-Xing

2010-12-01

There is convincing evidence showing that the probability distributions of stock returns in mature markets exhibit power-law tails and both the positive and negative tails conform to the inverse cubic law. It supports the possibility that the tail exponents are universal at least for mature markets in the sense that they do not depend on stock market, industry sector, and market capitalization. We investigate the distributions of intraday returns at different time scales ( Δt=1 , 5, 15, and 30 min) of all the A-share stocks traded in the Chinese stock market, which is the largest emerging market in the world. We find that the returns can be well fitted by the q -Gaussian distribution and the tails have power-law relaxations with the exponents increasing with Δt and being well outside the Lévy stable regime for individual stocks. We provide statistically significant evidence showing that, at small time scales Δt<15min , the exponents logarithmically decrease with the turnover rate and increase with the market capitalization. When Δt>15min , no conclusive evidence is found for a possible dependence of the tail exponent on the turnover rate or the market capitalization. Our findings indicate that the intraday return distributions at small time scales are not universal in emerging stock markets but might be universal at large time scales.

Investor sentiment and stock returns: Evidence from provincial TV audience rating in China

NASA Astrophysics Data System (ADS)

Zhang, Yongjie; Zhang, Yuzhao; Shen, Dehua; Zhang, Wei

2017-01-01

In this paper, we advocate the provincial TV audience rating as the novel proxy for the provincial investor sentiment (PIS) and investigate its relation with stock returns. The empirical results firstly show that the PIS is positively related to stock returns. Secondly, we provide direct evidence on the existence of home bias in China by observing that the provincial correlation coefficient is significantly larger than the cross-provincial correlation coefficient. Finally, the PIS can explain a large proportion of provincial comovement. To sum up, all these findings support the role of the non-traditional information sources in understanding the ;anomalies; in stock market.

The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model

NASA Astrophysics Data System (ADS)

Chen, Cathy W. S.; Yang, Ming Jing; Gerlach, Richard; Jim Lo, H.

2006-07-01

In this paper, we investigate the asymmetric reactions of mean and volatility of stock returns in five major markets to their own local news and the US information via linear and nonlinear models. We introduce a four-regime Double-Threshold GARCH (DTGARCH) model, which allows asymmetry in both the conditional mean and variance equations simultaneously by employing two threshold variables, to analyze the stock markets’ reactions to different types of information (good/bad news) generated from the domestic markets and the US stock market. By applying the four-regime DTGARCH model, this study finds that the interaction between the information of domestic and US stock markets leads to the asymmetric reactions of stock returns and their variability. In addition, this research also finds that the positive autocorrelation reported in the previous studies of financial markets may in fact be mis-specified, and actually due to the local market's positive response to the US stock market.

Rational GARCH model: An empirical test for stock returns

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2017-05-01

We propose a new ARCH-type model that uses a rational function to capture the asymmetric response of volatility to returns, known as the "leverage effect". Using 10 individual stocks on the Tokyo Stock Exchange and two stock indices, we compare the new model with several other asymmetric ARCH-type models. We find that according to the deviance information criterion, the new model ranks first for several stocks. Results show that the proposed new model can be used as an alternative asymmetric ARCH-type model in empirical applications.

Is Log Ratio a Good Value for Measuring Return in Stock Investments?

NASA Astrophysics Data System (ADS)

Ultsch, Alfred

Measuring the rate of return is an important issue for theory and practice of investments in the stock market. A common measure for rate of return is the logarithm of the ratio of successive prices (LogRatio). In this paper it is shown that LogRatio as well as arithmetic return rate (Ratio) have several disadvantages. As an alternative relative differences (RelDiff) are proposed to measure return. The stability against numerical and rounding errors of RelDiff is much better than for LogRatios and Ratio). RelDiff values are identical to LogRatios and Return for small absolutes. The usage of RelDiff maps returns to a finite range. For most subsequent analyses this is a big advantage. The usefulness of the approach is demonstrated on daily return rates of a large set of actual stocks. It is shown that returns can be modeled with a very simple mixture of distributions in great precision using Relative differences.

A wave function for stock market returns

NASA Astrophysics Data System (ADS)

Ataullah, Ali; Davidson, Ian; Tippett, Mark

2009-02-01

The instantaneous return on the Financial Times-Stock Exchange (FTSE) All Share Index is viewed as a frictionless particle moving in a one-dimensional square well but where there is a non-trivial probability of the particle tunneling into the well’s retaining walls. Our analysis demonstrates how the complementarity principle from quantum mechanics applies to stock market prices and of how the wave function presented by it leads to a probability density which exhibits strong compatibility with returns earned on the FTSE All Share Index. In particular, our analysis shows that the probability density for stock market returns is highly leptokurtic with slight (though not significant) negative skewness. Moreover, the moments of the probability density determined under the complementarity principle employed here are all convergent - in contrast to many of the probability density functions on which the received theory of finance is based.

Randomness in denoised stock returns: The case of Moroccan family business companies

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2018-02-01

In this paper, we scrutinize entropy in family business stocks listed on Casablanca stock exchange and market index to assess randomness in their returns. For this purpose, we adopt a novel approach based on combination of stationary wavelet transform and Tsallis entropy for empirical analysis of the return series. The obtained empirical results show strong evidence that their respective entropy functions are characterized by opposite dynamics. Indeed, the information contents of their respective dynamics are statistically and significantly different. Obviously, information on regular events carried by family business returns is more certain, whilst that carried by market returns is uncertain. Such results are definitively useful to understand the nonlinear dynamics on returns on family business companies and those of the market. Without a doubt, they could be helpful for quantitative portfolio managers and investors.

Non-parametric causality detection: An application to social media and financial data

NASA Astrophysics Data System (ADS)

Tsapeli, Fani; Musolesi, Mirco; Tino, Peter

2017-10-01

According to behavioral finance, stock market returns are influenced by emotional, social and psychological factors. Several recent works support this theory by providing evidence of correlation between stock market prices and collective sentiment indexes measured using social media data. However, a pure correlation analysis is not sufficient to prove that stock market returns are influenced by such emotional factors since both stock market prices and collective sentiment may be driven by a third unmeasured factor. Controlling for factors that could influence the study by applying multivariate regression models is challenging given the complexity of stock market data. False assumptions about the linearity or non-linearity of the model and inaccuracies on model specification may result in misleading conclusions. In this work, we propose a novel framework for causal inference that does not require any assumption about a particular parametric form of the model expressing statistical relationships among the variables of the study and can effectively control a large number of observed factors. We apply our method in order to estimate the causal impact that information posted in social media may have on stock market returns of four big companies. Our results indicate that social media data not only correlate with stock market returns but also influence them.

Risk assessment and stock market volatility in the Eurozone: 1986-2014

NASA Astrophysics Data System (ADS)

Menezes, Rui; Oliveira, Álvaro

2015-04-01

This paper studies the stock market return's volatility in the Eurozone as an input for evaluating the market risk. Stock market returns are endogenously determined by long-term interest rate changes and so is the return's conditional variance. The conditional variance is the time-dependent variance of the underlying variable. In other words, it is the variance of the returns measured at each moment t, so it changes through time depending on the specific market structure at each time observation. Thus, a multivariate EGARCH model is proposed to capture the complex nature of this network. By network, in this context, we mean the chain of stock exchanges that co-move and interact in such a way that a shock in one of them propagates up to the other ones (contagion). Previous studies provide evidence that the Eurozone stock exchanges are deeply integrated. The results indicate that asymmetry and leverage effects exist along with fat tails and endogeneity. In-sample and out-of-sample forecasting tests provide clear evidence that the multivariate EGARCH model performs better than the univariate counterpart to predict the behavior of returns both before and after the 2008 crisis.

Respiratory tract disease from thermosetting resins. Study of an outbreak in rubber tire workers.

PubMed

doPico, G A; Rankin, J; Chosy, L W; Reddan, W G; Barbee, R A; Gee, B; Dickie, H A

1975-08-01

An outbreak of upper and lower respiratory tract inflammatory disease and conjunctivitis among synthetic rubber tire workers occurred. The outbreak began after the introduction of a new thermosetting resin, containing resorcinol and a trimere of methylene aminoacetronitrile, into the rubber tire carcass stock formulation. Two hundred ten workers were affected. Characteristically, symptoms improved during periods of sick leave or vacation, recurring upon the workers' return to the plant. Chest radiograms disclosed pneumonic infiltrates in about one fourth of the cases. Pulmonary function studies detected abnormal airways dynamics as well as abnormal diffusing capacity in more than one third of the workers tested. Lung biopsy showed evidence of focal interstitial fibrosis and peribronchiolar and perivascular chronic inflammatory reaction. The illness was ascribed to volatile products released during the manufacture of synthetic rubber tires. The exact chemical nature of these products is unknown.

Multifractals in Western Major STOCK Markets Historical Volatilities in Times of Financial Crisis

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

In this paper, the generalized Hurst exponent is used to investigate multifractal properties of historical volatility (CHV) in stock market price and return series before, during and after 2008 financial crisis. Empirical results from NASDAQ, S&P500, TSE, CAC40, DAX, and FTSE stock market data show that there is strong evidence of multifractal patterns in HV of both price and return series. In addition, financial crisis deeply affected the behavior and degree of multifractality in volatility of Western financial markets at price and return levels.

Association between Stock Market Gains and Losses and Google Searches

PubMed Central

Arditi, Eli; Yechiam, Eldad; Zahavi, Gal

2015-01-01

Experimental studies in the area of Psychology and Behavioral Economics have suggested that people change their search pattern in response to positive and negative events. Using Internet search data provided by Google, we investigated the relationship between stock-specific events and related Google searches. We studied daily data from 13 stocks from the Dow-Jones and NASDAQ100 indices, over a period of 4 trading years. Focusing on periods in which stocks were extensively searched (Intensive Search Periods), we found a correlation between the magnitude of stock returns at the beginning of the period and the volume, peak, and duration of search generated during the period. This relation between magnitudes of stock returns and subsequent searches was considerably magnified in periods following negative stock returns. Yet, we did not find that intensive search periods following losses were associated with more Google searches than periods following gains. Thus, rather than increasing search, losses improved the fit between people’s search behavior and the extent of real-world events triggering the search. The findings demonstrate the robustness of the attentional effect of losses. PMID:26513371

Linear and nonlinear market correlations: Characterizing financial crises and portfolio optimization.

PubMed

Haluszczynski, Alexander; Laut, Ingo; Modest, Heike; Räth, Christoph

2017-12-01

Pearson correlation and mutual information-based complex networks of the day-to-day returns of U.S. S&P500 stocks between 1985 and 2015 have been constructed to investigate the mutual dependencies of the stocks and their nature. We show that both networks detect qualitative differences especially during (recent) turbulent market periods, thus indicating strongly fluctuating interconnections between the stocks of different companies in changing economic environments. A measure for the strength of nonlinear dependencies is derived using surrogate data and leads to interesting observations during periods of financial market crises. In contrast to the expectation that dependencies reduce mainly to linear correlations during crises, we show that (at least in the 2008 crisis) nonlinear effects are significantly increasing. It turns out that the concept of centrality within a network could potentially be used as some kind of an early warning indicator for abnormal market behavior as we demonstrate with the example of the 2008 subprime mortgage crisis. Finally, we apply a Markowitz mean variance portfolio optimization and integrate the measure of nonlinear dependencies to scale the investment exposure. This leads to significant outperformance as compared to a fully invested portfolio.

Linear and nonlinear market correlations: Characterizing financial crises and portfolio optimization

NASA Astrophysics Data System (ADS)

Haluszczynski, Alexander; Laut, Ingo; Modest, Heike; Räth, Christoph

2017-12-01

Pearson correlation and mutual information-based complex networks of the day-to-day returns of U.S. S&P500 stocks between 1985 and 2015 have been constructed to investigate the mutual dependencies of the stocks and their nature. We show that both networks detect qualitative differences especially during (recent) turbulent market periods, thus indicating strongly fluctuating interconnections between the stocks of different companies in changing economic environments. A measure for the strength of nonlinear dependencies is derived using surrogate data and leads to interesting observations during periods of financial market crises. In contrast to the expectation that dependencies reduce mainly to linear correlations during crises, we show that (at least in the 2008 crisis) nonlinear effects are significantly increasing. It turns out that the concept of centrality within a network could potentially be used as some kind of an early warning indicator for abnormal market behavior as we demonstrate with the example of the 2008 subprime mortgage crisis. Finally, we apply a Markowitz mean variance portfolio optimization and integrate the measure of nonlinear dependencies to scale the investment exposure. This leads to significant outperformance as compared to a fully invested portfolio.

The dynamic correlation between policy uncertainty and stock market returns in China

NASA Astrophysics Data System (ADS)

Yang, Miao; Jiang, Zhi-Qiang

2016-11-01

The dynamic correlation is examined between government's policy uncertainty and Chinese stock market returns in the period from January 1995 to December 2014. We find that the stock market is significantly correlated to policy uncertainty based on the results of the Vector Auto Regression (VAR) and Structural Vector Auto Regression (SVAR) models. In contrast, the results of the Dynamic Conditional Correlation Generalized Multivariate Autoregressive Conditional Heteroscedasticity (DCC-MGARCH) model surprisingly show a low dynamic correlation coefficient between policy uncertainty and market returns, suggesting that the fluctuations of each variable are greatly influenced by their values in the preceding period. Our analysis highlights the understanding of the dynamical relationship between stock market and fiscal and monetary policy.

Are stock market returns related to the weather effects? Empirical evidence from Taiwan

NASA Astrophysics Data System (ADS)

Chang, Tsangyao; Nieh, Chien-Chung; Yang, Ming Jing; Yang, Tse-Yu

2006-05-01

In this study, we employ a recently developed econometric technique of the threshold model with the GJR-GARCH process on error terms to investigate the relationships between weather factors and stock market returns in Taiwan using daily data for the period of 1 July 1997-22 October 2003. The major weather factors studied include temperature, humidity, and cloud cover. Our empirical evidence shows that temperature and cloud cover are two important weather factors that affect the stock returns in Taiwan. Our empirical findings further support the previous arguments that advocate the inclusion of economically neutral behavioral variables in asset pricing models. These results also have significant implications for individual investors and financial institutions planning to invest in the Taiwan stock market.

Profitability of Contrarian Strategies in the Chinese Stock Market

PubMed Central

Shi, Huai-Long; Jiang, Zhi-Qiang; Zhou, Wei-Xing

2015-01-01

This paper reexamines the profitability of loser, winner and contrarian portfolios in the Chinese stock market using monthly data of all stocks traded on the Shanghai Stock Exchange and Shenzhen Stock Exchange covering the period from January 1997 to December 2012. We find evidence of short-term and long-term contrarian profitability in the whole sample period when the estimation and holding horizons are 1 month or longer than 12 months and the annualized return of contrarian portfolios increases with the estimation and holding horizons. We perform subperiod analysis and find that the long-term contrarian effect is significant in both bullish and bearish states, while the short-term contrarian effect disappears in bullish states. We compare the performance of contrarian portfolios based on different grouping manners in the estimation period and unveil that decile grouping outperforms quintile grouping and tertile grouping, which is more evident and robust in the long run. Generally, loser portfolios and winner portfolios have positive returns and loser portfolios perform much better than winner portfolios. Both loser and winner portfolios in bullish states perform better than those in the whole sample period. In contrast, loser and winner portfolios have smaller returns in bearish states, in which loser portfolio returns are significant only in the long term and winner portfolio returns become insignificant. These results are robust to the one-month skipping between the estimation and holding periods and for the two stock exchanges. Our findings show that the Chinese stock market is not efficient in the weak form. These findings also have obvious practical implications for financial practitioners. PMID:26368537

Profitability of Contrarian Strategies in the Chinese Stock Market.

PubMed

Shi, Huai-Long; Jiang, Zhi-Qiang; Zhou, Wei-Xing

2015-01-01

This paper reexamines the profitability of loser, winner and contrarian portfolios in the Chinese stock market using monthly data of all stocks traded on the Shanghai Stock Exchange and Shenzhen Stock Exchange covering the period from January 1997 to December 2012. We find evidence of short-term and long-term contrarian profitability in the whole sample period when the estimation and holding horizons are 1 month or longer than 12 months and the annualized return of contrarian portfolios increases with the estimation and holding horizons. We perform subperiod analysis and find that the long-term contrarian effect is significant in both bullish and bearish states, while the short-term contrarian effect disappears in bullish states. We compare the performance of contrarian portfolios based on different grouping manners in the estimation period and unveil that decile grouping outperforms quintile grouping and tertile grouping, which is more evident and robust in the long run. Generally, loser portfolios and winner portfolios have positive returns and loser portfolios perform much better than winner portfolios. Both loser and winner portfolios in bullish states perform better than those in the whole sample period. In contrast, loser and winner portfolios have smaller returns in bearish states, in which loser portfolio returns are significant only in the long term and winner portfolio returns become insignificant. These results are robust to the one-month skipping between the estimation and holding periods and for the two stock exchanges. Our findings show that the Chinese stock market is not efficient in the weak form. These findings also have obvious practical implications for financial practitioners.

What distinguishes individual stocks from the index?

NASA Astrophysics Data System (ADS)

Wagner, F.; Milaković, M.; Alfarano, S.

2010-01-01

Stochastic volatility models decompose the time series of financial returns into the product of a volatility factor and an iid noise factor. Assuming a slow dynamic for the volatility factor, we show via nonparametric tests that both the index as well as its individual stocks share a common volatility factor. While the noise component is Gaussian for the index, individual stock returns turn out to require a leptokurtic noise. Thus we propose a two-component model for stocks, given by the sum of Gaussian noise, which reflects market-wide fluctuations, and Laplacian noise, which incorporates firm-specific factors such as firm profitability or growth performance, both of which are known to be Laplacian distributed. In the case of purely Gaussian noise, the chi-squared probability for the density of individual stock returns is typically on the order of 10-20, while it increases to values of O(1) by adding the Laplace component.

The influences of delay time on the stability of a market model with stochastic volatility

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Mei, Dong-Cheng

2013-02-01

The effects of the delay time on the stability of a market model are investigated, by using a modified Heston model with a cubic nonlinearity and cross-correlated noise sources. These results indicate that: (i) There is an optimal delay time τo which maximally enhances the stability of the stock price under strong demand elasticity of stock price, and maximally reduces the stability of the stock price under weak demand elasticity of stock price; (ii) The cross correlation coefficient of noises and the delay time play an opposite role on the stability for the case of the delay time <τo and the same role for the case of the delay time >τo. Moreover, the probability density function of the escape time of stock price returns, the probability density function of the returns and the correlation function of the returns are compared with other literatures.

Multivariate multiscale entropy of financial markets

NASA Astrophysics Data System (ADS)

Lu, Yunfan; Wang, Jun

2017-11-01

In current process of quantifying the dynamical properties of the complex phenomena in financial market system, the multivariate financial time series are widely concerned. In this work, considering the shortcomings and limitations of univariate multiscale entropy in analyzing the multivariate time series, the multivariate multiscale sample entropy (MMSE), which can evaluate the complexity in multiple data channels over different timescales, is applied to quantify the complexity of financial markets. Its effectiveness and advantages have been detected with numerical simulations with two well-known synthetic noise signals. For the first time, the complexity of four generated trivariate return series for each stock trading hour in China stock markets is quantified thanks to the interdisciplinary application of this method. We find that the complexity of trivariate return series in each hour show a significant decreasing trend with the stock trading time progressing. Further, the shuffled multivariate return series and the absolute multivariate return series are also analyzed. As another new attempt, quantifying the complexity of global stock markets (Asia, Europe and America) is carried out by analyzing the multivariate returns from them. Finally we utilize the multivariate multiscale entropy to assess the relative complexity of normalized multivariate return volatility series with different degrees.

Price-volume multifractal analysis and its application in Chinese stock markets

NASA Astrophysics Data System (ADS)

Yuan, Ying; Zhuang, Xin-tian; Liu, Zhi-ying

2012-06-01

An empirical research on Chinese stock markets is conducted using statistical tools. First, the multifractality of stock price return series, ri(ri=ln(Pt+1)-ln(Pt)) and trading volume variation series, vi(vi=ln(Vt+1)-ln(Vt)) is confirmed using multifractal detrended fluctuation analysis. Furthermore, a multifractal detrended cross-correlation analysis between stock price return and trading volume variation in Chinese stock markets is also conducted. It is shown that the cross relationship between them is also found to be multifractal. Second, the cross-correlation between stock price Pi and trading volume Vi is empirically studied using cross-correlation function and detrended cross-correlation analysis. It is found that both Shanghai stock market and Shenzhen stock market show pronounced long-range cross-correlations between stock price and trading volume. Third, a composite index R based on price and trading volume is introduced. Compared with stock price return series ri and trading volume variation series vi, R variation series not only remain the characteristics of original series but also demonstrate the relative correlation between stock price and trading volume. Finally, we analyze the multifractal characteristics of R variation series before and after three financial events in China (namely, Price Limits, Reform of Non-tradable Shares and financial crisis in 2008) in the whole period of sample to study the changes of stock market fluctuation and financial risk. It is found that the empirical results verified the validity of R.

Quantized expected returns in terms of dividend yield at the money

NASA Astrophysics Data System (ADS)

Dieng, Lamine

2011-03-01

We use the Bachelier (additive model) and the Black-Scholes (multiplicative model) as our models for the stock price movement for an investor who has entered into an America call option contract. We assume the investor to pay certain dividend yield on the expected rate of returns from buying stocks. In this work, we also assume the stock price to be initially in the out of the money state and eventually will move up through at the money state to the deep in the money state where the expected future payoffs and returns are positive for the stock holder. We call a singularity point at the money because the expected payoff vanishes at this point. Then, using martingale, supermartingale and Markov theories we obtain the Bachelier-type of the Black-Scholes and the Black-Scholes equations which we hedge in the limit where the change of the expected payoff of the call option is extremely small. Hence, by comparison we obtain the time-independent Schroedinger equation in Quantum Mechanics. We solve completely the time independent Schroedinger equation for both models to obtain the expected rate of returns and the expected payoffs for the stock holder at the money. We find the expected rate of returns to be quantized in terms of the dividend yield.

Steelhead Supplementation in Idaho Rivers, 2000 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrne, Alan

In 2000, we continued our assessment of the Sawtooth Hatchery steelhead stock to reestablish natural populations in Beaver and Frenchman creeks in the upper Salmon River. We stocked both streams with 15 pair of hatchery adults and estimated the potential smolt production from the 1999 outplant. I estimated that about nine smolts per female could be produced in both streams from the 1999 outplant. The smolt-to-adult return would need to exceed 20% to return two adults at this level of production. In the Red River drainage, we stocked Dworshak hatchery stock fingerlings and smolts, from 1993 to 1999, to assessmore » which life-stage produces more progeny when the adults return to spawn. In 2000, we operated the Red River weir to trap adults that returned from these stockings, but none were caught from either group. We continued to monitor wild steelhead populations in the Lochsa and Selway river drainages. We estimated that 26 wild adult steelhead returned to Fish Creek. This is the lowest adult escapement we have documented (when the weir was intact all spring) since we began monitoring Fish Creek in 1992. I estimated that nearly 25,000 juvenile steelhead migrated out of Fish Creek this year. Juvenile steelhead densities in Lochsa and Selway tributaries were similar to those observed in 1999. In 2000, we obtained funding for a DNA analysis to assess Idaho's steelhead stock structure. We collected fin samples from wild steelhead in 70 streams of the Clearwater, Snake, and Salmon River drainages and from our five hatchery stocks. The DNA analysis was subcontracted to Dr. Jennifer Nielsen, Alaska Biological Science Center, Anchorage, and will be completed in 2001.« less

Asymmetric conditional volatility in international stock markets

NASA Astrophysics Data System (ADS)

Ferreira, Nuno B.; Menezes, Rui; Mendes, Diana A.

2007-08-01

Recent studies show that a negative shock in stock prices will generate more volatility than a positive shock of similar magnitude. The aim of this paper is to appraise the hypothesis under which the conditional mean and the conditional variance of stock returns are asymmetric functions of past information. We compare the results for the Portuguese Stock Market Index PSI 20 with six other Stock Market Indices, namely the SP 500, FTSE 100, DAX 30, CAC 40, ASE 20, and IBEX 35. In order to assess asymmetric volatility we use autoregressive conditional heteroskedasticity specifications known as TARCH and EGARCH. We also test for asymmetry after controlling for the effect of macroeconomic factors on stock market returns using TAR and M-TAR specifications within a VAR framework. Our results show that the conditional variance is an asymmetric function of past innovations raising proportionately more during market declines, a phenomenon known as the leverage effect. However, when we control for the effect of changes in macroeconomic variables, we find no significant evidence of asymmetric behaviour of the stock market returns. There are some signs that the Portuguese Stock Market tends to show somewhat less market efficiency than other markets since the effect of the shocks appear to take a longer time to dissipate.

Multifractal in Volatility of Family Business Stocks Listed on Casablanca STOCK Exchange

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

In this paper, we check for existence of multifractal in volatility of Moroccan family business stock returns and in volatility of Casablanca market index returns based on multifractal detrended fluctuation analysis (MF-DFA) technique. Empirical results show strong evidence of multifractal characteristics in volatility series of both family business stocks and market index. In addition, it is found that small variations in volatility of family business stocks are persistent, whilst small variations in volatility of market index are anti-persistent. However, large variations in family business volatility and market index volatility are both anti-persistent. Furthermore, multifractal spectral analysis based results show strong evidence that volatility in Moroccan family business companies exhibits more multifractality than volatility in the main stock market. These results may provide insightful information for risk managers concerned with family business stocks.

Enhanced index tracking modelling in portfolio optimization

NASA Astrophysics Data System (ADS)

Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin

2013-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

Analysis of portfolio optimization with lot of stocks amount constraint: case study index LQ45

NASA Astrophysics Data System (ADS)

Chin, Liem; Chendra, Erwinna; Sukmana, Agus

2018-01-01

To form an optimum portfolio (in the sense of minimizing risk and / or maximizing return), the commonly used model is the mean-variance model of Markowitz. However, there is no amount of lots of stocks constraint. And, retail investors in Indonesia cannot do short selling. So, in this study we will develop an existing model by adding an amount of lot of stocks and short-selling constraints to get the minimum risk of portfolio with and without any target return. We will analyse the stocks listed in the LQ45 index based on the stock market capitalization. To perform this analysis, we will use Solver that available in Microsoft Excel.

Modeling stock return distributions with a quantum harmonic oscillator

NASA Astrophysics Data System (ADS)

Ahn, K.; Choi, M. Y.; Dai, B.; Sohn, S.; Yang, B.

2017-11-01

We propose a quantum harmonic oscillator as a model for the market force which draws a stock return from short-run fluctuations to the long-run equilibrium. The stochastic equation governing our model is transformed into a Schrödinger equation, the solution of which features “quantized” eigenfunctions. Consequently, stock returns follow a mixed χ distribution, which describes Gaussian and non-Gaussian features. Analyzing the Financial Times Stock Exchange (FTSE) All Share Index, we demonstrate that our model outperforms traditional stochastic process models, e.g., the geometric Brownian motion and the Heston model, with smaller fitting errors and better goodness-of-fit statistics. In addition, making use of analogy, we provide an economic rationale of the physics concepts such as the eigenstate, eigenenergy, and angular frequency, which sheds light on the relationship between finance and econophysics literature.

Analytical study of index-coupled herd behavior in financial markets

NASA Astrophysics Data System (ADS)

Berman, Yonatan; Shapira, Yoash; Schwartz, Moshe

2016-12-01

Herd behavior in financial markets had been investigated extensively in the past few decades. Scholars have argued that the behavioral tendency of traders and investors to follow the market trend, notably reflected in indices both on short and long time scales, is substantially affecting the overall market behavior. Research has also been devoted to revealing these behaviors and characterizing the market herd behavior. In this paper we present a simple herd behavior model for the dynamics of financial variables by introducing a simple coupling mechanism of stock returns to the index return, deriving analytic expressions for statistical properties of the returns. We found that several important phenomena in the stock market, namely the correlations between stock market returns and the exponential decay of short-term autocorrelations, are derived from our model. These phenomena have been given various explanations and theories, with herd market behavior being one of the leading. We conclude that the coupling mechanism, which essentially encapsulates the herd behavior, indeed creates correlation and autocorrelation. We also show that this introduces a time scale to the system, which is the characteristic time lag between a change in the index and its effect on the return of a stock.

Analysis of Realized Volatility in Two Trading Sessionsof the Japanese Stock Market

NASA Astrophysics Data System (ADS)

Takaishi, T.; Chen, T. T.; Zheng, Z.

We analyze realized volatilities constructedusing high-frequency stock data on the Tokyo Stock Exchange. In order to avoid non-trading hours issue in volatility calculations we define two realized volatilities calculated separately in the two trading sessions of the Tokyo Stock Exchange, i.e. morning and afternoon sessions. After calculating the realized volatilities at various sampling frequencies we evaluate the bias from the microstructure noise as a function of sampling frequency. Taking account of the bias to realized volatility we examine returns standardized by realized volatilities and confirm that price returns on the Tokyo Stock Exchange are described approximately by Gaussian time series with time-varying volatility, i.e. consistent with a mixture of distributions hypothesis.

27 CFR 46.231 - Floor stocks tax return.

Code of Federal Regulations, 2012 CFR

2012-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette....28T09, 2009 Floor Stocks Tax Return—Tobacco Products and Cigarette Papers and Tubes, is available for...

27 CFR 46.231 - Floor stocks tax return.

Code of Federal Regulations, 2011 CFR

2011-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette....28T09, 2009 Floor Stocks Tax Return—Tobacco Products and Cigarette Papers and Tubes, is available for...

27 CFR 46.231 - Floor stocks tax return.

Code of Federal Regulations, 2014 CFR

2014-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette....28T09, 2009 Floor Stocks Tax Return—Tobacco Products and Cigarette Papers and Tubes, is available for...

27 CFR 46.231 - Floor stocks tax return.

Code of Federal Regulations, 2013 CFR

2013-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette....28T09, 2009 Floor Stocks Tax Return—Tobacco Products and Cigarette Papers and Tubes, is available for...

27 CFR 46.231 - Floor stocks tax return.

Code of Federal Regulations, 2010 CFR

2010-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette....28T09, 2009 Floor Stocks Tax Return—Tobacco Products and Cigarette Papers and Tubes, is available for...

Hot money and China's stock market volatility: Further evidence using the GARCH-MIDAS model

NASA Astrophysics Data System (ADS)

Wei, Yu; Yu, Qianwen; Liu, Jing; Cao, Yang

2018-02-01

This paper investigates the influence of hot money on the return and volatility of the Chinese stock market using a nonlinear Granger causality test and a new GARCH-class model based on mixed data sampling regression (GARCH-MIDAS). The empirical results suggest that no linear or nonlinear causality exists between the growth rate of hot money and the Chinese stock market return, implying that the Chinese stock market is not driven by hot money and vice versa. However, hot money has a significant positive impact on the long-term volatility of the Chinese stock market. Furthermore, the dependence between the long-term volatility caused by hot money and the total volatility of the Chinese stock market is time-variant, indicating that huge volatilities in the stock market are not always triggered by international speculation capital flow and that Chinese authorities should further focus on more systemic reforms in the trading rules and on effectively regulating the stock market.

Confidence and self-attribution bias in an artificial stock market.

PubMed

Bertella, Mario A; Pires, Felipe R; Rego, Henio H A; Silva, Jonathas N; Vodenska, Irena; Stanley, H Eugene

2017-01-01

Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index-both generated by our model-are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant.

Lead-lag relationships between stock and market risk within linear response theory

NASA Astrophysics Data System (ADS)

Borysov, Stanislav; Balatsky, Alexander

2015-03-01

We study historical correlations and lead-lag relationships between individual stock risks (standard deviation of daily stock returns) and market risk (standard deviation of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over stocks, using historical stock prices from the Standard & Poor's 500 index for 1994-2013. The observed historical dynamics suggests that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when individual stock risks affect market risk and vice versa. This work was supported by VR 621-2012-2983.

Confidence and self-attribution bias in an artificial stock market

PubMed Central

Bertella, Mario A.; Pires, Felipe R.; Rego, Henio H. A.; Vodenska, Irena; Stanley, H. Eugene

2017-01-01

Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index—both generated by our model—are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant. PMID:28231255

Static and dynamic factors in an information-based multi-asset artificial stock market

NASA Astrophysics Data System (ADS)

Ponta, Linda; Pastore, Stefano; Cincotti, Silvano

2018-02-01

An information-based multi-asset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented. In the market, agents trade risky assets in exchange for cash. Beside the amount of cash and of stocks owned, each agent is characterized by sentiments and agents share their sentiments by means of interactions that are determined by sparsely connected networks. A central market maker (clearing house mechanism) determines the price processes for each stock at the intersection of the demand and the supply curves. Single stock price processes exhibit volatility clustering and fat-tailed distribution of returns whereas multivariate price process exhibits both static and dynamic stylized facts, i.e., the presence of static factors and common trends. Static factors are studied making reference to the cross-correlation of returns of different stocks. The common trends are investigated considering the variance-covariance matrix of prices. Results point out that the probability distribution of eigenvalues of the cross-correlation matrix of returns shows the presence of sectors, similar to those observed on real empirical data. As regarding the dynamic factors, the variance-covariance matrix of prices point out a limited number of assets prices series that are independent integrated processes, in close agreement with the empirical evidence of asset price time series of real stock markets. These results remarks the crucial dependence of statistical properties of multi-assets stock market on the agents' interaction structure.

Clustering stocks using partial correlation coefficients

NASA Astrophysics Data System (ADS)

Jung, Sean S.; Chang, Woojin

2016-11-01

A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.

Tick size and stock returns

NASA Astrophysics Data System (ADS)

Onnela, Jukka-Pekka; Töyli, Juuso; Kaski, Kimmo

2009-02-01

Tick size is an important aspect of the micro-structural level organization of financial markets. It is the smallest institutionally allowed price increment, has a direct bearing on the bid-ask spread, influences the strategy of trading order placement in electronic markets, affects the price formation mechanism, and appears to be related to the long-term memory of volatility clustering. In this paper we investigate the impact of tick size on stock returns. We start with a simple simulation to demonstrate how continuous returns become distorted after confining the price to a discrete grid governed by the tick size. We then move on to a novel experimental set-up that combines decimalization pilot programs and cross-listed stocks in New York and Toronto. This allows us to observe a set of stocks traded simultaneously under two different ticks while holding all security-specific characteristics fixed. We then study the normality of the return distributions and carry out fits to the chosen distribution models. Our empirical findings are somewhat mixed and in some cases appear to challenge the simulation results.

Random matrix approach to cross correlations in financial data

NASA Astrophysics Data System (ADS)

Plerou, Vasiliki; Gopikrishnan, Parameswaran; Rosenow, Bernd; Amaral, Luís A.; Guhr, Thomas; Stanley, H. Eugene

2002-06-01

We analyze cross correlations between price fluctuations of different stocks using methods of random matrix theory (RMT). Using two large databases, we calculate cross-correlation matrices C of returns constructed from (i) 30-min returns of 1000 US stocks for the 2-yr period 1994-1995, (ii) 30-min returns of 881 US stocks for the 2-yr period 1996-1997, and (iii) 1-day returns of 422 US stocks for the 35-yr period 1962-1996. We test the statistics of the eigenvalues λi of C against a ``null hypothesis'' - a random correlation matrix constructed from mutually uncorrelated time series. We find that a majority of the eigenvalues of C fall within the RMT bounds [λ-,λ+] for the eigenvalues of random correlation matrices. We test the eigenvalues of C within the RMT bound for universal properties of random matrices and find good agreement with the results for the Gaussian orthogonal ensemble of random matrices-implying a large degree of randomness in the measured cross-correlation coefficients. Further, we find that the distribution of eigenvector components for the eigenvectors corresponding to the eigenvalues outside the RMT bound display systematic deviations from the RMT prediction. In addition, we find that these ``deviating eigenvectors'' are stable in time. We analyze the components of the deviating eigenvectors and find that the largest eigenvalue corresponds to an influence common to all stocks. Our analysis of the remaining deviating eigenvectors shows distinct groups, whose identities correspond to conventionally identified business sectors. Finally, we discuss applications to the construction of portfolios of stocks that have a stable ratio of risk to return.

Return Intervals Approach to Financial Fluctuations

NASA Astrophysics Data System (ADS)

Wang, Fengzhong; Yamasaki, Kazuko; Havlin, Shlomo; Stanley, H. Eugene

Financial fluctuations play a key role for financial markets studies. A new approach focusing on properties of return intervals can help to get better understanding of the fluctuations. A return interval is defined as the time between two successive volatilities above a given threshold. We review recent studies and analyze the 1000 most traded stocks in the US stock markets. We find that the distribution of the return intervals has a well approximated scaling over a wide range of thresholds. The scaling is also valid for various time windows from one minute up to one trading day. Moreover, these results are universal for stocks of different countries, commodities, interest rates as well as currencies. Further analysis shows some systematic deviations from a scaling law, which are due to the nonlinear correlations in the volatility sequence. We also examine the memory in return intervals for different time scales, which are related to the long-term correlations in the volatility. Furthermore, we test two popular models, FIGARCH and fractional Brownian motion (fBm). Both models can catch the memory effect but only fBm shows a good scaling in the return interval distribution.

Portfolio optimization in enhanced index tracking with goal programming approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. Enhanced index tracking aims to generate excess return over the return achieved by the market index without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio to maximize the mean return and minimize the risk. The objective of this paper is to determine the portfolio composition and performance using goal programming approach in enhanced index tracking and comparing it to the market index. Goal programming is a branch of multi-objective optimization which can handle decision problems that involve two different goals in enhanced index tracking, a trade-off between maximizing the mean return and minimizing the risk. The results of this study show that the optimal portfolio with goal programming approach is able to outperform the Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

The pricing effect of the common pattern in firm-level idiosyncratic volatility: Evidence from A-Share stocks of China

NASA Astrophysics Data System (ADS)

Su, Zhi; Shu, Tengjia; Yin, Libo

2018-05-01

Inspired by Herskovic et al. (2016), we investigate the pricing effect of the firm-level common idiosyncratic volatility (CIV) in China's A-Share market. Return tests indicate that lower CIV risk loadings bring higher returns significantly, while the pricing function of market volatility (MV) is inconsistent. Strategy that goes long the highest CIV-beta quintile and short the lowest CIV-beta quintile brings an annualized average return of 5%-7%. Our findings supplement Herskovic et al. (2016) by confirming a significantly negative relationship between CIV and stock returns in a developing market.

26 CFR 1.6039-2 - Statements to persons with respect to whom information is reported.

Code of Federal Regulations, 2010 CFR

2010-04-01

... THE TREASURY (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES Information Returns § 1.6039-2 Statements... incentive stock options under section 6039(b). (1) Every corporation filing a return under § 1.6039-1(a... to any person must be furnished to such person on Form 3921, Exercise of an Incentive Stock Option...

Black-Litterman model on non-normal stock return (Case study four banks at LQ-45 stock index)

NASA Astrophysics Data System (ADS)

Mahrivandi, Rizki; Noviyanti, Lienda; Setyanto, Gatot Riwi

2017-03-01

The formation of the optimal portfolio is a method that can help investors to minimize risks and optimize profitability. One model for the optimal portfolio is a Black-Litterman (BL) model. BL model can incorporate an element of historical data and the views of investors to form a new prediction about the return of the portfolio as a basis for preparing the asset weighting models. BL model has two fundamental problems, the assumption of normality and estimation parameters on the market Bayesian prior framework that does not from a normal distribution. This study provides an alternative solution where the modelling of the BL model stock returns and investor views from non-normal distribution.

A multiscale analysis of stock return co-movements and spillovers: Evidence from Pacific developed markets

NASA Astrophysics Data System (ADS)

Das, Debojyoti; Bhowmik, Puja; Jana, R. K.

2018-07-01

In this paper we examine the stock market co-movement and volatility spillover dynamics in the Pacific developed markets for a period spanning over January 05, 2001 to January 09, 2018. We employ wavelet-based techniques to study the multiscale co-movement dynamics of stock returns. Additionally, we also study the subtleties of volatility spillover of returns among the sample countries. We find that: (a) diversification benefits in these markets are limited due to higher degrees of integration, (b) Pacific developed markets co-move strongly during the periods of financial crisis (i.e. the contagion hypothesis) and (c) higher degree of volatility spills during financial crisis. We believe our study holds significance in the perspective of international portfolio diversification.

Predictability of Bristol Bay, Alaska, sockeye salmon returns one to four years in the future

USGS Publications Warehouse

Adkison, Milo D.; Peterson, R.M.

2000-01-01

Historically, forecast error for returns of sockeye salmon Oncorhynchus nerka to Bristol Bay, Alaska, has been large. Using cross-validation forecast error as our criterion, we selected forecast models for each of the nine principal Bristol Bay drainages. Competing forecast models included stock-recruitment relationships, environmental variables, prior returns of siblings, or combinations of these predictors. For most stocks, we found prior returns of siblings to be the best single predictor of returns; however, forecast accuracy was low even when multiple predictors were considered. For a typical drainage, an 80% confidence interval ranged from one half to double the point forecast. These confidence intervals appeared to be appropriately wide.

Coupling detrended fluctuation analysis of Asian stock markets

NASA Astrophysics Data System (ADS)

Wang, Qizhen; Zhu, Yingming; Yang, Liansheng; Mul, Remco A. H.

2017-04-01

This paper uses the coupling detrended fluctuation analysis (CDFA) method to investigate the multifractal characteristics of four Asian stock markets using three stock indices: stock price returns, trading volumes and the composite index. The results show that coupled correlations exist among the four stock markets and the coupled correlations have multifractal characteristics. We then use the chi square (χ2) test to identify the sources of multifractality. For the different stock indices, the contributions of a single series to multifractality are different. In other words, the contributions of each country to coupled correlations are different. The comparative analysis shows that the research on the combine effect of stock price returns and trading volumes may be more comprehensive than on an individual index. By comparing the strength of multifractality for original data with the residual errors of the vector autoregression (VAR) model, we find that the VAR model could not be used to describe the dynamics of the coupled correlations among four financial time series.

Temporal structure and gain-loss asymmetry for real and artificial stock indices

NASA Astrophysics Data System (ADS)

Siven, Johannes Vitalis; Lins, Jeffrey Todd

2009-11-01

Previous research has shown that for stock indices, the most likely time until a return of a particular size has been observed is longer for gains than for losses. We demonstrate that this so-called gain-loss asymmetry vanishes if the temporal dependence structure is destroyed by scrambling the time series. We also show that an artificial index constructed by a simple average of a number of individual stocks display gain-loss asymmetry—this allows us to explicitly analyze the dependence between the index constituents. We consider mutual information and correlation-based measures and show that the stock returns indeed have a higher degree of dependence in times of market downturns than upturns.

Risk-Adjusted Returns and Stock Market Games.

ERIC Educational Resources Information Center

Kagan, Gary; And Others

1995-01-01

Maintains that stock market games are designed to provide students with a background for investing in securities, especially stocks. Reviews two games used with secondary students, analyzes statistical data from these experiences, and considers weaknesses in the games. (CFR)

Cross-Correlation Asymmetries and Causal Relationships between Stock and Market Risk

PubMed Central

Borysov, Stanislav S.; Balatsky, Alexander V.

2014-01-01

We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard & Poor's 500 index for 1994–2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa. PMID:25162697

Stock-specific migration timing of adult spring-summer Chinook salmon in the Columbia River basin

USGS Publications Warehouse

Keefer, M.L.; Peery, C.A.; Jepson, M.A.; Tolotti, K.R.; Bjornn, T.C.; Stuehrenberg, L.C.

2004-01-01

An understanding of the migration timing patterns of Pacific salmon Oncorhynchus spp. and steelhead O. mykiss is important for managing complex mixed-stock fisheries and preserving genetic and life history diversity. We examined adult return timing for 3,317 radio-tagged fish from 38 stocks of Columbia River basin spring-summer Chinook salmon O. tshawytscha over 5 years. Stock composition varied widely within and between years depending on the strength of influential populations. Most individual stocks migrated at similar times each year relative to overall runs, supporting the hypotheses that run timing is predictable, is at least partially due to genetic adaptation, and can be used to differentiate between some conspecific populations. Arrival timing of both aggregated radio-tagged stocks and annual runs was strongly correlated with river discharge; stocks arrived earlier at Bonneville Dam and at upstream dams in years with low discharge. Migration timing analyses identified many between-stock and between-year differences in anadromous salmonid return behavior and should and managers interested in protection and recovery of evolutionary significant populations.

Cross-correlation asymmetries and causal relationships between stock and market risk.

PubMed

Borysov, Stanislav S; Balatsky, Alexander V

2014-01-01

We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard & Poor's 500 index for 1994-2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa.

Idiosyncratic risk in the Dow Jones Eurostoxx50 Index

NASA Astrophysics Data System (ADS)

Daly, Kevin; Vo, Vinh

2008-07-01

Recent evidence by Campbell et al. [J.Y. Campbell, M. Lettau B.G. Malkiel, Y. Xu, Have individual stocks become more volatile? An empirical exploration of idiosyncratic risk, The Journal of Finance (February) (2001)] shows an increase in firm-level volatility and a decline of the correlation among stock returns in the US. In relation to the Euro-Area stock markets, we find that both aggregate firm-level volatility and average stock market correlation have trended upwards. We estimate a linear model of the market risk-return relationship nested in an EGARCH(1, 1)-M model for conditional second moments. We then show that traditional estimates of the conditional risk-return relationship, that use ex-post excess-returns as the conditioning information set, lead to joint tests of the theoretical model (usually the ICAPM) and of the Efficient Market Hypothesis in its strong form. To overcome this problem we propose alternative measures of expected market risk based on implied volatility extracted from traded option prices and we discuss the conditions under which implied volatility depends solely on expected risk. We then regress market excess-returns on lagged market implied variance computed from implied market volatility to estimate the relationship between expected market excess-returns and expected market risk.We investigate whether, as predicted by the ICAPM, the expected market risk is the main factor in explaining the market risk premium and the latter is independent of aggregate idiosyncratic risk.

76 FR 73752 - Self-Regulatory Organizations; Options Clearing Corporation; Notice of Filing of Amendment No. 2...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-29

... measure the relative total returns of a stock or exchange-traded fund (``ETF'') against another stock or ETF, including where one of the reference ETFs measured by the index is a gold- or silver-based ETF.\\4... reference securities of an underlying relative performance index is an ETF designed to measure the return of...

76 FR 62891 - Self-Regulatory Organizations; Options Clearing Corporation; Notice of Filing of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-11

... relative total returns of a stock or exchange-traded fund (``ETF'') against another stock or ETF, including where one of the reference ETFs measured by the index is a gold- or silver-based ETF.\\3\\ Generally, a... of an underlying relative performance index is an ETF designed to measure the return of gold or...

Financial factor influence on scaling and memory of trading volume in stock market

NASA Astrophysics Data System (ADS)

Li, Wei; Wang, Fengzhong; Havlin, Shlomo; Stanley, H. Eugene

2011-10-01

We study the daily trading volume volatility of 17 197 stocks in the US stock markets during the period 1989-2008 and analyze the time return intervals τ between volume volatilities above a given threshold q. For different thresholds q, the probability density function Pq(τ) scales with mean interval <τ> as Pq(τ)=<τ>-1f(τ/<τ>), and the tails of the scaling function can be well approximated by a power law f(x)˜x-γ. We also study the relation between the form of the distribution function Pq(τ) and several financial factors: stock lifetime, market capitalization, volume, and trading value. We find a systematic tendency of Pq(τ) associated with these factors, suggesting a multiscaling feature in the volume return intervals. We analyze the conditional probability Pq(τ|τ0) for τ following a certain interval τ0, and find that Pq(τ|τ0) depends on τ0 such that immediately following a short (long) return interval a second short (long) return interval tends to occur. We also find indications that there is a long-term correlation in the daily volume volatility. We compare our results to those found earlier for price volatility.

Profitability of simple technical trading rules of Chinese stock exchange indexes

NASA Astrophysics Data System (ADS)

Zhu, Hong; Jiang, Zhi-Qiang; Li, Sai-Ping; Zhou, Wei-Xing

2015-12-01

Although technical trading rules have been widely used by practitioners in financial markets, their profitability still remains controversial. We here investigate the profitability of moving average (MA) and trading range break (TRB) rules by using the Shanghai Stock Exchange Composite Index (SHCI) from May 21, 1992 through December 31, 2013 and Shenzhen Stock Exchange Component Index (SZCI) from April 3, 1991 through December 31, 2013. The t-test is adopted to check whether the mean returns which are conditioned on the trading signals are significantly different from unconditioned returns and whether the mean returns conditioned on the buy signals are significantly different from the mean returns conditioned on the sell signals. We find that TRB rules outperform MA rules and short-term variable moving average (VMA) rules outperform long-term VMA rules. By applying White's Reality Check test and accounting for the data snooping effects, we find that the best trading rule outperforms the buy-and-hold strategy when transaction costs are not taken into consideration. Once transaction costs are included, trading profits will be eliminated completely. Our analysis suggests that simple trading rules like MA and TRB cannot beat the standard buy-and-hold strategy for the Chinese stock exchange indexes.

The dynamic conditional relationship between stock market returns and implied volatility

NASA Astrophysics Data System (ADS)

Park, Sung Y.; Ryu, Doojin; Song, Jeongseok

2017-09-01

Using the dynamic conditional correlation multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) model, we empirically examine the dynamic relationship between stock market returns (KOSPI200 returns) and implied volatility (VKOSPI), as well as their statistical mechanics, in the Korean market, a representative and leading emerging market. We consider four macroeconomic variables (exchange rates, risk-free rates, term spreads, and credit spreads) as potential determinants of the dynamic conditional correlation between returns and volatility. Of these macroeconomic variables, the change in exchange rates has a significant impact on the dynamic correlation between KOSPI200 returns and the VKOSPI, especially during the recent financial crisis. We also find that the risk-free rate has a marginal effect on this dynamic conditional relationship.

Do Earthquakes Shake Stock Markets?

PubMed Central

2015-01-01

This paper examines how major earthquakes affected the returns and volatility of aggregate stock market indices in thirty-five financial markets over the last twenty years. Results show that global financial markets are resilient to shocks caused by earthquakes even if these are domestic. Our analysis reveals that, in a few instances, some macroeconomic variables and earthquake characteristics (gross domestic product per capita, trade openness, bilateral trade flows, earthquake magnitude, a tsunami indicator, distance to the epicenter, and number of fatalities) mediate the impact of earthquakes on stock market returns, resulting in a zero net effect. However, the influence of these variables is market-specific, indicating no systematic pattern across global capital markets. Results also demonstrate that stock market volatility is unaffected by earthquakes, except for Japan. PMID:26197482

Estimating time-varying conditional correlations between stock and foreign exchange markets

NASA Astrophysics Data System (ADS)

Tastan, Hüseyin

2006-02-01

This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

Do Earthquakes Shake Stock Markets?

PubMed

Ferreira, Susana; Karali, Berna

2015-01-01

This paper examines how major earthquakes affected the returns and volatility of aggregate stock market indices in thirty-five financial markets over the last twenty years. Results show that global financial markets are resilient to shocks caused by earthquakes even if these are domestic. Our analysis reveals that, in a few instances, some macroeconomic variables and earthquake characteristics (gross domestic product per capita, trade openness, bilateral trade flows, earthquake magnitude, a tsunami indicator, distance to the epicenter, and number of fatalities) mediate the impact of earthquakes on stock market returns, resulting in a zero net effect. However, the influence of these variables is market-specific, indicating no systematic pattern across global capital markets. Results also demonstrate that stock market volatility is unaffected by earthquakes, except for Japan.

Correlation based networks of equity returns sampled at different time horizons

NASA Astrophysics Data System (ADS)

Tumminello, M.; di Matteo, T.; Aste, T.; Mantegna, R. N.

2007-01-01

We investigate the planar maximally filtered graphs of the portfolio of the 300 most capitalized stocks traded at the New York Stock Exchange during the time period 2001 2003. Topological properties such as the average length of shortest paths, the betweenness and the degree are computed on different planar maximally filtered graphs generated by sampling the returns at different time horizons ranging from 5 min up to one trading day. This analysis confirms that the selected stocks compose a hierarchical system progressively structuring as the sampling time horizon increases. Finally, a cluster formation, associated to economic sectors, is quantitatively investigated.

A causality between fund performance and stock market

NASA Astrophysics Data System (ADS)

Kim, Ho-Yong; Kwon, Okyu; Oh, Gabjin

2016-02-01

We investigate whether the characteristic fund performance indicators (FPI), such as the fund return, the Net asset value (NAV) and the cash flow, are correlated with the asset price movement using information flows estimated by the Granger causality test. First, we find that the information flow of FPI is most sensitive to extreme events of the Korean stock market, which include negative events such as the sub-prime crisis and the impact of QE (quantitative easing) by the US subprime and Europe financial crisis as well as the positive events of the golden period of Korean Composite Stock Price Index (KOSPI), except for the fund cash flow. Second, both the fund return and the NAV exhibit significant correlations with the KOSPI, whereas the cash flow is not correlated with the stock market. This result suggests that the information resulting from the ability of the fund manager should influence stock market. Finally, during market crisis period, information flows between FPI and the Korean stock market are significantly positively correlated with the market volatility.

Multiscale multifractal DCCA and complexity behaviors of return intervals for Potts price model

NASA Astrophysics Data System (ADS)

Wang, Jie; Wang, Jun; Stanley, H. Eugene

2018-02-01

To investigate the characteristics of extreme events in financial markets and the corresponding return intervals among these events, we use a Potts dynamic system to construct a random financial time series model of the attitudes of market traders. We use multiscale multifractal detrended cross-correlation analysis (MM-DCCA) and Lempel-Ziv complexity (LZC) perform numerical research of the return intervals for two significant China's stock market indices and for the proposed model. The new MM-DCCA method is based on the Hurst surface and provides more interpretable cross-correlations of the dynamic mechanism between different return interval series. We scale the LZC method with different exponents to illustrate the complexity of return intervals in different scales. Empirical studies indicate that the proposed return intervals from the Potts system and the real stock market indices hold similar statistical properties.

Sector Identification in a Set of Stock Return Time Series Traded at the London Stock Exchange

NASA Astrophysics Data System (ADS)

Coronnello, C.; Tumminello, M.; Lillo, F.; Micciche, S.; Mantegna, R. N.

2005-09-01

We compare some methods recently used in the literature to detect the existence of a certain degree of common behavior of stock returns belonging to the same economic sector. Specifically, we discuss methods based on random matrix theory and hierarchical clustering techniques. We apply these methods to a portfolio of stocks traded at the London Stock Exchange. The investigated time series are recorded both at a daily time horizon and at a 5-minute time horizon. The correlation coefficient matrix is very different at different time horizons confirming that more structured correlation coefficient matrices are observed for long time horizons. All the considered methods are able to detect economic information and the presence of clusters characterized by the economic sector of stocks. However, different methods present a different degree of sensitivity with respect to different sectors. Our comparative analysis suggests that the application of just a single method could not be able to extract all the economic information present in the correlation coefficient matrix of a stock portfolio.

Stochastic GARCH dynamics describing correlations between stocks

NASA Astrophysics Data System (ADS)

Prat-Ortega, G.; Savel'ev, S. E.

2014-09-01

The ARCH and GARCH processes have been successfully used for modelling price dynamics such as stock returns or foreign exchange rates. Analysing the long range correlations between stocks, we propose a model, based on the GARCH process, which is able to describe the main characteristics of the stock price correlations, including the mean, variance, probability density distribution and the noise spectrum.

Comparable Stocks, Boundedly Rational Stock Markets and IPO Entry Rates

PubMed Central

Chok, Jay; Qian, Jifeng

2013-01-01

In this study, we examine how initial public offerings (IPO) entry rates are affected when stock markets are boundedly rational and IPO firms infer information from their counterparts in the market. We hypothesize a curvilinear relationship between the number of comparable stocks and initial public offerings (IPO) entry rates into the NASDAQ Stock Exchange. Furthermore, we argue that trading volume and changes in stock returns partially mediates the relationship between the number of comparable stocks and IPO entry rates. The statistical evidence provides strong support for the hypotheses. PMID:23690924

Comparable stocks, boundedly rational stock markets and IPO entry rates.

PubMed

Chok, Jay; Qian, Jifeng

2013-01-01

In this study, we examine how initial public offerings (IPO) entry rates are affected when stock markets are boundedly rational and IPO firms infer information from their counterparts in the market. We hypothesize a curvilinear relationship between the number of comparable stocks and initial public offerings (IPO) entry rates into the NASDAQ Stock Exchange. Furthermore, we argue that trading volume and changes in stock returns partially mediates the relationship between the number of comparable stocks and IPO entry rates. The statistical evidence provides strong support for the hypotheses.

Short-term market reaction after trading halts in Chinese stock market

NASA Astrophysics Data System (ADS)

Xu, Hai-Chuan; Zhang, Wei; Liu, Yi-Fang

2014-05-01

In this paper, we study the dynamics of absolute return, trading volume and bid-ask spread after the trading halts using high-frequency data from the Shanghai Stock Exchange. We deal with all three types of trading halts, namely intraday halts, one-day halts and inter-day halts, of 203 stocks in Shanghai Stock Exchange from August 2009 to 2011. We find that absolute return, trading volume, and in case of bid-ask spread around intraday halts share the same pattern with a sharp peak and a power law relaxation after that. While for different types of trading halts, the peaks’ height and the relaxation exponents are different. From the perspective of halt reasons or halt durations, the relaxation exponents of absolute return after inter-day halts are larger than those after intraday halts and one-day halts, which implies that inter-day halts are most effective. From the perspective of price trends, the relaxation exponents of excess absolute return and excess volume for positive events are larger than those for negative events in case of intraday halts and one-day halts, implying that positive events are more effective than negative events for intraday halts and one-day halts. In contrast, negative events are more effective than positive events for inter-day halts.

STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS*

PubMed Central

HUDOMIET, PÉTER; KÉZDI, GÁBOR; WILLIS, ROBERT J.

2011-01-01

SUMMARY This paper utilizes data on subjective probabilities to study the impact of the stock market crash of 2008 on households’ expectations about the returns on the stock market index. We use data from the Health and Retirement Study that was fielded in February 2008 through February 2009. The effect of the crash is identified from the date of the interview, which is shown to be exogenous to previous stock market expectations. We estimate the effect of the crash on the population average of expected returns, the population average of the uncertainty about returns (subjective standard deviation), and the cross-sectional heterogeneity in expected returns (disagreement). We show estimates from simple reduced-form regressions on probability answers as well as from a more structural model that focuses on the parameters of interest and separates survey noise from relevant heterogeneity. We find a temporary increase in the population average of expectations and uncertainty right after the crash. The effect on cross-sectional heterogeneity is more significant and longer lasting, which implies substantial long-term increase in disagreement. The increase in disagreement is larger among the stockholders, the more informed, and those with higher cognitive capacity, and disagreement co-moves with trading volume and volatility in the market. PMID:21547244

Daily stock index return for the Canadian, UK, and US equity markets, compiled by Morgan Stanley Capital International, obtained from Datastream.

PubMed

Li, Leon

2018-02-01

The data presented in this article are related to the research article entitled "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation. North American Journal of Economics and Finance, 40, 116-135. doi:10.1016/j.najef.2017.02.006 (Li, 2017) [1]. Data on daily stock index return for the Canadian, UK, and US equity markets, as compiled by Morgan Stanley Capital International, are provided in this paper. The country indices comprise at least 80% of the stock market capitalization of each country. The data cover the period from January 1, 1990, through September 8, 2016, and include 6963 observations. All stock prices are stated in dollars.

Comparison between goal programming and cointegration approaches in enhanced index tracking

NASA Astrophysics Data System (ADS)

Lam, Weng Siew; Jamaan, Saiful Hafizah Hj.

2013-04-01

Index tracking is a popular form of passive fund management in stock market. Passive management is a buy-and-hold strategy that aims to achieve rate of return similar to the market return. Index tracking problem is a problem of reproducing the performance of a stock market index, without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio that minimizes risk or tracking error. An improved index tracking (enhanced index tracking) is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the tracking error. Enhanced index tracking aims to generate excess return over the return achieved by the index. The objective of this study is to compare the portfolio compositions and performances by using two different approaches in enhanced index tracking problem, which are goal programming and cointegration. The result of this study shows that the optimal portfolios for both approaches are able to outperform the Malaysia market index which is Kuala Lumpur Composite Index. Both approaches give different optimal portfolio compositions. Besides, the cointegration approach outperforms the goal programming approach because the cointegration approach gives higher mean return and lower risk or tracking error. Therefore, the cointegration approach is more appropriate for the investors in Malaysia.

26 CFR 1.1081-11 - Records to be kept and information to be filed with returns.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., determined immediately before the exchange, of any stock or securities transferred by the significant holder... or exchange, of the stock, securities or other property (including money) received by the significant... the distribution or exchange, of the stock, securities, or other property (including money...

Modeling stock price dynamics by continuum percolation system and relevant complex systems analysis

NASA Astrophysics Data System (ADS)

Xiao, Di; Wang, Jun

2012-10-01

The continuum percolation system is developed to model a random stock price process in this work. Recent empirical research has demonstrated various statistical features of stock price changes, the financial model aiming at understanding price fluctuations needs to define a mechanism for the formation of the price, in an attempt to reproduce and explain this set of empirical facts. The continuum percolation model is usually referred to as a random coverage process or a Boolean model, the local interaction or influence among traders is constructed by the continuum percolation, and a cluster of continuum percolation is applied to define the cluster of traders sharing the same opinion about the market. We investigate and analyze the statistical behaviors of normalized returns of the price model by some analysis methods, including power-law tail distribution analysis, chaotic behavior analysis and Zipf analysis. Moreover, we consider the daily returns of Shanghai Stock Exchange Composite Index from January 1997 to July 2011, and the comparisons of return behaviors between the actual data and the simulation data are exhibited.

Stylized facts in internal rates of return on stock index and its derivative transactions

NASA Astrophysics Data System (ADS)

Pichl, Lukáš; Kaizoji, Taisei; Yamano, Takuya

2007-08-01

Universal features in stock markets and their derivative markets are studied by means of probability distributions in internal rates of return on buy and sell transaction pairs. Unlike the stylized facts in normalized log returns, the probability distributions for such single asset encounters incorporate the time factor by means of the internal rate of return, defined as the continuous compound interest. Resulting stylized facts are shown in the probability distributions derived from the daily series of TOPIX, S & P 500 and FTSE 100 index close values. The application of the above analysis to minute-tick data of NIKKEI 225 and its futures market, respectively, reveals an interesting difference in the behavior of the two probability distributions, in case a threshold on the minimal duration of the long position is imposed. It is therefore suggested that the probability distributions of the internal rates of return could be used for causality mining between the underlying and derivative stock markets. The highly specific discrete spectrum, which results from noise trader strategies as opposed to the smooth distributions observed for fundamentalist strategies in single encounter transactions may be useful in deducing the type of investment strategy from trading revenues of small portfolio investors.

Foraging under conditions of short-term exploitative competition: the case of stock traders.

PubMed

Saavedra, Serguei; Malmgren, R Dean; Switanek, Nicholas; Uzzi, Brian

2013-03-22

Theory purports that animal foraging choices evolve to maximize returns, such as net energy intake. Empirical research in both human and non-human animals reveals that individuals often attend to the foraging choices of their competitors while making their own foraging choices. Owing to the complications of gathering field data or constructing experiments, however, broad facts relating theoretically optimal and empirically realized foraging choices are only now emerging. Here, we analyse foraging choices of a cohort of professional day traders who must choose between trading the same stock multiple times in a row--patch exploitation--or switching to a different stock--patch exploration--with potentially higher returns. We measure the difference between a trader's resource intake and the competitors' expected intake within a short period of time--a difference we call short-term comparative returns. We find that traders' choices can be explained by foraging heuristics that maximize their daily short-term comparative returns. However, we find no one-best relationship between different trading choices and net income intake. This suggests that traders' choices can be short-term win oriented and, paradoxically, maybe maladaptive for absolute market returns.

The Effect of Subjective Risk Attitudes and Overconfidence on Risk Taking Behaviors: A Experimental Study Based on Traders of the Chinese Stock Market

NASA Astrophysics Data System (ADS)

Chen, Qi-An; Xiao, Yinghong; Chen, Hui; Chen, Liang

Our research analyzes the effect of the traders’ subjective risk attitude, optimism and overconfidence on their risk taking behaviors on the Chinese Stock Market by experimental study method. We find that investors’ risk taking behavior is significantly affected by their subjective risk attitude, optimism and overconfidence. Our results also argue that the objective return and volatility of stock are not as good predictors of risk taking behavior as subjective risk and return measures. Moreover, we illustrate that overconfidence and optimism have an significant impact on risk taking behavior In line with theoretical models.

Efficient Portfolios of the Energy Technologies

NASA Astrophysics Data System (ADS)

Nikonov, Oleg I.; Medvedeva, Marina A.

2011-09-01

The goal of the research is to apply the methods of Portfolio Theory to a set of technologies instead of to a set of securities on a stock market (as it is the case in the original model). Assets on the stock market are objects that have risk and return, parameters that depend on uncertain factors and thus are uncertain. The returns from the use of technologies also depend on uncertain factors and thus each technology has a certain amount of risk. The simultaneous use of technologies could diversify the risks that are associated with technologies just the same way as diversification works on the stock market.

26 CFR 1.6045-1T - Returns of information of brokers and barter exchanges (temporary).

Code of Federal Regulations, 2014 CFR

2014-04-01

... paragraph (g)(1)(i) of this section. Therefore, unless X is an FFI (as defined in § 1.1471-1(b)(47)) that is... (B) A sale with respect to which a return is not required by applying the rules of § 1.6049-4(c)(4... a stock transfer agent (as described in § 1.6045-1(b)(iv)) with respect to a redemption of stock of...

Quantifying the cross-sectional relationship between online sentiment and the skewness of stock returns

NASA Astrophysics Data System (ADS)

Shen, Dehua; Liu, Lanbiao; Zhang, Yongjie

2018-01-01

The constantly increasing utilization of social media as the alternative information channel, e.g., Twitter, provides us a unique opportunity to investigate the dynamics of the financial market. In this paper, we employ the daily happiness sentiment extracted from Twitter as the proxy for the online sentiment dynamics and investigate its association with the skewness of stock returns of 26 international stock market index returns. The empirical results show that: (1) by dividing the daily happiness sentiment into quintiles from the least to the most happiness days, the skewness of the Most-happiness subgroup is significantly larger than that of the Least-happiness subgroup. Besides, there exist significant differences in any pair of subgroups; (2) in an event study methodology, we further show that the skewness around the highest happiness days is significantly larger than the skewness around the lowest happiness days.

Long memory of abnormal investor attention and the cross-correlations between abnormal investor attention and trading volume, volatility respectively

NASA Astrophysics Data System (ADS)

Fan, Xiaoqian; Yuan, Ying; Zhuang, Xintian; Jin, Xiu

2017-03-01

Taking Baidu Index as a proxy for abnormal investor attention (AIA), the long memory property in the AIA of Shanghai Stock Exchange (SSE) 50 Index component stocks was empirically investigated using detrended fluctuation analysis (DFA) method. The results show that abnormal investor attention is power-law correlated with Hurst exponents between 0.64 and 0.98. Furthermore, the cross-correlations between abnormal investor attention and trading volume, volatility respectively are studied using detrended cross-correlation analysis (DCCA) and the DCCA cross-correlation coefficient (ρDCCA). The results suggest that there are positive correlations between AIA and trading volume, volatility respectively. In addition, the correlations for trading volume are in general higher than the ones for volatility. By carrying on rescaled range analysis (R/S) and rolling windows analysis, we find that the results mentioned above are effective and significant.

26 CFR 1.338-8 - Asset and stock consistency.

Code of Federal Regulations, 2010 CFR

2010-04-01

... election under section 338 is deemed made or required with respect to target or any target affiliate... target during the target consistency period and target is a subsidiary in a consolidated group. In such a... consolidated return regulations in the basis of target stock and may reduce gain from the sale of the stock...

26 CFR 1.338-8 - Asset and stock consistency.

Code of Federal Regulations, 2011 CFR

2011-04-01

... election under section 338 is deemed made or required with respect to target or any target affiliate... target during the target consistency period and target is a subsidiary in a consolidated group. In such a... consolidated return regulations in the basis of target stock and may reduce gain from the sale of the stock...

26 CFR 1.304-2 - Acquisition by related corporation (other than subsidiary).

Code of Federal Regulations, 2010 CFR

2010-04-01

... the issuing corporation and not to his ownership of stock in the acquiring corporation (except for... corporation (other than subsidiary). (a) If a corporation, in return for property, acquires stock of another corporation from one or more persons, and the person or persons from whom the stock was acquired were in...

A multi-assets artificial stock market with zero-intelligence traders

NASA Astrophysics Data System (ADS)

Ponta, L.; Raberto, M.; Cincotti, S.

2011-01-01

In this paper, a multi-assets artificial financial market populated by zero-intelligence traders with finite financial resources is presented. The market is characterized by different types of stocks representing firms operating in different sectors of the economy. Zero-intelligence traders follow a random allocation strategy which is constrained by finite resources, past market volatility and allocation universe. Within this framework, stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Moreover, the cross-correlations between returns of different stocks are studied using methods of random matrix theory. The probability distribution of eigenvalues of the cross-correlation matrix shows the presence of outliers, similar to those recently observed on real data for business sectors. It is worth noting that business sectors have been recovered in our framework without dividends as only consequence of random restrictions on the allocation universe of zero-intelligence traders. Furthermore, in the presence of dividend-paying stocks and in the case of cash inflow added to the market, the artificial stock market points out the same structural results obtained in the simulation without dividends. These results suggest a significative structural influence on statistical properties of multi-assets stock market.

A spring-block analogy for the dynamics of stock indexes

NASA Astrophysics Data System (ADS)

Sándor, Bulcsú; Néda, Zoltán

2015-06-01

A spring-block chain placed on a running conveyor belt is considered for modeling stylized facts observed in the dynamics of stock indexes. Individual stocks are modeled by the blocks, while the stock-stock correlations are introduced via simple elastic forces acting in the springs. The dragging effect of the moving belt corresponds to the expected economic growth. The spring-block system produces collective behavior and avalanche like phenomena, similar to the ones observed in stock markets. An artificial index is defined for the spring-block chain, and its dynamics is compared with the one measured for the Dow Jones Industrial Average. For certain parameter regions the model reproduces qualitatively well the dynamics of the logarithmic index, the logarithmic returns, the distribution of the logarithmic returns, the avalanche-size distribution and the distribution of the investment horizons. A noticeable success of the model is that it is able to account for the gain-loss asymmetry observed in the inverse statistics. Our approach has mainly a pedagogical value, bridging between a complex socio-economic phenomena and a basic (mechanical) model in physics.

Value-at-Risk forecasts by a spatiotemporal model in Chinese stock market

NASA Astrophysics Data System (ADS)

Gong, Pu; Weng, Yingliang

2016-01-01

This paper generalizes a recently proposed spatial autoregressive model and introduces a spatiotemporal model for forecasting stock returns. We support the view that stock returns are affected not only by the absolute values of factors such as firm size, book-to-market ratio and momentum but also by the relative values of factors like trading volume ranking and market capitalization ranking in each period. This article studies a new method for constructing stocks' reference groups; the method is called quartile method. Applying the method empirically to the Shanghai Stock Exchange 50 Index, we compare the daily volatility forecasting performance and the out-of-sample forecasting performance of Value-at-Risk (VaR) estimated by different models. The empirical results show that the spatiotemporal model performs surprisingly well in terms of capturing spatial dependences among individual stocks, and it produces more accurate VaR forecasts than the other three models introduced in the previous literature. Moreover, the findings indicate that both allowing for serial correlation in the disturbances and using time-varying spatial weight matrices can greatly improve the predictive accuracy of a spatial autoregressive model.

The synchronicity between the stock and the stock index via information in market

NASA Astrophysics Data System (ADS)

Gao, Hai-Ling; Li, Jiang-Cheng; Guo, Wei; Mei, Dong-Cheng

2018-02-01

The synchronicity between the stock and the stock-index in a market system is investigated. The results show that: (i) the synchronicity between the stock and the stock-index increases with the rising degree of market information capitalized into stock prices in certain range; (ii) the synchronicity decreases for large firm-specific information; (iii) the stock return synchronicity is small compared to the big noise trading, however the variance noise facilitates the synchronization within the tailored realms. These findings may be helpful in understanding the effect of market information on synchronicity, especially for the response of firm-specific information and noise trading to synchronicity.

On The Value at Risk Using Bayesian Mixture Laplace Autoregressive Approach for Modelling the Islamic Stock Risk Investment

NASA Astrophysics Data System (ADS)

Miftahurrohmah, Brina; Iriawan, Nur; Fithriasari, Kartika

2017-06-01

Stocks are known as the financial instruments traded in the capital market which have a high level of risk. Their risks are indicated by their uncertainty of their return which have to be accepted by investors in the future. The higher the risk to be faced, the higher the return would be gained. Therefore, the measurements need to be made against the risk. Value at Risk (VaR) as the most popular risk measurement method, is frequently ignore when the pattern of return is not uni-modal Normal. The calculation of the risks using VaR method with the Normal Mixture Autoregressive (MNAR) approach has been considered. This paper proposes VaR method couple with the Mixture Laplace Autoregressive (MLAR) that would be implemented for analysing the first three biggest capitalization Islamic stock return in JII, namely PT. Astra International Tbk (ASII), PT. Telekomunikasi Indonesia Tbk (TLMK), and PT. Unilever Indonesia Tbk (UNVR). Parameter estimation is performed by employing Bayesian Markov Chain Monte Carlo (MCMC) approaches.

A mini-review on econophysics: Comparative study of Chinese and western financial markets

NASA Astrophysics Data System (ADS)

Zheng, Bo; Jiang, Xiong-Fei; Ni, Peng-Yun

2014-07-01

We present a review of our recent research in econophysics, and focus on the comparative study of Chinese and western financial markets. By virtue of concepts and methods in statistical physics, we investigate the time correlations and spatial structure of financial markets based on empirical high-frequency data. We discover that the Chinese stock market shares common basic properties with the western stock markets, such as the fat-tail probability distribution of price returns, the long-range auto-correlation of volatilities, and the persistence probability of volatilities, while it exhibits very different higher-order time correlations of price returns and volatilities, spatial correlations of individual stock prices, and large-fluctuation dynamic behaviors. Furthermore, multi-agent-based models are developed to simulate the microscopic interaction and dynamic evolution of the stock markets.

Evidence of increment of efficiency of the Mexican Stock Market through the analysis of its variations

NASA Astrophysics Data System (ADS)

Coronel-Brizio, H. F.; Hernández-Montoya, A. R.; Huerta-Quintanilla, R.; Rodríguez-Achach, M.

2007-07-01

It is well known that there exist statistical and structural differences between the stock markets of developed and emerging countries. In this work, and in order to find out if the efficiency of the Mexican Stock Market has been changing over time, we have performed and compared several analyses of the variations of the Mexican Stock Market index (IPC) and Dow Jones industrial average index (DJIA) for different periods of their historical daily data. We have analyzed the returns autocorrelation function (ACF) and used detrended fluctuation analysis (DFA) to study returns variations. We also analyze the volatility, mean value and standard deviation of both markets and compare their evolution. We conclude from the overall result of these studies, that they show compelling evidence of the increment of efficiency of the Mexican Stock Market over time. The data samples analyzed here, correspond to daily values of the IPC and DJIA for the period 10/30/1978-02/28/2006.

Detrended cross-correlations between returns, volatility, trading activity, and volume traded for the stock market companies

NASA Astrophysics Data System (ADS)

Rak, Rafał; Drożdż, Stanisław; Kwapień, Jarosław; Oświȩcimka, Paweł

2015-11-01

We consider a few quantities that characterize trading on a stock market in a fixed time interval: logarithmic returns, volatility, trading activity (i.e., the number of transactions), and volume traded. We search for the power-law cross-correlations among these quantities aggregated over different time units from 1 min to 10 min. Our study is based on empirical data from the American stock market consisting of tick-by-tick recordings of 31 stocks listed in Dow Jones Industrial Average during the years 2008-2011. Since all the considered quantities except the returns show strong daily patterns related to the variable trading activity in different parts of a day, which are the most evident in the autocorrelation function, we remove these patterns by detrending before we proceed further with our study. We apply the multifractal detrended cross-correlation analysis with sign preserving (MFCCA) and show that the strongest power-law cross-correlations exist between trading activity and volume traded, while the weakest ones exist (or even do not exist) between the returns and the remaining quantities. We also show that the strongest cross-correlations are carried by those parts of the signals that are characterized by large and medium variance. Our observation that the most convincing power-law cross-correlations occur between trading activity and volume traded reveals the existence of strong fractal-like coupling between these quantities.

Probability distribution of financial returns in a model of multiplicative Brownian motion with stochastic diffusion coefficient

NASA Astrophysics Data System (ADS)

Silva, Antonio

2005-03-01

It is well-known that the mathematical theory of Brownian motion was first developed in the Ph. D. thesis of Louis Bachelier for the French stock market before Einstein [1]. In Ref. [2] we studied the so-called Heston model, where the stock-price dynamics is governed by multiplicative Brownian motion with stochastic diffusion coefficient. We solved the corresponding Fokker-Planck equation exactly and found an analytic formula for the time-dependent probability distribution of stock price changes (returns). The formula interpolates between the exponential (tent-shaped) distribution for short time lags and the Gaussian (parabolic) distribution for long time lags. The theoretical formula agrees very well with the actual stock-market data ranging from the Dow-Jones index [2] to individual companies [3], such as Microsoft, Intel, etc. [] [1] Louis Bachelier, ``Th'eorie de la sp'eculation,'' Annales Scientifiques de l''Ecole Normale Sup'erieure, III-17:21-86 (1900).[] [2] A. A. Dragulescu and V. M. Yakovenko, ``Probability distribution of returns in the Heston model with stochastic volatility,'' Quantitative Finance 2, 443--453 (2002); Erratum 3, C15 (2003). [cond-mat/0203046] [] [3] A. C. Silva, R. E. Prange, and V. M. Yakovenko, ``Exponential distribution of financial returns at mesoscopic time lags: a new stylized fact,'' Physica A 344, 227--235 (2004). [cond-mat/0401225

Evidence of Large Fluctuations of Stock Return and Financial Crises from Turkey: Using Wavelet Coherency and Varma Modeling to Forecast Stock Return

NASA Astrophysics Data System (ADS)

Oygur, Tunc; Unal, Gazanfer

Shocks, jumps, booms and busts are typical large fluctuation markers which appear in crisis. Models and leading indicators vary according to crisis type in spite of the fact that there are a lot of different models and leading indicators in literature to determine structure of crisis. In this paper, we investigate structure of dynamic correlation of stock return, interest rate, exchange rate and trade balance differences in crisis periods in Turkey over the period between October 1990 and March 2015 by applying wavelet coherency methodologies to determine nature of crises. The time period includes the Turkeys currency and banking crises; US sub-prime mortgage crisis and the European sovereign debt crisis occurred in 1994, 2001, 2008 and 2009, respectively. Empirical results showed that stock return, interest rate, exchange rate and trade balance differences are significantly linked during the financial crises in Turkey. The cross wavelet power, the wavelet coherency, the multiple wavelet coherency and the quadruple wavelet coherency methodologies have been used to examine structure of dynamic correlation. Moreover, in consequence of quadruple and multiple wavelet coherence, strongly correlated large scales indicate linear behavior and, hence VARMA (vector autoregressive moving average) gives better fitting and forecasting performance. In addition, increasing the dimensions of the model for strongly correlated scales leads to more accurate results compared to scalar counterparts.

The shift from defined benefit pensions to 401(k) plans and the pension assets of the baby boom cohort

PubMed Central

Poterba, James; Venti, Steven; Wise, David A.

2007-01-01

The rise of 401(k) plans and the decline of defined benefit plans will have an important effect on the wealth of future retirees. Changing demographic structure also will affect the aggregate stock of retirement wealth. We project the stock of assets held in retirement plans and the average retirement saving of retirees through 2040. Our projections show large increases in wealth at retirement, especially if the returns on corporate equities are comparable with historical returns. Retirement wealth will grow, however, even if equity returns fall substantially below their historical level. PMID:17686989

Risk of portfolio with simulated returns based on copula model

NASA Astrophysics Data System (ADS)

Razak, Ruzanna Ab; Ismail, Noriszura

2015-02-01

The commonly used tool for measuring risk of a portfolio with equally weighted stocks is variance-covariance method. Under extreme circumstances, this method leads to significant underestimation of actual risk due to its multivariate normality assumption of the joint distribution of stocks. The purpose of this research is to compare the actual risk of portfolio with the simulated risk of portfolio in which the joint distribution of two return series is predetermined. The data used is daily stock prices from the ASEAN market for the period January 2000 to December 2012. The copula approach is applied to capture the time varying dependence among the return series. The results shows that the chosen copula families are not suitable to present the dependence structures of each bivariate returns. Exception for the Philippines-Thailand pair where by t copula distribution appears to be the appropriate choice to depict its dependence. Assuming that the t copula distribution is the joint distribution of each paired series, simulated returns is generated and value-at-risk (VaR) is then applied to evaluate the risk of each portfolio consisting of two simulated return series. The VaR estimates was found to be symmetrical due to the simulation of returns via elliptical copula-GARCH approach. By comparison, it is found that the actual risks are underestimated for all pairs of portfolios except for Philippines-Thailand. This study was able to show that disregard of the non-normal dependence structure of two series will result underestimation of actual risk of the portfolio.

Analysis of aggregated tick returns: Evidence for anomalous diffusion

NASA Astrophysics Data System (ADS)

Weber, Philipp

2007-01-01

In order to investigate the origin of large price fluctuations, we analyze stock price changes of ten frequently traded NASDAQ stocks in the year 2002. Though the influence of the trading frequency on the aggregate return in a certain time interval is important, it cannot alone explain the heavy-tailed distribution of stock price changes. For this reason, we analyze intervals with a fixed number of trades in order to eliminate the influence of the trading frequency and investigate the relevance of other factors for the aggregate return. We show that in tick time the price follows a discrete diffusion process with a variable step width while the difference between the number of steps in positive and negative direction in an interval is Gaussian distributed. The step width is given by the return due to a single trade and is long-term correlated in tick time. Hence, its mean value can well characterize an interval of many trades and turns out to be an important determinant for large aggregate returns. We also present a statistical model reproducing the cumulative distribution of aggregate returns. For an accurate agreement with the empirical distribution, we also take into account asymmetries of the step widths in different directions together with cross correlations between these asymmetries and the mean step width as well as the signs of the steps.

27 CFR 46.232 - Preparation of floor stocks tax return.

Code of Federal Regulations, 2013 CFR

2013-04-01

... TOBACCO PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Filing Requirements § 46.232 Preparation of...

27 CFR 46.232 - Preparation of floor stocks tax return.

Code of Federal Regulations, 2011 CFR

2011-04-01

... TOBACCO PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Filing Requirements § 46.232 Preparation of...

27 CFR 46.232 - Preparation of floor stocks tax return.

Code of Federal Regulations, 2012 CFR

2012-04-01

... TOBACCO PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Filing Requirements § 46.232 Preparation of...

27 CFR 46.232 - Preparation of floor stocks tax return.

Code of Federal Regulations, 2014 CFR

2014-04-01

... TOBACCO PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Filing Requirements § 46.232 Preparation of...

27 CFR 46.232 - Preparation of floor stocks tax return.

Code of Federal Regulations, 2010 CFR

2010-04-01

... TOBACCO PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Filing Requirements § 46.232 Preparation of...

Lake Roosevelt Fisheries Evaluation Program : Lake Whatcom Kokanee Salmon (Oncorhynchus nerka kennerlyi) : Investigations in Lake Roosevelt Annual Report 1999-2000.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McLellan, Holly J.; Scholz, Allan T.; McLellan, Jason G.

2001-07-01

Lake Whatcom stock kokanee have been planted in Lake Roosevelt since 1988 with the primary goal of establishing a self-sustaining fishery. Returns of hatchery kokanee to egg collection facilities and recruitment to the creel have been minimal. Therefore, four experiments were conducted to determine the most appropriate release strategy that would increase kokanee returns. The first experiment compared morpholine and non-morpholine imprinted kokanee return rates, the second experiment compared early and middle run Whatcom kokanee, the third experiment compared early and late release dates, and the fourth experiment compared three net pen release strategies: Sherman Creek hatchery vs. Sherman Creekmore » net pens, Colville River net pens vs. Sherman Creek net pens, and upper vs. lower reservoir net pen releases. Each experiment was tested in three ways: (1) returns to Sherman Creek, (2) returns to other tributaries throughout the reservoir, and (3) returns to the creel. Chi-square analysis of hatchery and tributary returns indicated no significant difference between morpholine imprinted and non-imprinted fish, early run fish outperformed middle run fish, early release date outperformed late release fish, and the hatchery outperformed all net pen releases. Hatchery kokanee harvest was estimated at 3,323 fish, which was 33% of the total harvest. Return rates (1998 = 0.52%) of Whatcom kokanee were low indicating an overall low performance that could be caused by high entrainment, predation, and precocity. A kokanee stock native to the upper Columbia, as opposed to the coastal Whatcom stock, may perform better in Lake Roosevelt.« less

The real economic effects of cross-delisting from the United States: Evidence on post-operating performance, financial constraints and stock crash risk =

NASA Astrophysics Data System (ADS)

Silva, Sonia Maria da Silva Faria Nogueira da

In this study we examine the economic consequences for firms that cross-delisted from a U.S. stock exchange. Using a sample of foreign firms that cross-delisted from U.S. exchange markets from 2000 to 2012, we investigate the long-term performance, the level of financial constraints, and the likelihood of stock price crashes after the cross-delisting event. We document several new findings as follows: i) cross-delisted firms have less growth opportunities, in the long-run, than their cross-listed peers; ii) after the adoption of Rule 12h-6 of 2007, cross-delisted firms exhibit a significant decline in operating performance; iii) cross-delisted firms underperform their cross-listed peers as they experience negative average abnormal returns, especially in the post-cross-delisting period; iv) cross-delisted firms face higher financial constraints post-delisting than their cross-listed counterparts, and also tend to save more cash out of cash flows; v) the increase in financial constraints post-cross-delisting seems to be primarily driven by informational frictions that constrain access to external financing, which are stronger for firms from countries with weaker investor protection and less developed capital markets; vi) cross-delisted firms experience a significant increase in crash risk associated with earnings management in the post-delisting period relative to a control sample of cross-listed firms, and this effect is more pronounced for delisted firms from countries with weaker investor protection and poor quality of their information environment; vii) cross-delisted firms that engage in earnings management to inflate reported earnings prior to a seasoned equity offering are more likely to a subsequent stock price crash.

Migratory Patterns of Wild Chinook Salmon Oncorhynchus tshawytscha Returning to a Large, Free-Flowing River Basin

PubMed Central

Eiler, John H.; Evans, Allison N.; Schreck, Carl B.

2015-01-01

Upriver movements were determined for Chinook salmon Oncorhynchus tshawytscha returning to the Yukon River, a large, virtually pristine river basin. These returns have declined dramatically since the late 1990s, and information is needed to better manage the run and facilitate conservation efforts. A total of 2,860 fish were radio tagged during 2002–2004. Most (97.5%) of the fish tracked upriver to spawning areas displayed continual upriver movements and strong fidelity to the terminal tributaries entered. Movement rates were substantially slower for fish spawning in lower river tributaries (28–40 km d-1) compared to upper basin stocks (52–62 km d-1). Three distinct migratory patterns were observed, including a gradual decline, pronounced decline, and substantial increase in movement rate as the fish moved upriver. Stocks destined for the same region exhibited similar migratory patterns. Individual fish within a stock showed substantial variation, but tended to reflect the regional pattern. Differences between consistently faster and slower fish explained 74% of the within-stock variation, whereas relative shifts in sequential movement rates between “hares” (faster fish becoming slower) and “tortoises” (slow but steady fish) explained 22% of the variation. Pulses of fish moving upriver were not cohesive. Fish tagged over a 4-day period took 16 days to pass a site 872 km upriver. Movement rates were substantially faster and the percentage of atypical movements considerably less than reported in more southerly drainages, but may reflect the pristine conditions within the Yukon River, wild origins of the fish, and discrete run timing of the returns. Movement data can provide numerous insights into the status and management of salmon returns, particularly in large river drainages with widely scattered fisheries where management actions in the lower river potentially impact harvests and escapement farther upstream. However, the substantial variation exhibited among individual fish within a stock can complicate these efforts. PMID:25919286

Migratory Patterns of Chinook Salmon Oncorhynchus tshawytscha Returning to a Large, Free-flowing River Basin

USGS Publications Warehouse

Eiler, John H.; Evans, Allison N.; Schreck, Carl B.

2015-01-01

Upriver movements were determined for Chinook salmon Oncorhynchus tshawytscha returning to the Yukon River, a large, virtually pristine river basin. These returns have declined dramatically since the late 1990s, and information is needed to better manage the run and facilitate conservation efforts. A total of 2,860 fish were radio tagged during 2002–2004. Most (97.5%) of the fish tracked upriver to spawning areas displayed continual upriver movements and strong fidelity to the terminal tributaries entered. Movement rates were substantially slower for fish spawning in lower river tributaries (28–40 km d-1) compared to upper basin stocks (52–62 km d-1). Three distinct migratory patterns were observed, including a gradual decline, pronounced decline, and substantial increase in movement rate as the fish moved upriver. Stocks destined for the same region exhibited similar migratory patterns. Individual fish within a stock showed substantial variation, but tended to reflect the regional pattern. Differences between consistently faster and slower fish explained 74% of the within-stock variation, whereas relative shifts in sequential movement rates between “hares” (faster fish becoming slower) and “tortoises” (slow but steady fish) explained 22% of the variation. Pulses of fish moving upriver were not cohesive. Fish tagged over a 4-day period took 16 days to pass a site 872 km upriver. Movement rates were substantially faster and the percentage of atypical movements considerably less than reported in more southerly drainages, but may reflect the pristine conditions within the Yukon River, wild origins of the fish, and discrete run timing of the returns. Movement data can provide numerous insights into the status and management of salmon returns, particularly in large river drainages with widely scattered fisheries where management actions in the lower river potentially impact harvests and escapement farther upstream. However, the substantial variation exhibited among individual fish within a stock can complicate these efforts.

Fluctuation behaviors of financial return volatility duration

NASA Astrophysics Data System (ADS)

Niu, Hongli; Wang, Jun; Lu, Yunfan

2016-04-01

It is of significantly crucial to understand the return volatility of financial markets because it helps to quantify the investment risk, optimize the portfolio, and provide a key input of option pricing models. The characteristics of isolated high volatility events above certain threshold in price fluctuations and the distributions of return intervals between these events arouse great interest in financial research. In the present work, we introduce a new concept of daily return volatility duration, which is defined as the shortest passage time when the future volatility intensity is above or below the current volatility intensity (without predefining a threshold). The statistical properties of the daily return volatility durations for seven representative stock indices from the world financial markets are investigated. Some useful and interesting empirical results of these volatility duration series about the probability distributions, memory effects and multifractal properties are obtained. These results also show that the proposed stock volatility series analysis is a meaningful and beneficial trial.

The returns and risks of investment portfolio in stock market crashes

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Long, Chao; Chen, Xiao-Dan

2015-06-01

The returns and risks of investment portfolio in stock market crashes are investigated by considering a theoretical model, based on a modified Heston model with a cubic nonlinearity, proposed by Spagnolo and Valenti. Through numerically simulating probability density function of returns and the mean escape time of the model, the results indicate that: (i) the maximum stability of returns is associated with the maximum dispersion of investment portfolio and an optimal stop-loss position; (ii) the maximum risks are related with a worst dispersion of investment portfolio and the risks of investment portfolio are enhanced by increasing stop-loss position. In addition, the good agreements between the theoretical result and real market data are found in the behaviors of the probability density function and the mean escape time.

What Does Stock Ownership Breadth Measure?*

PubMed Central

Choi, James J.; Jin, Li; Yan, Hongjun

2013-01-01

Using holdings data on a representative sample of all Shanghai Stock Exchange investors, we show that increases in ownership breadth (the fraction of market participants who own a stock) predict low returns: highest change quintile stocks underperform lowest quintile stocks by 23% per year. Small retail investors drive this result. Retail ownership breadth increases appear to be correlated with overpricing. Among institutional investors, however, the opposite holds: Stocks in the top decile of wealth-weighted institutional breadth change outperform the bottom decile by 8% per year, consistent with prior work that interprets breadth as a measure of short-sales constraints. PMID:24764801

The use of the Hurst exponent to predict changes in trends on the Warsaw Stock Exchange

NASA Astrophysics Data System (ADS)

Domino, Krzysztof

2011-01-01

The local properties of the time series of the evolution of share prices of 126 significant companies traded on the Warsaw Stock Exchange during the period between 1991-2008 have been investigated. The analysis was applied to daily financial returns. I have used the local DFA to obtain the Hurst exponent (diffusion coefficient) while searching for negative correlations by which changes of long-term trends would be effected. A certain evidence, proving that after the signature of anti-correlation-the drop in the Hurst exponent-the change in the trend and in the return rate of an investment is probable, was pointed out. Hence after further investigation this method may be useful as a part of an investment strategy. As the Warsaw Stock Exchange is relatively smaller and younger than other significant world Stock Exchanges-and as the developing market is less efficient-the generalization for others markets needs further investigation.

Quantifying Stock Return Distributions in Financial Markets

PubMed Central

Botta, Federico; Moat, Helen Susannah; Stanley, H. Eugene; Preis, Tobias

2015-01-01

Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales. PMID:26327593

Quantifying Stock Return Distributions in Financial Markets.

PubMed

Botta, Federico; Moat, Helen Susannah; Stanley, H Eugene; Preis, Tobias

2015-01-01

Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales.

Long memory in international financial markets trends and short movements during 2008 financial crisis based on variational mode decomposition and detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2015-11-01

The purpose of this study is to investigate long-range dependence in trend and short variation of stock market price and return series before, during, and after 2008 financial crisis. Variational mode decomposition (VMD), a newly introduced technique for signal processing, is adopted to decompose stock market data into a finite set of modes so as to obtain long term trends and short term movements of stock market data. Then, the detrended fluctuation analysis (DFA) and range scale (R/S) analysis are used to estimate Hurst exponent in each variational mode obtained from VMD. For both price and return series, the empirical results from twelve international stock markets show evidence that long term trends are persistent, whilst short term variations are anti-persistent before, during, and after 2008 financial crisis.

Applying Modern Portfolio Theory and the Capital Asset Pricing Model to DoD’s Information Technology Investments

DTIC Science & Technology

2009-03-01

axis was really historical volatility of the return on a particular stock (capital gains of losses as well as dividends). Markowitz’s theory is an...market, the risk involved in a particular stock is determined by the historical volatility of the return. “But investments like IT projects or new...product development don’t typically have ‘ historical volatility .’ They do, however, share another characteristic of risk that is more fundamental than

Stock Market Expectations of Dutch Households

PubMed Central

Hurd, Michael; van Rooij, Maarten; Winter, Joachim

2013-01-01

Despite its importance for the analysis of life-cycle behavior and, in particular, retirement planning, stock ownership by private households is poorly understood. Among other approaches to investigate this puzzle, recent research has started to elicit private households’ expectations of stock market returns. This paper reports findings from a study that collected data over a two-year period both on households’ stock market expectations (subjective probabilities of gains or losses) and on whether they own stocks. We document substantial heterogeneity in financial market expectations. Expectations are correlated with stock ownership. Over the two years of our data, stock market prices increased, and expectations of future stock market price changes also increased, lending support to the view that expectations are influenced by recent stock gains or losses. PMID:23997423

Asymmetry of price returns-Analysis and perspectives from a non-extensive statistical physics point of view.

PubMed

Bil, Łukasz; Grech, Dariusz; Zienowicz, Magdalena

2017-01-01

We study how the approach grounded on non-extensive statistical physics can be applied to describe and distinguish different stages of the stock and money market development. A particular attention is given to asymmetric behavior of fat tailed distributions of positive and negative returns. A new method to measure this asymmetry is proposed. It is based on the value of the non-extensive Tsallis parameter q. The new quantifier of the relative asymmetry level between tails in terms of the Tsallis parameters q± is provided to analyze the effect of memory in data caused by nonlinear autocorrelations. The presented analysis takes into account data of separate stocks from the main developing stock market in Europe, i.e., the Warsaw Stock Exchange (WSE) in Poland and-for comparison-data from the most mature money market (Forex). It is argued that the proposed new quantifier is able to describe the stage of market development and its robustness to speculation. The main strength is put on a description and interpretation of the asymmetry between statistical properties of positive and negative returns for various stocks and for diversified time-lags Δt of data counting. The particular caution in this context is addressed to the difference between intraday and interday returns. Our search is extended to study memory effects and their dependence on the quotation frequency for similar large companies-owners of food-industrial retail supermarkets acting on both Polish and European markets (Eurocash, Jeronimo-Martins, Carrefour, Tesco)-but traded on various European stock markets of diversified economical maturity (respectively in Warsaw, Lisbon, Paris and London). The latter analysis seems to indicate quantitatively that stocks from the same economic sector traded on different markets within European Union (EU) may be a target of diversified level of speculations involved in trading independently on the true economic situation of the company. Our work thus gives indications that the statement:" where you are is more important than who you are" is true on trading markets.

How Random is the Walk: Efficiency of Indian Stock and Futures Markets

NASA Astrophysics Data System (ADS)

Basu, Udayan Kumar

Time series of prices of stock and its rates of return has been one of the major areas of study in Econophysics. The price of a stock depends on a number of factors as well as information related thereto, and how quickly and effectively the price of a stock assimilates all such information decides the efficiency of the stock market. Instead of individual stocks, people often study the behaviour of stock indices to get a feel of the market as a whole, and the outcomes of such studies for the Dow Jones Industrial Average (DJIA), the Nasdaq Index and the S & P 500 Index have been listed in a number of articles. In this context, it has also been argued that for a market to be considered sufficiently liquid, correlation between successive price movements and rates of return should be insignificant, because any significant correlation would lead to an arbitrage opportunity that is expected to be rapidly exploited and thus washed out. The residual correlations are those little enough not to be profitable for strategies due to imperfect market conditions. Unless transaction costs or slippages or any other impediment exists, leading to some transactional inefficiency, arbitrages would take place to bring back the markets to a stage of insignifficant correlations [1, 2].

Multifractal characterization of energy stocks in China: A multifractal detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Yang, Liansheng; Zhu, Yingming; Wang, Yudong

2016-06-01

In this paper, we investigate the impacts of oil price changes on energy stocks in Chinese stock market from the multifractal perspective. The well-known multifractal detrended fluctuation analysis (MF-DFA) is applied to detect the multifractality. We find that both returns and volatilities of energy industry index display apparent multifractal behavior. Oil market activity is an important source of multifractality in energy stocks index in addition to long-range correlations and fat-tail distributions.

Variety of Behavior of Equity Returns in Financial Markets

NASA Astrophysics Data System (ADS)

Bonanno, Giovanni; Lillo, Fabrizio; Mantegna, Rosario N.

2001-03-01

The price dynamics of a set of equities traded in an efficient market is pretty complex. It consists of almost not redundant time series which have (i) long-range correlated volatility and (ii) cross-correlation between each pair of equities. We perform a study of the statistical properties of an ensemble of equities returns which is fruitful to elucidate the nature and role of time and ensemble correlation. Specifically, we investigate a statistical ensemble of daily returns of n equities traded in United States financial markets. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days [1] with the exception of crash and rally days and of the days following to these extreme events [2]. We analyze each ensemble return distribution by extracting its first two central moments. We call the second moment of the ensemble return distribution the variety of the market. We choose this term because high variety implies a variated behavior of the equities returns in the considered day. We observe that the mean return and the variety are fluctuating in time and are stochastic processes themselves. The variety is a long-range correlated stochastic process. Customary time-averaged statistical properties of time series of stock returns are also considered. In general, time-averaged and portfolio-averaged returns have different statistical properties [1]. We infer from these differences information about the relative strength of correlation between equities and between different trading days. We also compare our empirical results with those predicted by the single-index model and we conclude that this simple model is unable to explain the statistical properties of the second moment of the ensemble return distribution. Correlation between pairs of equities are continuously present in the dynamics of a stock portfolio. Hence, it is relevant to investigate pair correlation in a efficient and original way. We propose to investigate these correlations at a daily and intra daily time horizon with a method based on concepts of random frustrated systems. Specifically, a hierarchical organization of the investigated equities is obtained by determining a metric distance between stocks and by investigating the properties of the subdominant ultrametric associated with it [3]. The high-frequency cross-correlation existing between pairs of equities are investigated in a set of 100 stocks traded in US equity markets. The decrease of the cross-correlation between the equity returns observed for diminishing time horizons progressively changes the nature of the hierarchical structure associated to each different time horizon [4]. The nature of the correlation present between pairs of time series of equity returns collected in a portfolio has a strong influence on the variety of the market. We finally discuss the relation between pair correlation and variety of an ensemble return distribution. References [1] Fabrizio Lillo and Rosario N. Mantegna, Variety and volatility in financial markets, Phys. Rev. E 62, 6126-6134 (2000). [2] Fabrizio Lillo and Rosario N. Mantegna, Symmetry alteration of ensemble return distribution in crash and rally days of financial market, Eur. Phys. J. B 15, 603-606 (2000). [3] Rosario N. Mantegna, Hierarchical structure in financial markets, Eur. Phys. J. B 11, 193-197 (1999). [4] Giovanni Bonanno, Fabrizio Lillo, and Rosario N. Mantegna, High-frequency cross-correlation in a set of stocks, Quantitative Finance (in press).

26 CFR 1.6042-1 - Return of information as to dividends paid in calendar years before 1963.

Code of Federal Regulations, 2010 CFR

2010-04-01

... owner or payee, the name of the issuing corporation, the number of shares of such stock, and the amount... such actual owner (without itemization as to the issuing company, class of stock, etc.). (2) Exceptions... periodical distributions of earnings on running installment shares of stock paid or credited by a building...

76 FR 602 - Self-Regulatory Organizations; The Options Clearing Corporation; Notice of Filing of Proposed...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-05

... member and guarantees the return of the loaned stock to the lending clearing member and the collateral to.... OCC's risk is, in turn, reduced by having the benefit of the hedge. \\3\\ With respect to both the Stock... net risk of all open positions carried in the account, including stock loan positions as well as...

77 FR 57189 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-17

... currently approved collection. Title: TD 8560 (CO-30-92) Consolidated Returns--Stock Basis and Excess Loss...) allocating items between returns. The information will facilitate enforcement of consolidated return... completed prior to the effective data and to stop an election to use a historic loss payment pattern...

A first application of independent component analysis to extracting structure from stock returns.

PubMed

Back, A D; Weigend, A S

1997-08-01

This paper explores the application of a signal processing technique known as independent component analysis (ICA) or blind source separation to multivariate financial time series such as a portfolio of stocks. The key idea of ICA is to linearly map the observed multivariate time series into a new space of statistically independent components (ICs). We apply ICA to three years of daily returns of the 28 largest Japanese stocks and compare the results with those obtained using principal component analysis. The results indicate that the estimated ICs fall into two categories, (i) infrequent large shocks (responsible for the major changes in the stock prices), and (ii) frequent smaller fluctuations (contributing little to the overall level of the stocks). We show that the overall stock price can be reconstructed surprisingly well by using a small number of thresholded weighted ICs. In contrast, when using shocks derived from principal components instead of independent components, the reconstructed price is less similar to the original one. ICA is shown to be a potentially powerful method of analyzing and understanding driving mechanisms in financial time series. The application to portfolio optimization is described in Chin and Weigend (1998).

Illiquidity premium and expected stock returns in the UK: A new approach

NASA Astrophysics Data System (ADS)

Chen, Jiaqi; Sherif, Mohamed

2016-09-01

This study examines the relative importance of liquidity risk for the time-series and cross-section of stock returns in the UK. We propose a simple way to capture the multidimensionality of illiquidity. Our analysis indicates that existing illiquidity measures have considerable asset specific components, which justifies our new approach. Further, we use an alternative test of the Amihud (2002) measure and parametric and non-parametric methods to investigate whether liquidity risk is priced in the UK. We find that the inclusion of the illiquidity factor in the capital asset pricing model plays a significant role in explaining the cross-sectional variation in stock returns, in particular with the Fama-French three-factor model. Further, using Hansen-Jagannathan non-parametric bounds, we find that the illiquidity-augmented capital asset pricing models yield a small distance error, other non-liquidity based models fail to yield economically plausible distance values. Our findings have important implications for managing the liquidity risk of equity portfolios.

Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2018-06-01

The realized stochastic volatility model has been introduced to estimate more accurate volatility by using both daily returns and realized volatility. The main advantage of the model is that no special bias-correction factor for the realized volatility is required a priori. Instead, the model introduces a bias-correction parameter responsible for the bias hidden in realized volatility. We empirically investigate the bias-correction parameter for realized volatilities calculated at various sampling frequencies for six stocks on the Tokyo Stock Exchange, and then show that the dynamic behavior of the bias-correction parameter as a function of sampling frequency is qualitatively similar to that of the Hansen-Lunde bias-correction factor although their values are substantially different. Under the stochastic diffusion assumption of the return dynamics, we investigate the accuracy of estimated volatilities by examining the standardized returns. We find that while the moments of the standardized returns from low-frequency realized volatilities are consistent with the expectation from the Gaussian variables, the deviation from the expectation becomes considerably large at high frequencies. This indicates that the realized stochastic volatility model itself cannot completely remove bias at high frequencies.

Multifactor analysis of multiscaling in volatility return intervals.

PubMed

Wang, Fengzhong; Yamasaki, Kazuko; Havlin, Shlomo; Stanley, H Eugene

2009-01-01

We study the volatility time series of 1137 most traded stocks in the U.S. stock markets for the two-year period 2001-2002 and analyze their return intervals tau , which are time intervals between volatilities above a given threshold q . We explore the probability density function of tau , P_(q)(tau) , assuming a stretched exponential function, P_(q)(tau) approximately e;(-tau;(gamma)) . We find that the exponent gamma depends on the threshold in the range between q=1 and 6 standard deviations of the volatility. This finding supports the multiscaling nature of the return interval distribution. To better understand the multiscaling origin, we study how gamma depends on four essential factors, capitalization, risk, number of trades, and return. We show that gamma depends on the capitalization, risk, and return but almost does not depend on the number of trades. This suggests that gamma relates to the portfolio selection but not on the market activity. To further characterize the multiscaling of individual stocks, we fit the moments of tau , mu_(m) identical with(tautau);(m);(1m) , in the range of 10

Multifactor analysis of multiscaling in volatility return intervals

NASA Astrophysics Data System (ADS)

Wang, Fengzhong; Yamasaki, Kazuko; Havlin, Shlomo; Stanley, H. Eugene

2009-01-01

We study the volatility time series of 1137 most traded stocks in the U.S. stock markets for the two-year period 2001-2002 and analyze their return intervals τ , which are time intervals between volatilities above a given threshold q . We explore the probability density function of τ , Pq(τ) , assuming a stretched exponential function, Pq(τ)˜e-τγ . We find that the exponent γ depends on the threshold in the range between q=1 and 6 standard deviations of the volatility. This finding supports the multiscaling nature of the return interval distribution. To better understand the multiscaling origin, we study how γ depends on four essential factors, capitalization, risk, number of trades, and return. We show that γ depends on the capitalization, risk, and return but almost does not depend on the number of trades. This suggests that γ relates to the portfolio selection but not on the market activity. To further characterize the multiscaling of individual stocks, we fit the moments of τ , μm≡⟨(τ/⟨τ⟩)m⟩1/m , in the range of 10<⟨τ⟩⩽100 by a power law, μm˜⟨τ⟩δ . The exponent δ is found also to depend on the capitalization, risk, and return but not on the number of trades, and its tendency is opposite to that of γ . Moreover, we show that δ decreases with increasing γ approximately by a linear relation. The return intervals demonstrate the temporal structure of volatilities and our findings suggest that their multiscaling features may be helpful for portfolio optimization.

Stock price prediction using geometric Brownian motion

NASA Astrophysics Data System (ADS)

Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM

2018-03-01

Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

Portfolio optimization with mean-variance model

NASA Astrophysics Data System (ADS)

Hoe, Lam Weng; Siew, Lam Weng

2016-06-01

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

The effects of behavioral and structural assumptions in artificial stock market

NASA Astrophysics Data System (ADS)

Liu, Xinghua; Gregor, Shirley; Yang, Jianmei

2008-04-01

Recent literature has developed the conjecture that important statistical features of stock price series, such as the fat tails phenomenon, may depend mainly on the market microstructure. This conjecture motivated us to investigate the roles of both the market microstructure and agent behavior with respect to high-frequency returns and daily returns. We developed two simple models to investigate this issue. The first one is a stochastic model with a clearing house microstructure and a population of zero-intelligence agents. The second one has more behavioral assumptions based on Minority Game and also has a clearing house microstructure. With the first model we found that a characteristic of the clearing house microstructure, namely the clearing frequency, can explain fat tail, excess volatility and autocorrelation phenomena of high-frequency returns. However, this feature does not cause the same phenomena in daily returns. So the Stylized Facts of daily returns depend mainly on the agents’ behavior. With the second model we investigated the effects of behavioral assumptions on daily returns. Our study implicates that the aspects which are responsible for generating the stylized facts of high-frequency returns and daily returns are different.

Random matrix approach to the dynamics of stock inventory variations

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Mu, Guo-Hua; Kertész, János

2012-09-01

It is well accepted that investors can be classified into groups owing to distinct trading strategies, which forms the basic assumption of many agent-based models for financial markets when agents are not zero-intelligent. However, empirical tests of these assumptions are still very rare due to the lack of order flow data. Here we adopt the order flow data of Chinese stocks to tackle this problem by investigating the dynamics of inventory variations for individual and institutional investors that contain rich information about the trading behavior of investors and have a crucial influence on price fluctuations. We find that the distributions of cross-correlation coefficient Cij have power-law forms in the bulk that are followed by exponential tails, and there are more positive coefficients than negative ones. In addition, it is more likely that two individuals or two institutions have a stronger inventory variation correlation than one individual and one institution. We find that the largest and the second largest eigenvalues (λ1 and λ2) of the correlation matrix cannot be explained by random matrix theory and the projections of investors' inventory variations on the first eigenvector u(λ1) are linearly correlated with stock returns, where individual investors play a dominating role. The investors are classified into three categories based on the cross-correlation coefficients CV R between inventory variations and stock returns. A strong Granger causality is unveiled from stock returns to inventory variations, which means that a large proportion of individuals hold the reversing trading strategy and a small part of individuals hold the trending strategy. Our empirical findings have scientific significance in the understanding of investors' trading behavior and in the construction of agent-based models for emerging stock markets.

Selection Input Output by Restriction Using DEA Models Based on a Fuzzy Delphi Approach and Expert Information

NASA Astrophysics Data System (ADS)

Arsad, Roslah; Nasir Abdullah, Mohammad; Alias, Suriana; Isa, Zaidi

2017-09-01

Stock evaluation has always been an interesting problem for investors. In this paper, a comparison regarding the efficiency stocks of listed companies in Bursa Malaysia were made through the application of estimation method of Data Envelopment Analysis (DEA). One of the interesting research subjects in DEA is the selection of appropriate input and output parameter. In this study, DEA was used to measure efficiency of stocks of listed companies in Bursa Malaysia in terms of the financial ratio to evaluate performance of stocks. Based on previous studies and Fuzzy Delphi Method (FDM), the most important financial ratio was selected. The results indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share, price to earnings and debt to equity were the most important ratios. Using expert information, all the parameter were clarified as inputs and outputs. The main objectives were to identify most critical financial ratio, clarify them based on expert information and compute the relative efficiency scores of stocks as well as rank them in the construction industry and material completely. The methods of analysis using Alirezaee and Afsharian’s model were employed in this study, where the originality of Charnes, Cooper and Rhodes (CCR) with the assumption of Constant Return to Scale (CSR) still holds. This method of ranking relative efficiency of decision making units (DMUs) was value-added by the Balance Index. The interested data was made for year 2015 and the population of the research includes accepted companies in stock markets in the construction industry and material (63 companies). According to the ranking, the proposed model can rank completely for 63 companies using selected financial ratio.

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

PubMed

Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

2015-01-01

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode.

Hospital profitability and capital structure: a comparative analysis.

PubMed Central

Valvona, J; Sloan, F A

1988-01-01

This article compares the financial performance of hospitals by ownership type and of five publicly traded hospital companies with other industries, using such indicators as profit margins, return on equity (ROE) and total capitalization, and debt-to-equity ratios. We also examine stock returns to investors for the five hospital companies versus other industries, as well as the relative roles of debt and equity in new financing. Investor-owned hospitals had substantially greater margins and ROE than did other hospital types. In 1982, investor-owned chain hospitals had a ROE of 26 percent, 18 points above the average for all hospitals. Stock returns on the five selected hospital companies were more than twice as large as returns on other industries between 1972 and 1983. However, after 1983, returns for these companies fell dramatically in absolute terms and relative to other industries. We also found investor-owned hospitals to be much more highly levered than their government and voluntary counterparts, and more highly levered than other industries as well. PMID:3403274

An autocatalytic network model for stock markets

NASA Astrophysics Data System (ADS)

Caetano, Marco Antonio Leonel; Yoneyama, Takashi

2015-02-01

The stock prices of companies with businesses that are closely related within a specific sector of economy might exhibit movement patterns and correlations in their dynamics. The idea in this work is to use the concept of autocatalytic network to model such correlations and patterns in the trends exhibited by the expected returns. The trends are expressed in terms of positive or negative returns within each fixed time interval. The time series derived from these trends is then used to represent the movement patterns by a probabilistic boolean network with transitions modeled as an autocatalytic network. The proposed method might be of value in short term forecasting and identification of dependencies. The method is illustrated with a case study based on four stocks of companies in the field of natural resource and technology.

Time-independent models of asset returns revisited

NASA Astrophysics Data System (ADS)

Gillemot, L.; Töyli, J.; Kertesz, J.; Kaski, K.

2000-07-01

In this study we investigate various well-known time-independent models of asset returns being simple normal distribution, Student t-distribution, Lévy, truncated Lévy, general stable distribution, mixed diffusion jump, and compound normal distribution. For this we use Standard and Poor's 500 index data of the New York Stock Exchange, Helsinki Stock Exchange index data describing a small volatile market, and artificial data. The results indicate that all models, excluding the simple normal distribution, are, at least, quite reasonable descriptions of the data. Furthermore, the use of differences instead of logarithmic returns tends to make the data looking visually more Lévy-type distributed than it is. This phenomenon is especially evident in the artificial data that has been generated by an inflated random walk process.

Price performance following stock's IPO in different price limit systems

NASA Astrophysics Data System (ADS)

Wu, Ting; Wang, Yue; Li, Ming-Xia

2018-01-01

An IPO burst occurred in China's stock markets in 2015, while price limit trading rules usually help to reduce the short-term trading mania on individual stocks. It is interesting to make clear the function of the price limits after IPOs. We firstly make a statistical analysis based on all the IPO stocks listed from 1990 to 2015. A high dependency exists between the activities in stock's IPO and various market environment. We also focus on the price dynamics in the first 40 trading days after the stock listed. We find that price limit system will delay the price movement, especially for the up-trend movements, which may lead to longer continuous price limit hits. Similar to our previous work, many results such as ;W; shape can be also observed in the future daily return after the price limit open. At last, we find most IPO measures show evident correlations with the following price limit hits. IPO stocks with lower first-day turnover and earning per share will be followed with a longer continuous price limit hits and lower future daily return under the newest trading rules, which give us a good way to estimate the occurrence of price limit hits and the following price dynamics. Our analysis provides a better understanding of the price dynamics after IPO events and offers potential practical values for investors.

Leverage effect and its causality in the Korea composite stock price index

NASA Astrophysics Data System (ADS)

Lee, Chang-Yong

2012-02-01

In this paper, we investigate the leverage effect and its causality in the time series of the Korea Composite Stock Price Index from November of 1997 to September of 2010. The leverage effect, which can be quantitatively expressed as a negative correlation between past return and future volatility, is measured by using the cross-correlation coefficient of different time lags between the two time series of the return and the volatility. We find that past return and future volatility are negatively correlated and that the cross correlation is moderate and decays over 60 trading days. We also carry out a partial correlation analysis in order to confirm that the negative correlation between past return and future volatility is neither an artifact nor influenced by the traded volume. To determine the causality of the leverage effect within the decay time, we additionally estimate the cross correlation between past volatility and future return. With the estimate, we perform a statistical hypothesis test to demonstrate that the causal relation is in favor of the return influencing the volatility rather than the other way around.

Arbitrage and Volatility in Chinese Stock's Markets

NASA Astrophysics Data System (ADS)

Lu, Shu Quan; Ito, Takao; Zhang, Jianbo

From the point of view of no-arbitrage pricing, what matters is how much volatility the stock has, for volatility measures the amount of profit that can be made from shorting stocks and purchasing options. With the short-sales constraints or in the absence of options, however, high volatility is likely to mean arbitrage from stock market. As emerging stock markets for China, investors are increasingly concerned about volatilities of Chinese two stock markets. We estimate volatility's models for Chinese stock markets' indexes using Markov chain Monte Carlo (MCMC) method and GARCH. We find that estimated values of volatility parameters are very high for all data frequencies. It suggests that stock returns are extremely volatile even at long term intervals in Chinese markets. Furthermore, this result could be considered that there seems to be arbitrage opportunities in Chinese stock markets.

Neglected chaos in international stock markets: Bayesian analysis of the joint return-volatility dynamical system

NASA Astrophysics Data System (ADS)

Tsionas, Mike G.; Michaelides, Panayotis G.

2017-09-01

We use a novel Bayesian inference procedure for the Lyapunov exponent in the dynamical system of returns and their unobserved volatility. In the dynamical system, computation of largest Lyapunov exponent by traditional methods is impossible as the stochastic nature has to be taken explicitly into account due to unobserved volatility. We apply the new techniques to daily stock return data for a group of six countries, namely USA, UK, Switzerland, Netherlands, Germany and France, from 2003 to 2014, by means of Sequential Monte Carlo for Bayesian inference. The evidence points to the direction that there is indeed noisy chaos both before and after the recent financial crisis. However, when a much simpler model is examined where the interaction between returns and volatility is not taken into consideration jointly, the hypothesis of chaotic dynamics does not receive much support by the data ("neglected chaos").

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

NASA Astrophysics Data System (ADS)

Yang, Ge; Wang, Jun; Fang, Wen

2015-04-01

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.

Stock price dynamics and option valuations under volatility feedback effect

NASA Astrophysics Data System (ADS)

Kanniainen, Juho; Piché, Robert

2013-02-01

According to the volatility feedback effect, an unexpected increase in squared volatility leads to an immediate decline in the price-dividend ratio. In this paper, we consider the properties of stock price dynamics and option valuations under the volatility feedback effect by modeling the joint dynamics of stock price, dividends, and volatility in continuous time. Most importantly, our model predicts the negative effect of an increase in squared return volatility on the value of deep-in-the-money call options and, furthermore, attempts to explain the volatility puzzle. We theoretically demonstrate a mechanism by which the market price of diffusion return risk, or an equity risk-premium, affects option prices and empirically illustrate how to identify that mechanism using forward-looking information on option contracts. Our theoretical and empirical results support the relevance of the volatility feedback effect. Overall, the results indicate that the prevailing practice of ignoring the time-varying dividend yield in option pricing can lead to oversimplification of the stock market dynamics.

Impact of global financial crisis on stylized facts between energy markets and stock markets

NASA Astrophysics Data System (ADS)

Leng, Tan Kim; Cheong, Chin Wen; Hooi, Tan Siow

2014-06-01

Understanding the stylized facts is extremely important and has becomes a hot issue nowadays. However, recent global financial crisis that started from United States had spread all over the world and adversely affected the commodities and financial sectors of both developed and developing countries. This paper tends to examine the impact of crisis on stylized facts between energy and stock markets using ARCH-family models based on the experience over 2008 global financial crisis. Empirical results denote that there is long lasting, persists and positively significant the autocorrelation function of absolute returns and their squares in both markets for before and during crisis. Besides that, leverage effects are found in stock markets whereby bad news has a greater impact on volatility than good news for both before and during crisis. However, crisis does not indicate any impact on risk-return tradeoff for both energy and stock markets. For forecasting evaluations, GARCH model and FIAPARCH model indicate superior out of sample forecasts for before and during crisis respectively.

Empirical behavior of a world stock index from intra-day to monthly time scales

NASA Astrophysics Data System (ADS)

Breymann, W.; Lüthi, D. R.; Platen, E.

2009-10-01

Most of the papers that study the distributional and fractal properties of financial instruments focus on stock prices or foreign exchange rates. This typically leads to mixed results concerning the distributions of log-returns and some multi-fractal properties of exchange rates, stock prices, and regional indices. This paper uses a well diversified world stock index as the central object of analysis. Such index approximates the growth optimal portfolio, which is demonstrated under the benchmark approach, it is the ideal reference unit for studying basic securities. When denominating this world index in units of a given currency, one measures the movements of the currency against the entire market. This provides a least disturbed observation of the currency dynamics. In this manner, one can expect to disentangle, e.g., the superposition of the two currencies involved in an exchange rate. This benchmark approach to the empirical analysis of financial data allows us to establish remarkable stylized facts. Most important is the observation that the repeatedly documented multi-fractal appearance of financial time series is very weak and much less pronounced than the deviation of the mono-scaling properties from Brownian-motion type scaling. The generalized Hurst exponent H(2) assumes typical values between 0.55 and 0.6. Accordingly, autocorrelations of log-returns decay according to a power law, and the quadratic variation vanishes when going to vanishing observation time step size. Furthermore, one can identify the Student t distribution as the log-return distribution of a well-diversified world stock index for long time horizons when a long enough data series is used for estimation. The study of dependence properties, finally, reveals that jumps at daily horizon originate primarily in the stock market while at 5min horizon they originate in the foreign exchange market. The principal message of the empirical analysis is that there is evidence that a diffusion model without multi-scaling could reasonably well model the dynamics of a broadly diversified world stock index. in here

On the Empirical Importance of the Conditional Skewness Assumption in Modelling the Relationship between Risk and Return

NASA Astrophysics Data System (ADS)

Pipień, M.

2008-09-01

We present the results of an application of Bayesian inference in testing the relation between risk and return on the financial instruments. On the basis of the Intertemporal Capital Asset Pricing Model, proposed by Merton we built a general sampling distribution suitable in analysing this relationship. The most important feature of our assumptions is that the skewness of the conditional distribution of returns is used as an alternative source of relation between risk and return. This general specification relates to Skewed Generalized Autoregressive Conditionally Heteroscedastic-in-Mean model. In order to make conditional distribution of financial returns skewed we considered the unified approach based on the inverse probability integral transformation. In particular, we applied hidden truncation mechanism, inverse scale factors, order statistics concept, Beta and Bernstein distribution transformations and also a constructive method. Based on the daily excess returns on the Warsaw Stock Exchange Index we checked the empirical importance of the conditional skewness assumption on the relation between risk and return on the Warsaw Stock Market. We present posterior probabilities of all competing specifications as well as the posterior analysis of the positive sign of the tested relationship.

41 CFR 101-26.304 - Substitution policy.

Code of Federal Regulations, 2010 CFR

2010-07-01

... issued from new stock or from returned stock that is in serviceable condition (condition code A) as... 41 Public Contracts and Property Management 2 2010-07-01 2010-07-01 true Substitution policy. 101-26.304 Section 101-26.304 Public Contracts and Property Management Federal Property Management...

Stabilizing effect of volatility in financial markets

NASA Astrophysics Data System (ADS)

Valenti, Davide; Fazio, Giorgio; Spagnolo, Bernardo

2018-06-01

In financial markets, greater volatility is usually considered to be synonymous with greater risk and instability. However, large market downturns and upturns are often preceded by long periods where price returns exhibit only small fluctuations. To investigate this surprising feature, here we propose using the mean first hitting time, i.e., the average time a stock return takes to undergo for the first time a large negative (crashes) or positive variation (rallies), as an indicator of price stability, and relate this to a standard measure of volatility. In an empirical analysis of daily returns for 1071 stocks traded in the New York Stock Exchange, we find that this measure of stability displays nonmonotonic behavior, with a maximum, as a function of volatility. Also, we show that the statistical properties of the empirical data can be reproduced by a nonlinear Heston model. This analysis implies that, contrary to conventional wisdom, not only high, but also low volatility values can be associated with higher instability in financial markets. This proposed measure of stability can be extremely useful in risk control.

Single stock dynamics on high-frequency data: from a compressed coding perspective.

PubMed

Fushing, Hsieh; Chen, Shu-Chun; Hwang, Chii-Ruey

2014-01-01

High-frequency return, trading volume and transaction number are digitally coded via a nonparametric computing algorithm, called hierarchical factor segmentation (HFS), and then are coupled together to reveal a single stock dynamics without global state-space structural assumptions. The base-8 digital coding sequence, which is capable of revealing contrasting aggregation against sparsity of extreme events, is further compressed into a shortened sequence of state transitions. This compressed digital code sequence vividly demonstrates that the aggregation of large absolute returns is the primary driving force for stimulating both the aggregations of large trading volumes and transaction numbers. The state of system-wise synchrony is manifested with very frequent recurrence in the stock dynamics. And this data-driven dynamic mechanism is seen to correspondingly vary as the global market transiting in and out of contraction-expansion cycles. These results not only elaborate the stock dynamics of interest to a fuller extent, but also contradict some classical theories in finance. Overall this version of stock dynamics is potentially more coherent and realistic, especially when the current financial market is increasingly powered by high-frequency trading via computer algorithms, rather than by individual investors.

Fractality of profit landscapes and validation of time series models for stock prices

NASA Astrophysics Data System (ADS)

Yi, Il Gu; Oh, Gabjin; Kim, Beom Jun

2013-08-01

We apply a simple trading strategy for various time series of real and artificial stock prices to understand the origin of fractality observed in the resulting profit landscapes. The strategy contains only two parameters p and q, and the sell (buy) decision is made when the log return is larger (smaller) than p (-q). We discretize the unit square (p,q) ∈ [0,1] × [0,1] into the N × N square grid and the profit Π(p,q) is calculated at the center of each cell. We confirm the previous finding that local maxima in profit landscapes are scattered in a fractal-like fashion: the number M of local maxima follows the power-law form M ˜ Na, but the scaling exponent a is found to differ for different time series. From comparisons of real and artificial stock prices, we find that the fat-tailed return distribution is closely related to the exponent a ≈ 1.6 observed for real stock markets. We suggest that the fractality of profit landscape characterized by a ≈ 1.6 can be a useful measure to validate time series model for stock prices.

Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective

PubMed Central

Fushing, Hsieh; Chen, Shu-Chun; Hwang, Chii-Ruey

2014-01-01

High-frequency return, trading volume and transaction number are digitally coded via a nonparametric computing algorithm, called hierarchical factor segmentation (HFS), and then are coupled together to reveal a single stock dynamics without global state-space structural assumptions. The base-8 digital coding sequence, which is capable of revealing contrasting aggregation against sparsity of extreme events, is further compressed into a shortened sequence of state transitions. This compressed digital code sequence vividly demonstrates that the aggregation of large absolute returns is the primary driving force for stimulating both the aggregations of large trading volumes and transaction numbers. The state of system-wise synchrony is manifested with very frequent recurrence in the stock dynamics. And this data-driven dynamic mechanism is seen to correspondingly vary as the global market transiting in and out of contraction-expansion cycles. These results not only elaborate the stock dynamics of interest to a fuller extent, but also contradict some classical theories in finance. Overall this version of stock dynamics is potentially more coherent and realistic, especially when the current financial market is increasingly powered by high-frequency trading via computer algorithms, rather than by individual investors. PMID:24586235

Has microblogging changed stock market behavior? Evidence from China

NASA Astrophysics Data System (ADS)

Jin, Xi; Shen, Dehua; Zhang, Wei

2016-06-01

This paper examines the stock market behavior for a long-lived subset of firms in Shanghai and Shenzhen CSI 300 Index (CSI 300 Index) both before and after the establishment of firms' Microblogging in Sina Weibo. The empirical results show a significant increase in the relative trading volume as well as the decreases in the daily expected stock return and firm-level volatility in the post-Sina Weibo period. These findings suggest that Sina Weibo as an alternative information interaction channel has changed the information environment for individual stock, enhanced the speed of information diffusion and therefore changed the overall stock market behavior.

Multifractal property of Chinese stock market in the CSI 800 index based on MF-DFA approach

NASA Astrophysics Data System (ADS)

Zhu, Huijian; Zhang, Weiguo

2018-01-01

CSI 800 index consists of CSI 500 index and CSI 300 index, aiming to reflect the performance of stocks with large, mid and small size of China A share market. In this paper we analyze the multifractal structure of Chinese stock market in the CSI 800 index based on the multifractal detrended fluctuation analysis (MF-DFA) method. We find that the fluctuation of the closing logarithmic returns have multifractal properties, the shape and width of multifractal spectrum are depended on the weighing order q. More interestingly, we observe a bigger market crash in June-August 2015 than the one in 2008 based on the local Hurst exponents. The result provides important information for further study on dynamic mechanism of return fluctuation and whether it would trigger a new financial crisis.

Research on the fractal structure in the Chinese stock market

NASA Astrophysics Data System (ADS)

Zhuang, Xin-tian; Huang, Xiao-yuan; Sha, Yan-li

2004-02-01

Applying fractal theory, this paper probes and discusses self-similarity and scale invariance of the Chinese stock market. It analyses three kinds of scale indexes, i.e., autocorrelation index, Hurst index and the scale index on the basis of detrended fluctuation analysis (DFA) algorithm and promotes DFA into a recursive algorithm. Using the three kinds of scale indexes, we conduct empirical research on the Chinese Shanghai and Shenzhen stock markets. The results indicate that the rate of returns of the two stock markets does not obey the normal distribution. A correlation exists between the stock price indexes over time scales. The stock price indexes exhibit fractal time series. It indicates that the policy guide hidden at the back influences the characteristic of the Chinese stock market.

Bivariate sub-Gaussian model for stock index returns

NASA Astrophysics Data System (ADS)

Jabłońska-Sabuka, Matylda; Teuerle, Marek; Wyłomańska, Agnieszka

2017-11-01

Financial time series are commonly modeled with methods assuming data normality. However, the real distribution can be nontrivial, also not having an explicitly formulated probability density function. In this work we introduce novel parameter estimation and high-powered distribution testing methods which do not rely on closed form densities, but use the characteristic functions for comparison. The approach applied to a pair of stock index returns demonstrates that such a bivariate vector can be a sample coming from a bivariate sub-Gaussian distribution. The methods presented here can be applied to any nontrivially distributed financial data, among others.

27 CFR 46.252 - Claim based on error on return.

Code of Federal Regulations, 2011 CFR

2011-04-01

... PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Claims § 46.252 Claim based on error on return. If the dealer...

27 CFR 46.252 - Claim based on error on return.

Code of Federal Regulations, 2012 CFR

2012-04-01

... PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Claims § 46.252 Claim based on error on return. If the dealer...

27 CFR 46.252 - Claim based on error on return.

Code of Federal Regulations, 2014 CFR

2014-04-01

... PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Claims § 46.252 Claim based on error on return. If the dealer...

27 CFR 46.252 - Claim based on error on return.

Code of Federal Regulations, 2013 CFR

2013-04-01

... PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Claims § 46.252 Claim based on error on return. If the dealer...

27 CFR 46.252 - Claim based on error on return.

Code of Federal Regulations, 2010 CFR

2010-04-01

... PRODUCTS AND CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette Tubes Held for Sale on April 1, 2009 Claims § 46.252 Claim based on error on return. If the dealer...

A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test

NASA Astrophysics Data System (ADS)

Polanco-Martínez, J. M.; Fernández-Macho, J.; Neumann, M. B.; Faria, S. H.

2018-01-01

This paper presents an analysis of EU peripheral (so-called PIIGS) stock market indices and the S&P Europe 350 index (SPEURO), as a European benchmark market, over the pre-crisis (2004-2007) and crisis (2008-2011) periods. We computed a rolling-window wavelet correlation for the market returns and applied a non-linear Granger causality test to the wavelet decomposition coefficients of these stock market returns. Our results show that the correlation is stronger for the crisis than for the pre-crisis period. The stock market indices from Portugal, Italy and Spain were more interconnected among themselves during the crisis than with the SPEURO. The stock market from Portugal is the most sensitive and vulnerable PIIGS member, whereas the stock market from Greece tends to move away from the European benchmark market since the 2008 financial crisis till 2011. The non-linear causality test indicates that in the first three wavelet scales (intraweek, weekly and fortnightly) the number of uni-directional and bi-directional causalities is greater during the crisis than in the pre-crisis period, because of financial contagion. Furthermore, the causality analysis shows that the direction of the Granger cause-effect for the pre-crisis and crisis periods is not invariant in the considered time-scales, and that the causality directions among the studied stock markets do not seem to have a preferential direction. These results are relevant to better understand the behaviour of vulnerable stock markets, especially for investors and policymakers.

Impact of Stock Market Structure on Intertrade Time and Price Dynamics

NASA Astrophysics Data System (ADS)

Yuen, Ainslie; Ivanov, Plamen Ch.

2005-08-01

The NYSE and NASDAQ stock markets have very different structures and there is continuing controversy over whether differences in stock price behaviour are due to market structure or company characteristics. As the influence of market structure on stock prices may be obscured by exogenous factors such as demand and supply, we hypothesize that modulation of the flow of transactions due to market operations may carry a stronger imprint of the internal market mechanism. We analyse times between consecutive transactions (ITT) for NYSE and NASDAQ stocks, and we relate the dynamical properties of the ITT with those of the corresponding price fluctuations. We find a robust scale-invariant temporal organisation in the ITT of stocks which is independent of individual company characteristics and industry sector, but which depends on market structure. We find that stocks registered on the NASDAQ exhibit stronger correlations in their transaction timing within a trading day, compared with NYSE stocks. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing within a trading day, after the move, suggesting influences of market structure. Surprisingly, we also observe that stronger power-law correlations in the ITT are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of ITT and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ, we demonstrate that the higher correlations we find in ITT for NASDAQ stocks are matched by higher correlations in absolute price returns and by higher volatility, suggesting that market structure may affect price behaviour through information contained in transaction timing.

Empirical study of recent Chinese stock market

NASA Astrophysics Data System (ADS)

Jiang, J.; Li, W.; Cai, X.; Wang, Qiuping A.

2009-05-01

We investigate the statistical properties of the empirical data taken from the Chinese stock market during the time period from January, 2006 to July, 2007. By using the methods of detrended fluctuation analysis (DFA) and calculating correlation coefficients, we acquire the evidence of strong correlations among different stock types, stock index, stock volume turnover, A share (B share) seat number, and GDP per capita. In addition, we study the behavior of “volatility”, which is now defined as the difference between the new account numbers for two consecutive days. It is shown that the empirical power-law of the number of aftershock events exceeding the selected threshold is analogous to the Omori law originally observed in geophysics. Furthermore, we find that the cumulative distributions of stock return, trade volume and trade number are all exponential-like, which does not belong to the universality class of such distributions found by Xavier Gabaix et al. [Xavier Gabaix, Parameswaran Gopikrishnan, Vasiliki Plerou, H. Eugene Stanley, Nature, 423 (2003)] for major western markets. Through the comparison, we draw a conclusion that regardless of developed stock markets or emerging ones, “cubic law of returns” is valid only in the long-term absolute return, and in the short-term one, the distributions are exponential-like. Specifically, the distributions of both trade volume and trade number display distinct decaying behaviors in two separate regimes. Lastly, the scaling behavior of the relation is analyzed between dispersion and the mean monthly trade value for each administrative area in China.

Dynamic evolution of cross-correlations in the Chinese stock market.

PubMed

Ren, Fei; Zhou, Wei-Xing

2014-01-01

The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management.

Dynamic Evolution of Cross-Correlations in the Chinese Stock Market

PubMed Central

Ren, Fei; Zhou, Wei-Xing

2014-01-01

The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management. PMID:24867071

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems

PubMed Central

Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

2015-01-01

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

Evolution and anti-evolution in a minimal stock market model

NASA Astrophysics Data System (ADS)

Rothenstein, R.; Pawelzik, K.

2003-08-01

We present a novel microscopic stock market model consisting of a large number of random agents modeling traders in a market. Each agent is characterized by a set of parameters that serve to make iterated predictions of two successive returns. The future price is determined according to the offer and the demand of all agents. The system evolves by redistributing the capital among the agents in each trading cycle. Without noise the dynamics of this system is nearly regular and thereby fails to reproduce the stochastic return fluctuations observed in real markets. However, when in each cycle a small amount of noise is introduced we find the typical features of real financial time series like fat-tails of the return distribution and large temporal correlations in the volatility without significant correlations in the price returns. Introducing the noise by an evolutionary process leads to different scalings of the return distributions that depend on the definition of fitness. Because our realistic model has only very few parameters, and the results appear to be robust with respect to the noise level and the number of agents we expect that our framework may serve as new paradigm for modeling self-generated return fluctuations in markets.

Public option and private profits: what do markets expect?

PubMed

Milani, Fabio

2010-01-01

The debate on US healthcare reform has largely focused on the introduction of a public health plan option. While supporters stress various beneficial effects that would arise from increased competition in the health insurance market, opponents often contend that a public plan would drive insurers out of the market and potentially lead to the 'collapse' of the private health insurance industry. To contribute to the US healthcare reform debate by inferring, from financial market data, the effect that the public option is likely to have on the private health insurance market. The study utilized daily data on the price of a security that was traded in a prediction market from June 2009 and whose pay-off was tied to the event that a federal government-run healthcare plan - the 'public option' - would be approved by 31 December 2009 (100 daily observations). These data were combined with data on stock returns of health insurance companies (1500 observations from 100 trading days and 15 companies) to evaluate the expected effect of the public option on private health insurers. The impact on hospital companies (1000 observations) was also estimated. The results suggested that daily stock returns of health insurance companies significantly responded to the changing probability regarding the public option. A 10% increase in the probability that the public option would pass, on average, reduced the stock returns of health insurance companies by 1.28% (p < 0.001). Hospital company stock returns were also affected (0.9% reduction; p < 0.001). The results reveal the market expectation of a negative effect of the public option on the value of health insurance companies. The magnitude of the effect suggests a downward adjustment in the expected profits of health insurers of around 13%, but it does not support more calamitous scenarios.

Comparing the structure of an emerging market with a mature one under global perturbation

NASA Astrophysics Data System (ADS)

Namaki, A.; Jafari, G. R.; Raei, R.

2011-09-01

In this paper we investigate the Tehran stock exchange (TSE) and Dow Jones Industrial Average (DJIA) in terms of perturbed correlation matrices. To perturb a stock market, there are two methods, namely local and global perturbation. In the local method, we replace a correlation coefficient of the cross-correlation matrix with one calculated from two Gaussian-distributed time series, whereas in the global method, we reconstruct the correlation matrix after replacing the original return series with Gaussian-distributed time series. The local perturbation is just a technical study. We analyze these markets through two statistical approaches, random matrix theory (RMT) and the correlation coefficient distribution. By using RMT, we find that the largest eigenvalue is an influence that is common to all stocks and this eigenvalue has a peak during financial shocks. We find there are a few correlated stocks that make the essential robustness of the stock market but we see that by replacing these return time series with Gaussian-distributed time series, the mean values of correlation coefficients, the largest eigenvalues of the stock markets and the fraction of eigenvalues that deviate from the RMT prediction fall sharply in both markets. By comparing these two markets, we can see that the DJIA is more sensitive to global perturbations. These findings are crucial for risk management and portfolio selection.

Leverage effect in financial markets: the retarded volatility model.

PubMed

Bouchaud, J P; Matacz, A; Potters, M

2001-11-26

We investigate quantitatively the so-called "leverage effect," which corresponds to a negative correlation between past returns and future volatility. For individual stocks this correlation is moderate and decays over 50 days, while for stock indices it is much stronger but decays faster. For individual stocks the magnitude of this correlation has a universal value that can be rationalized in terms of a new "retarded" model which interpolates between a purely additive and a purely multiplicative stochastic process. For stock indices a specific amplification phenomenon seems to be necessary to account for the observed amplitude of the effect.

Increasing market efficiency in the stock markets

NASA Astrophysics Data System (ADS)

Yang, Jae-Suk; Kwak, Wooseop; Kaizoji, Taisei; Kim, In-Mook

2008-01-01

We study the temporal evolutions of three stock markets; Standard and Poor's 500 index, Nikkei 225 Stock Average, and the Korea Composite Stock Price Index. We observe that the probability density function of the log-return has a fat tail but the tail index has been increasing continuously in recent years. We have also found that the variance of the autocorrelation function, the scaling exponent of the standard deviation, and the statistical complexity decrease, but that the entropy density increases as time goes over time. We introduce a modified microscopic spin model and simulate the model to confirm such increasing and decreasing tendencies in statistical quantities. These findings indicate that these three stock markets are becoming more efficient.

Scaling and memory in volatility return intervals in financial markets

PubMed Central

Yamasaki, Kazuko; Muchnik, Lev; Havlin, Shlomo; Bunde, Armin; Stanley, H. Eugene

2005-01-01

For both stock and currency markets, we study the return intervals τ between the daily volatilities of the price changes that are above a certain threshold q. We find that the distribution function Pq(τ) scales with the mean return interval \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} \\begin{equation*}{\\bar {{\\tau}}}\\end{equation*}\\end{document} as \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} \\begin{equation*}P_{q}({\\tau})={\\bar {{\\tau}}}^{-1}f({\\tau}/{\\bar {{\\tau}}})\\end{equation*}\\end{document}. The scaling function f(x) is similar in form for all seven stocks and for all seven currency databases analyzed, and f(x) is consistent with a power-law form, f(x) ∼ x-γ with γ ≈ 2. We also quantify how the conditional distribution Pq(τ|τ0) depends on the previous return interval τ0 and find that small (or large) return intervals are more likely to be followed by small (or large) return intervals. This “clustering” of the volatility return intervals is a previously unrecognized phenomenon that we relate to the long-term correlations known to be present in the volatility. PMID:15980152

Scaling and memory in volatility return intervals in financial markets

NASA Astrophysics Data System (ADS)

Yamasaki, Kazuko; Muchnik, Lev; Havlin, Shlomo; Bunde, Armin; Stanley, H. Eugene

2005-06-01

For both stock and currency markets, we study the return intervals τ between the daily volatilities of the price changes that are above a certain threshold q. We find that the distribution function Pq(τ) scales with the mean return interval [Formula] as [Formula]. The scaling function f(x) is similar in form for all seven stocks and for all seven currency databases analyzed, and f(x) is consistent with a power-law form, f(x) ˜ x-γ with γ ≈ 2. We also quantify how the conditional distribution Pq(τ|τ0) depends on the previous return interval τ0 and find that small (or large) return intervals are more likely to be followed by small (or large) return intervals. This “clustering” of the volatility return intervals is a previously unrecognized phenomenon that we relate to the long-term correlations known to be present in the volatility. Author contributions: S.H. and H.E.S. designed research; K.Y., L.M., S.H., and H.E.S. performed research; A.B. contributed new reagents/analytic tools; A.B. analyzed data; and S.H. wrote the paper.Abbreviations: pdf, probability density function; S&P 500, Standard and Poor's 500 Index; USD, U.S. dollar; JPY, Japanese yen; SEK, Swedish krona.

26 CFR 1.1502-19 - Excess loss accounts.

Code of Federal Regulations, 2013 CFR

2013-04-01

... have a separate return year. (2) Excess loss accounts—(i) In general. M's basis in S's stock is... nonmember. (2) Nonrecognition or deferral—(i) In general. M's income or gain under paragraph (b)(1) of this... disposition is also described in paragraph (c)(1)(i) of this section). For example, if M transfers S's stock...

26 CFR 1.1502-19 - Excess loss accounts.

Code of Federal Regulations, 2011 CFR

2011-04-01

... have a separate return year. (2) Excess loss accounts—(i) In general. M's basis in S's stock is... nonmember. (2) Nonrecognition or deferral—(i) In general. M's income or gain under paragraph (b)(1) of this... disposition is also described in paragraph (c)(1)(i) of this section). For example, if M transfers S's stock...

26 CFR 1.1502-19 - Excess loss accounts.

Code of Federal Regulations, 2012 CFR

2012-04-01

... have a separate return year. (2) Excess loss accounts—(i) In general. M's basis in S's stock is... nonmember. (2) Nonrecognition or deferral—(i) In general. M's income or gain under paragraph (b)(1) of this... disposition is also described in paragraph (c)(1)(i) of this section). For example, if M transfers S's stock...

26 CFR 1.338-8 - Asset and stock consistency.

Code of Federal Regulations, 2014 CFR

2014-04-01

... section, no election under section 338 is deemed made or required with respect to target or any target... from target during the target consistency period and target is a subsidiary in a consolidated group. In... the consolidated return regulations in the basis of target stock and may reduce gain from the sale of...

26 CFR 1.338-8 - Asset and stock consistency.

Code of Federal Regulations, 2013 CFR

2013-04-01

... section, no election under section 338 is deemed made or required with respect to target or any target... from target during the target consistency period and target is a subsidiary in a consolidated group. In... the consolidated return regulations in the basis of target stock and may reduce gain from the sale of...

26 CFR 1.338-8 - Asset and stock consistency.

Code of Federal Regulations, 2012 CFR

2012-04-01

... section, no election under section 338 is deemed made or required with respect to target or any target... from target during the target consistency period and target is a subsidiary in a consolidated group. In... the consolidated return regulations in the basis of target stock and may reduce gain from the sale of...

Market impact and structure dynamics of the Chinese stock market based on partial correlation analysis

NASA Astrophysics Data System (ADS)

Li, Xing; Qiu, Tian; Chen, Guang; Zhong, Li-Xin; Wu, Xiao-Run

2017-04-01

Partial correlation analysis is employed to study the market impact on the Chinese stock market from both the native and external markets. Whereas the native market index is observed to have a great impact on the market correlations for both the Shanghai and Shenzhen stock markets, some external stock indices of the United States, European and Asian stock markets show a slight influence on the Chinese market. The individual stock can be affected by different economic sectors, but the dominant influence is from the sector the stock itself belongs to or closely related to, and the finance and insurance sector shows a weaker correlation with other economic sectors. Moreover, the market structure similarity exhibits a negative correlation with the price return in most time, and the structure similarity decays with the time interval.

Evolutionary model of stock markets

NASA Astrophysics Data System (ADS)

Kaldasch, Joachim

2014-12-01

The paper presents an evolutionary economic model for the price evolution of stocks. Treating a stock market as a self-organized system governed by a fast purchase process and slow variations of demand and supply the model suggests that the short term price distribution has the form a logistic (Laplace) distribution. The long term return can be described by Laplace-Gaussian mixture distributions. The long term mean price evolution is governed by a Walrus equation, which can be transformed into a replicator equation. This allows quantifying the evolutionary price competition between stocks. The theory suggests that stock prices scaled by the price over all stocks can be used to investigate long-term trends in a Fisher-Pry plot. The price competition that follows from the model is illustrated by examining the empirical long-term price trends of two stocks.

Intelligent Ensemble Forecasting System of Stock Market Fluctuations Based on Symetric and Asymetric Wavelet Functions

NASA Astrophysics Data System (ADS)

Lahmiri, Salim; Boukadoum, Mounir

2015-08-01

We present a new ensemble system for stock market returns prediction where continuous wavelet transform (CWT) is used to analyze return series and backpropagation neural networks (BPNNs) for processing CWT-based coefficients, determining the optimal ensemble weights, and providing final forecasts. Particle swarm optimization (PSO) is used for finding optimal weights and biases for each BPNN. To capture symmetry/asymmetry in the underlying data, three wavelet functions with different shapes are adopted. The proposed ensemble system was tested on three Asian stock markets: The Hang Seng, KOSPI, and Taiwan stock market data. Three statistical metrics were used to evaluate the forecasting accuracy; including, mean of absolute errors (MAE), root mean of squared errors (RMSE), and mean of absolute deviations (MADs). Experimental results showed that our proposed ensemble system outperformed the individual CWT-ANN models each with different wavelet function. In addition, the proposed ensemble system outperformed the conventional autoregressive moving average process. As a result, the proposed ensemble system is suitable to capture symmetry/asymmetry in financial data fluctuations for better prediction accuracy.

Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets

NASA Astrophysics Data System (ADS)

Zeng, Yayun; Wang, Jun; Xu, Kaixuan

2017-04-01

A new financial agent-based time series model is developed and investigated by multiscale-continuum percolation system, which can be viewed as an extended version of continuum percolation system. In this financial model, for different parameters of proportion and density, two Poisson point processes (where the radii of points represent the ability of receiving or transmitting information among investors) are applied to model a random stock price process, in an attempt to investigate the fluctuation dynamics of the financial market. To validate its effectiveness and rationality, we compare the statistical behaviors and the multifractal behaviors of the simulated data derived from the proposed model with those of the real stock markets. Further, the multiscale sample entropy analysis is employed to study the complexity of the returns, and the cross-sample entropy analysis is applied to measure the degree of asynchrony of return autocorrelation time series. The empirical results indicate that the proposed financial model can simulate and reproduce some significant characteristics of the real stock markets to a certain extent.

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Ge; Wang, Jun; Fang, Wen, E-mail: fangwen@bjtu.edu.cn

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also definedmore » in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.« less

Spread of risk across financial markets: better to invest in the peripheries

NASA Astrophysics Data System (ADS)

Pozzi, F.; Di Matteo, T.; Aste, T.

2013-04-01

Risk is not uniformly spread across financial markets and this fact can be exploited to reduce investment risk contributing to improve global financial stability. We discuss how, by extracting the dependency structure of financial equities, a network approach can be used to build a well-diversified portfolio that effectively reduces investment risk. We find that investments in stocks that occupy peripheral, poorly connected regions in financial filtered networks, namely Minimum Spanning Trees and Planar Maximally Filtered Graphs, are most successful in diversifying, improving the ratio between returns' average and standard deviation, reducing the likelihood of negative returns, while keeping profits in line with the general market average even for small baskets of stocks. On the contrary, investments in subsets of central, highly connected stocks are characterized by greater risk and worse performance. This methodology has the added advantage of visualizing portfolio choices directly over the graphic layout of the network.

Spread of risk across financial markets: better to invest in the peripheries

PubMed Central

Pozzi, F.; Di Matteo, T.; Aste, T.

2013-01-01

Risk is not uniformly spread across financial markets and this fact can be exploited to reduce investment risk contributing to improve global financial stability. We discuss how, by extracting the dependency structure of financial equities, a network approach can be used to build a well-diversified portfolio that effectively reduces investment risk. We find that investments in stocks that occupy peripheral, poorly connected regions in financial filtered networks, namely Minimum Spanning Trees and Planar Maximally Filtered Graphs, are most successful in diversifying, improving the ratio between returns' average and standard deviation, reducing the likelihood of negative returns, while keeping profits in line with the general market average even for small baskets of stocks. On the contrary, investments in subsets of central, highly connected stocks are characterized by greater risk and worse performance. This methodology has the added advantage of visualizing portfolio choices directly over the graphic layout of the network. PMID:23588852

A methodology for stochastic analysis of share prices as Markov chains with finite states.

PubMed

Mettle, Felix Okoe; Quaye, Enoch Nii Boi; Laryea, Ravenhill Adjetey

2014-01-01

Price volatilities make stock investments risky, leaving investors in critical position when uncertain decision is made. To improve investor evaluation confidence on exchange markets, while not using time series methodology, we specify equity price change as a stochastic process assumed to possess Markov dependency with respective state transition probabilities matrices following the identified state pace (i.e. decrease, stable or increase). We established that identified states communicate, and that the chains are aperiodic and ergodic thus possessing limiting distributions. We developed a methodology for determining expected mean return time for stock price increases and also establish criteria for improving investment decision based on highest transition probabilities, lowest mean return time and highest limiting distributions. We further developed an R algorithm for running the methodology introduced. The established methodology is applied to selected equities from Ghana Stock Exchange weekly trading data.

Identifying the critical financial ratios for stocks evaluation: A fuzzy delphi approach

NASA Astrophysics Data System (ADS)

Mokhtar, Mazura; Shuib, Adibah; Mohamad, Daud

2014-12-01

Stocks evaluation has always been an interesting and challenging problem for both researchers and practitioners. Generally, the evaluation can be made based on a set of financial ratios. Nevertheless, there are a variety of financial ratios that can be considered and if all ratios in the set are placed into the evaluation process, data collection would be more difficult and time consuming. Thus, the objective of this paper is to identify the most important financial ratios upon which to focus in order to evaluate the stock's performance. For this purpose, a survey was carried out using an approach which is based on an expert judgement, namely the Fuzzy Delphi Method (FDM). The results of this study indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share and debt to equity are the most important ratios.

Herd behaviors in the stock and foreign exchange markets

NASA Astrophysics Data System (ADS)

Kim, Kyungsik; Yoon, Seong-Min; Kim, Yup

2004-10-01

The herd behavior of returns for the won-dollar exchange rate and the Korean stock price index (KOSPI) is analyzed in Korean financial markets. It is reported that the probability distribution P( R) of returns R for three types of herding parameter satisfies the power-law behavior P( R)≃ R- β with the exponents β=2.2 (the won-dollar exchange rate) and 2.4 (the KOSPI). When the herding parameter h satisfies h⩾2.33, the crash regime in which P( R) increases with the increasing R appears. The active state of the transaction exists to decrease for h>2.33. Especially, we find that the distribution of normalized returns shows a crossover to a Gaussian distribution when the time step Δ t=252 is used. Our results will also be compared to the other well-known analyses.

Growth and smolting in lower-mode Atlantic Salmon stocked into the Penobscot River, Maine

USGS Publications Warehouse

Zydlewski, Joseph D.; O'Malley, Andrew; Cox, Oliver; Ruksznis, Peter; Trial, Joan G.

2014-01-01

Restoration of Atlantic Salmon Salmo salar in Maine has relied on hatchery-produced fry and smolts for critical stocking strategies. Stocking fry minimizes domestication selection, but these fish have poor survival. Conversely, stocked smolts have little freshwater experience but provide higher adult returns. Lower-mode (LM) fish, those not growing fast enough to ensure smolting by the time of stocking, are a by-product of the smolt program and are an intermediate hatchery product. From 2002 to 2009, between 70,000 and 170,000 marked LM Atlantic Salmon were stocked into the Pleasant River (a tributary in the Penobscot River drainage, Maine) in late September to early October. These fish were recaptured as actively migrating smolts (screw trapping), as nonmigrants (electrofishing), and as returning adults to the Penobscot River (Veazie Dam trap). Fork length (FL) was measured and a scale sample was taken to retrospectively estimate FL at winter annulus one (FW1) using the intercept-corrected direct proportion model. The LM fish were observed to migrate as age-1, age-2, and infrequently as age-3 smolts. Those migrating as age-1 smolts had a distinctly larger estimated FL at FW1 (>112 mm) than those that remained in the river for at least one additional year. At the time of migration, age-2 and age-3 smolts were substantially larger than age-1 smolts. Returning adult Atlantic Salmon of LM origin had estimated FLs at FW1 that corresponded to smolt age (greater FL for age 1 than age 2). The LM product produces both age-1 and age-2 smolts that have greater freshwater experience than hatchery smolts and may have growth and fitness advantages. The data from this study will allow managers to better assess the probability of smolting age and manipulate hatchery growth rates to produce a targeted-size LM product.

Close the High Seas to Fishing?

PubMed Central

White, Crow; Costello, Christopher

2014-01-01

The world's oceans are governed as a system of over 150 sovereign exclusive economic zones (EEZs, ∼42% of the ocean) and one large high seas (HS) commons (∼58% of ocean) with essentially open access. Many high-valued fish species such as tuna, billfish, and shark migrate around these large oceanic regions, which as a consequence of competition across EEZs and a global race-to-fish on the HS, have been over-exploited and now return far less than their economic potential. We address this global challenge by analyzing with a spatial bioeconomic model the effects of completely closing the HS to fishing. This policy both induces cooperation among countries in the exploitation of migratory stocks and provides a refuge sufficiently large to recover and maintain these stocks at levels close to those that would maximize fisheries returns. We find that completely closing the HS to fishing would simultaneously give rise to large gains in fisheries profit (>100%), fisheries yields (>30%), and fish stock conservation (>150%). We also find that changing EEZ size may benefit some fisheries; nonetheless, a complete closure of the HS still returns larger fishery and conservation outcomes than does a HS open to fishing. PMID:24667759

Complex network analysis of conventional and Islamic stock market in Indonesia

NASA Astrophysics Data System (ADS)

Rahmadhani, Andri; Purqon, Acep; Kim, Sehyun; Kim, Soo Yong

2015-09-01

The rising popularity of Islamic financial products in Indonesia has become a new interesting topic to be analyzed recently. We introduce a complex network analysis to compare conventional and Islamic stock market in Indonesia. Additionally, Random Matrix Theory (RMT) has been added as a part of reference to expand the analysis of the result. Both of them are based on the cross correlation matrix of logarithmic price returns. Closing price data, which is taken from June 2011 to July 2012, is used to construct logarithmic price returns. We also introduce the threshold value using winner-take-all approach to obtain scale-free property of the network. This means that the nodes of the network that has a cross correlation coefficient below the threshold value should not be connected with an edge. As a result, we obtain 0.5 as the threshold value for all of the stock market. From the RMT analysis, we found that there is only market wide effect on both stock market and no clustering effect has been found yet. From the network analysis, both of stock market networks are dominated by the mining sector. The length of time series of closing price data must be expanded to get more valuable results, even different behaviors of the system.

Herd behaviour experimental testing in laboratory artificial stock market settings. Behavioural foundations of stylised facts of financial returns

NASA Astrophysics Data System (ADS)

Manahov, Viktor; Hudson, Robert

2013-10-01

Many scholars express concerns that herding behaviour causes excess volatility, destabilises financial markets, and increases the likelihood of systemic risk. We use a special form of the Strongly Typed Genetic Programming (STGP) technique to evolve a stock market divided into two groups-a small subset of artificial agents called ‘Best Agents’ and a main cohort of agents named ‘All Agents’. The ‘Best Agents’ perform best in term of the trailing return of a wealth moving average. We then investigate whether herding behaviour can arise when agents trade Dow Jones, General Electric, and IBM financial instruments in four different artificial stock markets. This paper uses real historical quotes of the three financial instruments to analyse the behavioural foundations of stylised facts such as leptokurtosis, non-IIDness, and volatility clustering. We found evidence of more herding in a group of stocks than in individual stocks, but the magnitude of herding does not contribute to the mispricing of assets in the long run. Our findings suggest that the price formation process caused by the collective behaviour of the entire market exhibit less herding and is more efficient than the segmented market populated by a small subset of agents. Hence, greater genetic diversity leads to greater consistency with fundamental values and market efficiency.

Stock price change rate prediction by utilizing social network activities.

PubMed

Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Stock Price Change Rate Prediction by Utilizing Social Network Activities

PubMed Central

Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

Performance of technical trading rules: evidence from Southeast Asian stock markets.

PubMed

Tharavanij, Piyapas; Siraprapasiri, Vasan; Rajchamaha, Kittichai

2015-01-01

This paper examines the profitability of technical trading rules in the five Southeast Asian stock markets. The data cover a period of 14 years from January 2000 to December 2013. The instruments investigated are five Southeast Asian stock market indices: SET index (Thailand), FTSE Bursa Malaysia KLC index (Malaysia), FTSE Straits Times index (Singapore), JSX Composite index (Indonesia), and PSE composite index (the Philippines). Trading strategies investigated include Relative Strength Index, Stochastic oscillator, Moving Average Convergence-Divergence, Directional Movement Indicator and On Balance Volume. Performances are compared to a simple Buy-and-Hold. Statistical tests are also performed. Our empirical results show a strong performance of technical trading rules in an emerging stock market of Thailand but not in a more mature stock market of Singapore. The technical trading rules also generate statistical significant returns in the Malaysian, Indonesian and the Philippine markets. However, after taking transaction costs into account, most technical trading rules do not generate net returns. This fact suggests different levels of market efficiency among Southeast Asian stock markets. This paper finds three new insights. Firstly, technical indicators does not help much in terms of market timing. Basically, traders cannot expect to buy at a relative low price and sell at a relative high price by just using technical trading rules. Secondly, technical trading rules can be beneficial to individual investors as they help them to counter the behavioral bias called disposition effects which is the tendency to sell winning stocks too soon and holding on to losing stocks too long. Thirdly, even profitable strategies could not reliably predict subsequent market directions. They make money from having a higher average profit from profitable trades than an average loss from unprofitable ones.

10 CFR Appendix I to Part 504 - Procedures for the Computation of the Real Cost of Capital

Code of Federal Regulations, 2011 CFR

2011-01-01

.... Government 13-week Treasury Bills, B=The “beta” coefficient—the relationship between the excess return on common stock and the excess return on the S&P 500 composite index, and R m=The mean excess return on the... statements of firms, and investment bankers. (2) The predicted nominal cost of debt (R d) may be estimated by...

Impact of stock market structure on intertrade time and price dynamics.

PubMed

Ivanov, Plamen Ch; Yuen, Ainslie; Perakakis, Pandelis

2014-01-01

We analyse times between consecutive transactions for a diverse group of stocks registered on the NYSE and NASDAQ markets, and we relate the dynamical properties of the intertrade times with those of the corresponding price fluctuations. We report that market structure strongly impacts the scale-invariant temporal organisation in the transaction timing of stocks, which we have observed to have long-range power-law correlations. Specifically, we find that, compared to NYSE stocks, stocks registered on the NASDAQ exhibit significantly stronger correlations in their transaction timing on scales within a trading day. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing on scales within a trading day, indicating influences of market structure. We also report a persistent decrease in correlation strength of intertrade times with increasing average intertrade time and with corresponding decrease in companies' market capitalization-a trend which is less pronounced for NASDAQ stocks. Surprisingly, we observe that stronger power-law correlations in intertrade times are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of intertrade times and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ markets, we demonstrate that the stronger correlations we find in intertrade times for NASDAQ stocks are associated with stronger correlations in absolute price returns and with higher volatility, suggesting that market structure may affect price behavior through information contained in transaction timing. These findings do not support the hypothesis of universal scaling behavior in stock dynamics that is independent of company characteristics and stock market structure. Further, our results have implications for utilising transaction timing patterns in price prediction and risk management optimization on different stock markets.

Impact of Stock Market Structure on Intertrade Time and Price Dynamics

PubMed Central

Ivanov, Plamen Ch.; Yuen, Ainslie; Perakakis, Pandelis

2014-01-01

We analyse times between consecutive transactions for a diverse group of stocks registered on the NYSE and NASDAQ markets, and we relate the dynamical properties of the intertrade times with those of the corresponding price fluctuations. We report that market structure strongly impacts the scale-invariant temporal organisation in the transaction timing of stocks, which we have observed to have long-range power-law correlations. Specifically, we find that, compared to NYSE stocks, stocks registered on the NASDAQ exhibit significantly stronger correlations in their transaction timing on scales within a trading day. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing on scales within a trading day, indicating influences of market structure. We also report a persistent decrease in correlation strength of intertrade times with increasing average intertrade time and with corresponding decrease in companies' market capitalization–a trend which is less pronounced for NASDAQ stocks. Surprisingly, we observe that stronger power-law correlations in intertrade times are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of intertrade times and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ markets, we demonstrate that the stronger correlations we find in intertrade times for NASDAQ stocks are associated with stronger correlations in absolute price returns and with higher volatility, suggesting that market structure may affect price behavior through information contained in transaction timing. These findings do not support the hypothesis of universal scaling behavior in stock dynamics that is independent of company characteristics and stock market structure. Further, our results have implications for utilising transaction timing patterns in price prediction and risk management optimization on different stock markets. PMID:24699376

Asymmetry of price returns—Analysis and perspectives from a non-extensive statistical physics point of view

PubMed Central

Bil, Łukasz; Zienowicz, Magdalena

2017-01-01

We study how the approach grounded on non-extensive statistical physics can be applied to describe and distinguish different stages of the stock and money market development. A particular attention is given to asymmetric behavior of fat tailed distributions of positive and negative returns. A new method to measure this asymmetry is proposed. It is based on the value of the non-extensive Tsallis parameter q. The new quantifier of the relative asymmetry level between tails in terms of the Tsallis parameters q± is provided to analyze the effect of memory in data caused by nonlinear autocorrelations. The presented analysis takes into account data of separate stocks from the main developing stock market in Europe, i.e., the Warsaw Stock Exchange (WSE) in Poland and—for comparison—data from the most mature money market (Forex). It is argued that the proposed new quantifier is able to describe the stage of market development and its robustness to speculation. The main strength is put on a description and interpretation of the asymmetry between statistical properties of positive and negative returns for various stocks and for diversified time-lags Δt of data counting. The particular caution in this context is addressed to the difference between intraday and interday returns. Our search is extended to study memory effects and their dependence on the quotation frequency for similar large companies—owners of food-industrial retail supermarkets acting on both Polish and European markets (Eurocash, Jeronimo-Martins, Carrefour, Tesco)—but traded on various European stock markets of diversified economical maturity (respectively in Warsaw, Lisbon, Paris and London). The latter analysis seems to indicate quantitatively that stocks from the same economic sector traded on different markets within European Union (EU) may be a target of diversified level of speculations involved in trading independently on the true economic situation of the company. Our work thus gives indications that the statement:” where you are is more important than who you are” is true on trading markets. PMID:29190696

Distinguishing manipulated stocks via trading network analysis

NASA Astrophysics Data System (ADS)

Sun, Xiao-Qian; Cheng, Xue-Qi; Shen, Hua-Wei; Wang, Zhao-Yang

2011-10-01

Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a trading network is constructed to characterize the relations among its investors. In trading networks, nodes represent investors and a directed link connects a stock seller to a buyer with the total trade size as the weight of the link, and the node strength is the sum of all edge weights of a node. For all these trading networks, we find that the node degree and node strength both have tails following a power-law distribution. Compared with non-manipulated stocks, manipulated stocks have a high lower bound of the power-law tail, a high average degree of the trading network and a low correlation between the price return and the seller-buyer ratio. These findings may help us to detect manipulated stocks.

An analysis of the financial crisis in the KOSPI market using Hurst exponents

NASA Astrophysics Data System (ADS)

Yim, Kyubin; Oh, Gabjin; Kim, Seunghwan

2014-09-01

Recently, the study of the financial crisis has progressed to include the concept of the complex system, thereby improving the understanding of this extreme event from a neoclassical economic perspective. To determine which variables are related to the financial event caused by the 2008 US subprime crisis using temporal correlations, we investigate the diverse variables that may explain the financial system. These variables include return, volatility, trading volume and inter-trade duration data sets within the TAQ data for 27 highly capitalized individual companies listed on the KOSPI stock market. During 2008 and 2009, the Hurst exponent for the return time series over the whole period was less than 0.5, and the Hurst exponents for other variables, such as the volatility, trading volume and inter-trade duration, were greater than 0.5. Additionally, we analyze the relationships between the variation of temporal correlation and market instability based on these Hurst exponents and the degree of multifractality. We find that for the data related to trading volume, the Hurst exponents do not allow us to detect changes in market status, such as changes from normal to abnormal status, whereas other variables, including the return, volatility and weekly inter-trade duration, indicate a significant change in market status after the Lehman Brothers' bankruptcy. In addition, the multifractality and the measurement defined by subtracting the Hurst exponent of the return time series from that of the volatility time series decrease sharply after the US subprime event and recover approximately 50 days after the Lehman Brothers' collapse. Our findings suggest that the temporal features of financial quantities in the TAQ data set and the market complexity perform very well at diagnosing financial market stability.

Statistical physics approaches to financial fluctuations

NASA Astrophysics Data System (ADS)

Wang, Fengzhong

2009-12-01

Complex systems attract many researchers from various scientific fields. Financial markets are one of these widely studied complex systems. Statistical physics, which was originally developed to study large systems, provides novel ideas and powerful methods to analyze financial markets. The study of financial fluctuations characterizes market behavior, and helps to better understand the underlying market mechanism. Our study focuses on volatility, a fundamental quantity to characterize financial fluctuations. We examine equity data of the entire U.S. stock market during 2001 and 2002. To analyze the volatility time series, we develop a new approach, called return interval analysis, which examines the time intervals between two successive volatilities exceeding a given value threshold. We find that the return interval distribution displays scaling over a wide range of thresholds. This scaling is valid for a range of time windows, from one minute up to one day. Moreover, our results are similar for commodities, interest rates, currencies, and for stocks of different countries. Further analysis shows some systematic deviations from a scaling law, which we can attribute to nonlinear correlations in the volatility time series. We also find a memory effect in return intervals for different time scales, which is related to the long-term correlations in the volatility. To further characterize the mechanism of price movement, we simulate the volatility time series using two different models, fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) and fractional Brownian motion (fBm), and test these models with the return interval analysis. We find that both models can mimic time memory but only fBm shows scaling in the return interval distribution. In addition, we examine the volatility of daily opening to closing and of closing to opening. We find that each volatility distribution has a power law tail. Using the detrended fluctuation analysis (DFA) method, we show long-term auto-correlations in these volatility time series. We also analyze return, the actual price changes of stocks, and find that the returns over the two sessions are often anti-correlated.

Is there any overtrading in stock markets? The moderating role of big five personality traits and gender in a unilateral trend stock market.

PubMed

Zhang, Jian; Wang, Haocheng; Wang, Limin; Liu, Shuyi

2014-01-01

Overtrading is a common anomaly among stock investors. This study examines the relationship between overtrading and investment returns and the impact of the Big Five traits and gender on overtrading in a unilateral trend stock market using a simulated stock investment system. The data were derived from a sample of undergraduates from six universities who performed in a simulated stock investment situation and had their personality traits measured by the Big Five Personality Questionnaire. The results indicate that: (1) Overtrading was significant in rising stock markets, but not significant in falling markets. (2) The degree of female investors who overtraded was significant in rising markets. (3) The degree of overtrading investors who were high in extroversion or agreeableness was significant in rising markets. The implications of these results for more effective investment strategies are discussed.

Is There Any Overtrading in Stock Markets? The Moderating Role of Big Five Personality Traits and Gender in a Unilateral Trend Stock Market

PubMed Central

Zhang, Jian; Wang, Haocheng; Wang, Limin; Liu, Shuyi

2014-01-01

Overtrading is a common anomaly among stock investors. This study examines the relationship between overtrading and investment returns and the impact of the Big Five traits and gender on overtrading in a unilateral trend stock market using a simulated stock investment system. The data were derived from a sample of undergraduates from six universities who performed in a simulated stock investment situation and had their personality traits measured by the Big Five Personality Questionnaire. The results indicate that: (1) Overtrading was significant in rising stock markets, but not significant in falling markets. (2) The degree of female investors who overtraded was significant in rising markets. (3) The degree of overtrading investors who were high in extroversion or agreeableness was significant in rising markets. The implications of these results for more effective investment strategies are discussed. PMID:24475235

Impact of monetary policy changes on the Chinese monetary and stock markets

NASA Astrophysics Data System (ADS)

Tang, Yong; Luo, Yong; Xiong, Jie; Zhao, Fei; Zhang, Yi-Cheng

2013-10-01

The impact of monetary policy changes on the monetary market and stock market in China is investigated in this study. The changes of two major monetary policies, the interest rate and required reserve ratio, are analyzed in a study period covering seven years on the interbank monetary market and Shanghai stock market. We find that the monetary market is related to the macro economy trend and we also find that the monetary change surprises both of lowering and raising bring significant impacts to the two markets and the two markets respond to the changes differently. The results suggest that the impact of fluctuations is much larger for raising policy changes than lowering changes in the monetary market on policy announcing and effective dates. This is consistent with the “sign effect”, i.e. bad news brings a greater impact than good news. By studying the event window of each policy change, we also find that the “sign effect” still exists before and after each change in the monetary market. A relatively larger fluctuation is observed before the event date, which indicates that the monetary market might have a certain ability to predict a potential monetary change, while it is kept secret by the central bank before official announcement. In the stock market, we investigate how the returns and spreads of the Shanghai stock market index respond to the monetary changes. Evidences suggest the stock market is influenced but in a different way than the monetary market. The climbing of returns after the event dates for the lowering policy agrees with the theory that lowering changes can provide a monetary supply to boost the market and drive the stock returns higher but with a delay of 2 to 3 trading days on average. While in the bear market, the lowering policy brings larger volatility to the market on average than the raising ones. These empirical findings are useful for policymakers to understand how monetary policy changes impact the monetary and stock markets especially in an emerging market like China where the economy is booming and the policy changes impact the markets as surprises by the central bank without a pre-decided schedule. This is totally different from previous studies on FED, which follows pre-decided schedules for monetary policy changes.

Corporate Consolidation: An Event Study of Historic Stock Prices in the Defense Aerospace Industry

DTIC Science & Technology

2009-12-01

1994 Raytheon Xyplex Inc 1/3/1995 Boeing Precision Gear 4/3/1995 Raytheon Raytheon E-Systems Inc 6/30/1995 Raytheon Litwin Engineers & Construction...Acquirer 6/30/1995 Litwin Engineers & Construction Raytheon Arithmetic Return Logarithmic Return Note: * is significant at the 5% level 90

Multifractal structures for the Russian stock market

NASA Astrophysics Data System (ADS)

Ikeda, Taro

2018-02-01

In this paper, we apply the multifractal detrended fluctuation analysis (MFDFA) to the Russian stock price returns. To the best of our knowledge, this paper is the first to reveal the multifractal structures for the Russian stock market by financial crises. The contributions of the paper are twofold. (i) Finding the multifractal structures for the Russian stock market. The generalized Hurst exponents estimated become highly-nonlinear to the order of the fluctuation functions. (ii) Computing the multifractality degree according to Zunino et al. (2008). We find that the multifractality degree of the Russian stock market can be categorized within emerging markets, however, the Russian 1998 crisis and the global financial crisis dampen the degree when we consider the order of the polynomial trends in the MFDFA.

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student’s t-distribution*

PubMed Central

Leão, William L.; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor’s 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model. PMID:29333210

Microscopic Spin Model for the STOCK Market with Attractor Bubbling on Regular and Small-World Lattices

NASA Astrophysics Data System (ADS)

Krawiecki, A.

A multi-agent spin model for changes of prices in the stock market based on the Ising-like cellular automaton with interactions between traders randomly varying in time is investigated by means of Monte Carlo simulations. The structure of interactions has topology of a small-world network obtained from regular two-dimensional square lattices with various coordination numbers by randomly cutting and rewiring edges. Simulations of the model on regular lattices do not yield time series of logarithmic price returns with statistical properties comparable with the empirical ones. In contrast, in the case of networks with a certain degree of randomness for a wide range of parameters the time series of the logarithmic price returns exhibit intermittent bursting typical of volatility clustering. Also the tails of distributions of returns obey a power scaling law with exponents comparable to those obtained from the empirical data.

The value of information in a multi-agent market model. The luck of the uninformed

NASA Astrophysics Data System (ADS)

Tóth, B.; Scalas, E.; Huber, J.; Kirchler, M.

2007-01-01

We present an experimental and simulated model of a multi-agent stock market driven by a double auction order matching mechanism. Studying the effect of cumulative information on the performance of traders, we find a non monotonic relationship of net returns of traders as a function of information levels, both in the experiments and in the simulations. Particularly, averagely informed traders perform worse than the non informed and only traders with high levels of information (insiders) are able to beat the market. The simulations and the experiments reproduce many stylized facts of tick-by-tick stock-exchange data, such as fast decay of autocorrelation of returns, volatility clustering and fat-tailed distribution of returns. These results have an important message for everyday life. They can give a possible explanation why, on average, professional fund managers perform worse than the market index.

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student's t-distribution.

PubMed

Leão, William L; Abanto-Valle, Carlos A; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor's 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model.

Utility of antenatal clinical factors for prediction of postpartum outcomes in women with gestational diabetes mellitus (GDM).

PubMed

Ingram, Emily R; Robertson, Iain K; Ogden, Kathryn J; Dennis, Amanda E; Campbell, Joanne E; Corbould, Anne M

2017-06-01

Gestational diabetes mellitus (GDM) is associated with life-long increased risk of type 2 diabetes: affected women are advised to undergo oral glucose tolerance testing (OGTT) at 6-12 weeks postpartum, then glucose screening every 1-3 years. We investigated whether in women with GDM, antenatal clinical factors predicted postpartum abnormal glucose tolerance and compliance with screening. In women with GDM delivering 2007 to mid-2009 in a single hospital, antenatal/obstetric data and glucose tests at 6-12 weeks postpartum and during 5.5 years post-pregnancy were retrospectively collected. Predictors of return for testing and abnormal glucose tolerance were identified using multivariate analysis. Of 165 women, 117 (70.9%) returned for 6-12 week postpartum OGTT: 23 (19.6%) were abnormal. Smoking and parity, independent of socioeconomic status, were associated with non-return for testing. Fasting glucose ≥5.4 mmol/L on pregnancy OGTT predicted both non-return for testing and abnormal OGTT. During 5.5 years post-pregnancy, 148 (89.7%) women accessed glucose screening: nine (6.1%) developed diabetes, 33 (22.3%) had impaired fasting glucose / impaired glucose tolerance. Predictors of abnormal glucose tolerance were fasting glucose ≥5.4 mmol/L and 2-h glucose ≥9.3 mmol/L on pregnancy OGTT (~2.5-fold increased risk), and polycystic ovary syndrome (~3.4 fold increased risk). Risk score calculation, based on combined antenatal factors, did not improve predictions. Antenatal clinical factors were modestly predictive of return for testing and abnormal glucose tolerance post-pregnancy in women with GDM. Risk score calculations were ineffective in predicting outcomes: risk scores developed in other populations require validation. Ongoing glucose screening is indicated for all women with GDM. © 2016 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

Foraging under conditions of short-term exploitative competition: the case of stock traders

PubMed Central

Saavedra, Serguei; Malmgren, R. Dean; Switanek, Nicholas; Uzzi, Brian

2013-01-01

Theory purports that animal foraging choices evolve to maximize returns, such as net energy intake. Empirical research in both human and non-human animals reveals that individuals often attend to the foraging choices of their competitors while making their own foraging choices. Owing to the complications of gathering field data or constructing experiments, however, broad facts relating theoretically optimal and empirically realized foraging choices are only now emerging. Here, we analyse foraging choices of a cohort of professional day traders who must choose between trading the same stock multiple times in a row—patch exploitation—or switching to a different stock—patch exploration—with potentially higher returns. We measure the difference between a trader's resource intake and the competitors' expected intake within a short period of time—a difference we call short-term comparative returns. We find that traders' choices can be explained by foraging heuristics that maximize their daily short-term comparative returns. However, we find no one-best relationship between different trading choices and net income intake. This suggests that traders' choices can be short-term win oriented and, paradoxically, maybe maladaptive for absolute market returns. PMID:23363635

Relative persistence and dispersal of age-0 and age-1 largemouth bass stocked into two Ohio River embayments

USGS Publications Warehouse

Hartman, K.J.; Janney, E.C.

2006-01-01

In October of 1998 the West Virginia Division of Natural Resources stocked age-0 [mean total length (MTL) = 178 mm] and age-1 (MTL = 273 mm) hatchery-reared largemouth bass into two embayments of the Ohio River. Stocked fish were fitted with both an anchor tag and a visible implant elastomer mark. A multifaceted sampling approach was undertaken to (1) evaluate the persistence of stocked largemouth bass, (2) estimate fidelity of stocked largemouth bass to release sites, and (3) compare return rates of the two age classes. Although stocked largemouth bass comprised the majority (81%) of all bass captured in electrofishing surveys of the stocked embayments during fall 1998, catches declined rapidly during winter 1998, and by spring and summer 1999 stocked largemouth bass were virtually absent from electrofishing surveys. Creel surveys indicated no catch of stocked largemouth bass in the release sites after winter 1998. Electrofishing surveys, creel surveys, and angler call-ins all suggested stocked fish did not persist and either moved out of the stocked embayments or died. The results suggest that stocking advanced-size largemouth bass into these embayments only provided a limited and short-term enhancement of the fishery in those areas.

Skewness, long-time memory, and non-stationarity: Application to leverage effect in financial time series

NASA Astrophysics Data System (ADS)

Roman, H. E.; Porto, M.; Dose, C.

2008-10-01

We analyze daily log-returns data for a set of 1200 stocks, taken from US stock markets, over a period of 2481 trading days (January 1996-November 2005). We estimate the degree of non-stationarity in daily market volatility employing a polynomial fit, used as a detrending function. We find that the autocorrelation function of absolute detrended log-returns departs strongly from the corresponding original data autocorrelation function, while the observed leverage effect depends only weakly on trends. Such effect is shown to occur when both skewness and long-time memory are simultaneously present. A fractional derivative random walk model is discussed yielding a quantitative agreement with the empirical results.

Path integral for equities: Dynamic correlation and empirical analysis

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.; Cao, Yang; Lau, Ada; Tang, Pan

2012-02-01

This paper develops a model to describe the unequal time correlation between rate of returns of different stocks. A non-trivial fourth order derivative Lagrangian is defined to provide an unequal time propagator, which can be fitted to the market data. A calibration algorithm is designed to find the empirical parameters for this model and different de-noising methods are used to capture the signals concealed in the rate of return. The detailed results of this Gaussian model show that the different stocks can have strong correlation and the empirical unequal time correlator can be described by the model's propagator. This preliminary study provides a novel model for the correlator of different instruments at different times.

The dynamic interdependence of international financial markets: An empirical study on twenty-seven stock markets

NASA Astrophysics Data System (ADS)

Zhang, Xingwei; Zheng, Xiaolong; Zeng, Daniel Dajun

2017-04-01

In this paper, we aim to investigate the dynamic interdependence of international financial markets. Based on the data regarding daily returns of each market during the period 2006-2015 from Yahoo finance, we mainly focus on examining 27 markets from three continents, including Asia, America and Europe. By checking the dynamic interdependence between those markets, we find that markets from different continents have strong correlation at specific time shift. We also obtain that markets from different continents not only have a strong linkage with others at same day, but at a delay of one day, especially between Asia, Europe and Asia, America. In addition, we further analyze the time-varying influence strength between each two continents and observe that this value has abnormal changes during the financial crisis. These findings can provide us significant insights to understand the underlying dynamic interdependency of international financial markets and further help us make corresponding reasonable decisions.

Bull Market Helped Endowments Earn Average of 17.2% in 1996.

ERIC Educational Resources Information Center

Nicklin, Julie L.

1997-01-01

The National Association of College and University Business Officers' annual survey of 1996 college endowment performance found the rate of return up 15.5% from the previous year, the best since 1986. The average institution had 51.6% of endowment in domestic stocks, 25.5% in domestic fixed-income investments, 9.5% in foreign stock, 5.4% in cash…

High quality topic extraction from business news explains abnormal financial market volatility.

PubMed

Hisano, Ryohei; Sornette, Didier; Mizuno, Takayuki; Ohnishi, Takaaki; Watanabe, Tsutomu

2013-01-01

Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affects trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affects stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their "thematic" features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized facts in financial economies, namely that at certain times trading volumes appear to be "abnormally large," can be partially explained by the flow of news. In this sense, our results prove that there is no "excess trading," when restricting to times when news is genuinely novel and provides relevant financial information.

Soccer and stock market risk: empirical evidence from the Istanbul Stock Exchange.

PubMed

Berument, M Hakan; Ceylan, Nildag Basak

2013-06-01

There is an emerging but important literature on the effects of sport events such as soccer on stock market returns. After a soccer team's win, agents discount future events more favorably and increase risk tolerance. Similarly, after a loss, risk tolerance decreases. This paper directly assesses risk tolerance after a sports event by using daily data from the three major soccer teams in Turkey (Beşiktaşç Fenerbahge and Galatasaray). Results provide evidence that risk tolerance increases after a win, but similar patterns were not found after a loss.

A Comparison of Six Repair Scheduling Policies for the P3 Aircraft.

DTIC Science & Technology

1988-03-01

each type component i: RHO(i) = LAMBDA(i) / SRATE(i) LINEUPti) - RHO(i) x COUNT(i) Step 14c: Sort components by LINEUP (i), reorder position in line in...favor of the largest LINEUP (i). Return to step 7. Dynamic 3 Model Modifications: Step 14a: Count the number of operating parts of each component i...STOCK(i)). Step 14b: Assign a priority to each component type based on the count of current stock in step 14a: LINEUP (i) < LINEUP (J) iff STOCK(i

26 CFR 1.6037-1 - Return of electing small business corporation.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 26 Internal Revenue 13 2011-04-01 2011-04-01 false Return of electing small business corporation... small business corporation. (a) In general. Every small business corporation (as defined in section 1371... corporation: (1) The names and addresses of all persons owning stock in the corporation at any time during the...

18 CFR 2.15 - Specified reasonable rate of return.

Code of Federal Regulations, 2011 CFR

2011-04-01

... average cost of long-term debt and preferred stock for the year, and the cost of common equity shall be... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Specified reasonable rate of return. 2.15 Section 2.15 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY...

How Volatilities Nonlocal in Time Affect the Price Dynamics in Complex Financial Systems

PubMed Central

Tan, Lei; Zheng, Bo; Chen, Jun-Jie; Jiang, Xiong-Fei

2015-01-01

What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time. PMID:25723154

Return volatility interval analysis of stock indexes during a financial crash

NASA Astrophysics Data System (ADS)

Li, Wei-Shen; Liaw, Sy-Sang

2015-09-01

We investigate the interval between return volatilities above a certain threshold q for 10 countries data sets during the 2008/2009 global financial crisis, and divide these data into several stages according to stock price tendencies: plunging stage (stage 1), fluctuating or rebounding stage (stage 2) and soaring stage (stage 3). For different thresholds q, the cumulative distribution function always satisfies a power law tail distribution. We find the absolute value of the power-law exponent is lowest in stage 1 for various types of markets, and increases monotonically from stage 1 to stage 3 in emerging markets. The fractal dimension properties of the return volatility interval series provide some surprising results. We find that developed markets have strong persistence and transform to weaker correlation in the plunging and soaring stages. In contrast, emerging markets fail to exhibit such a transformation, but rather show a constant-correlation behavior with the recurrence of extreme return volatility in corresponding stages during a crash. We believe this long-memory property found in recurrence-interval series, especially for developed markets, plays an important role in volatility clustering.

Structure of a financial cross-correlation matrix under attack

NASA Astrophysics Data System (ADS)

Lim, Gyuchang; Kim, SooYong; Kim, Junghwan; Kim, Pyungsoo; Kang, Yoonjong; Park, Sanghoon; Park, Inho; Park, Sang-Bum; Kim, Kyungsik

2009-09-01

We investigate the structure of a perturbed stock market in terms of correlation matrices. For the purpose of perturbing a stock market, two distinct methods are used, namely local and global perturbation. The former involves replacing a correlation coefficient of the cross-correlation matrix with one calculated from two Gaussian-distributed time series while the latter reconstructs the cross-correlation matrix just after replacing the original return series with Gaussian-distributed time series. Concerning the local case, it is a technical study only and there is no attempt to model reality. The term ‘global’ means the overall effect of the replacement on other untouched returns. Through statistical analyses such as random matrix theory (RMT), network theory, and the correlation coefficient distributions, we show that the global structure of a stock market is vulnerable to perturbation. However, apart from in the analysis of inverse participation ratios (IPRs), the vulnerability becomes dull under a small-scale perturbation. This means that these analysis tools are inappropriate for monitoring the whole stock market due to the low sensitivity of a stock market to a small-scale perturbation. In contrast, when going down to the structure of business sectors, we confirm that correlation-based business sectors are regrouped in terms of IPRs. This result gives a clue about monitoring the effect of hidden intentions, which are revealed via portfolios taken mostly by large investors.

Trade-offs between forest carbon stocks and harvests in a steady state - A multi-criteria analysis.

PubMed

Pingoud, Kim; Ekholm, Tommi; Sievänen, Risto; Huuskonen, Saija; Hynynen, Jari

2018-03-15

This paper provides a perspective for comparing trade-offs between harvested wood flows and forest carbon stocks with different forest management regimes. A constant management regime applied to a forest area with an even age-class distribution leads to a steady state, in which the annual harvest and carbon stocks remain constant over time. As both are desirable - carbon stocks for mitigating climate change and harvests for the economic use of wood and displacing fossil fuels - an ideal strategy should be chosen from a set of management regimes that are Pareto-optimal in the sense of multi-criteria decision-making. When choosing between Pareto-optimal alternatives, the trade-off between carbon stock and harvests is unavoidable. This trade-off can be described e.g. in terms of carbon payback times or carbon returns. As numerical examples, we present steady-state harvest levels and carbon stocks in a Finnish boreal forest region for different rotation periods, thinning intensities and collection patterns for harvest residues. In the set of simulated management practices, harvest residue collection presents the most favorable trade-off with payback times around 30-40 years; while Pareto-optimal changes in rotation or thinnings exhibited payback times over 100 years, or alternatively carbon returns below 1%. By extending the rotation period and using less-intensive thinnings compared to current practices, the steady-state carbon stocks could be increased by half while maintaining current harvest levels. Additional cases with longer rotation periods should be also considered, but were here excluded due to the lack of reliable data on older forest stands. Copyright © 2018 Elsevier Ltd. All rights reserved.

Understanding the multifractality in portfolio excess returns

NASA Astrophysics Data System (ADS)

Chen, Cheng; Wang, Yudong

2017-01-01

The multifractality in stock returns have been investigated extensively. However, whether the autocorrelations in portfolio returns are multifractal have not been considered in the literature. In this paper, we detect multifractal behavior of returns of portfolios constructed based on two popular trading rules, size and book-to-market (BM) ratio. Using the multifractal detrended fluctuation analysis, we find that the portfolio returns are significantly multifractal and the multifractality is mainly attributed to long-range dependence. We also investigate the multifractal cross-correlation between portfolio return and market average return using the detrended cross-correlation analysis. Our results show that the cross-correlations of small fluctuations are persistent, while those of large fluctuations are anti-persistent.

Alternate entropy measure for assessing volatility in financial markets.

PubMed

Bose, Ranjan; Hamacher, Kay

2012-11-01

We propose two alternate information theoretical approaches to assess non-Gaussian fluctuations in the return dynamics of financial markets. Specifically, we use superinformation, which is a measure of the disorder of the entropy of time series. We argue on theoretical grounds on its usefulness and show that it can be applied effectively for analyzing returns. A study of stock market data for over five years has been carried out using this approach. We show how superinformation helps to identify and classify important signals in the time series. The financial crisis of 2008 comes out very clearly in the superinformation plots. In addition, we introduce the super mutual information. Distinct super mutual information signatures are observed that might be used to mitigate idiosyncratic risk. The universality of our approach has been tested by carrying out the analysis for the 100 stocks listed in S&P100 index. The average superinformation values for the S&P100 stocks correlates very well with the VIX.

Inverse Statistics and Asset Allocation Efficiency

NASA Astrophysics Data System (ADS)

Bolgorian, Meysam

In this paper using inverse statistics analysis, the effect of investment horizon on the efficiency of portfolio selection is examined. Inverse statistics analysis is a general tool also known as probability distribution of exit time that is used for detecting the distribution of the time in which a stochastic process exits from a zone. This analysis was used in Refs. 1 and 2 for studying the financial returns time series. This distribution provides an optimal investment horizon which determines the most likely horizon for gaining a specific return. Using samples of stocks from Tehran Stock Exchange (TSE) as an emerging market and S&P 500 as a developed market, effect of optimal investment horizon in asset allocation is assessed. It is found that taking into account the optimal investment horizon in TSE leads to more efficiency for large size portfolios while for stocks selected from S&P 500, regardless of portfolio size, this strategy does not only not produce more efficient portfolios, but also longer investment horizons provides more efficiency.

Unraveling hidden order in the dynamics of developed and emerging markets.

PubMed

Berman, Yonatan; Shapira, Yoash; Ben-Jacob, Eshel

2014-01-01

The characterization of asset price returns is an important subject in modern finance. Traditionally, the dynamics of stock returns are assumed to lack any temporal order. Here we present an analysis of the autocovariance of stock market indices and unravel temporal order in several major stock markets. We also demonstrate a fundamental difference between developed and emerging markets in the past decade - emerging markets are marked by positive order in contrast to developed markets whose dynamics are marked by weakly negative order. In addition, the reaction to financial crises was found to be reversed among developed and emerging markets, presenting large positive/negative autocovariance spikes following the onset of these crises. Notably, the Chinese market shows neutral or no order while being regarded as an emerging market. These findings show that despite the coupling between international markets and global trading, major differences exist between different markets, and demonstrate that the autocovariance of markets is correlated with their stability, as well as with their state of development.

Unraveling Hidden Order in the Dynamics of Developed and Emerging Markets

PubMed Central

Berman, Yonatan; Shapira, Yoash; Ben-Jacob, Eshel

2014-01-01

The characterization of asset price returns is an important subject in modern finance. Traditionally, the dynamics of stock returns are assumed to lack any temporal order. Here we present an analysis of the autocovariance of stock market indices and unravel temporal order in several major stock markets. We also demonstrate a fundamental difference between developed and emerging markets in the past decade - emerging markets are marked by positive order in contrast to developed markets whose dynamics are marked by weakly negative order. In addition, the reaction to financial crises was found to be reversed among developed and emerging markets, presenting large positive/negative autocovariance spikes following the onset of these crises. Notably, the Chinese market shows neutral or no order while being regarded as an emerging market. These findings show that despite the coupling between international markets and global trading, major differences exist between different markets, and demonstrate that the autocovariance of markets is correlated with their stability, as well as with their state of development. PMID:25383630

Alternate entropy measure for assessing volatility in financial markets

NASA Astrophysics Data System (ADS)

Bose, Ranjan; Hamacher, Kay

2012-11-01

We propose two alternate information theoretical approaches to assess non-Gaussian fluctuations in the return dynamics of financial markets. Specifically, we use superinformation, which is a measure of the disorder of the entropy of time series. We argue on theoretical grounds on its usefulness and show that it can be applied effectively for analyzing returns. A study of stock market data for over five years has been carried out using this approach. We show how superinformation helps to identify and classify important signals in the time series. The financial crisis of 2008 comes out very clearly in the superinformation plots. In addition, we introduce the super mutual information. Distinct super mutual information signatures are observed that might be used to mitigate idiosyncratic risk. The universality of our approach has been tested by carrying out the analysis for the 100 stocks listed in S&P100 index. The average superinformation values for the S&P100 stocks correlates very well with the VIX.

An application of almost marginal conditional stochastic dominance (AMCSD) on forming efficient portfolios

NASA Astrophysics Data System (ADS)

Slamet, Isnandar; Mardiana Putri Carissa, Siska; Pratiwi, Hasih

2017-10-01

Investors always seek an efficient portfolio which is a portfolio that has a maximum return on specific risk or minimal risk on specific return. Almost marginal conditional stochastic dominance (AMCSD) criteria can be used to form the efficient portfolio. The aim of this research is to apply the AMCSD criteria to form an efficient portfolio of bank shares listed in the LQ-45. This criteria is used when there are areas that do not meet the criteria of marginal conditional stochastic dominance (MCSD). On the other words, this criteria can be derived from quotient of areas that violate the MCSD criteria with the area that violate and not violate the MCSD criteria. Based on the data bank stocks listed on LQ-45, it can be stated that there are 38 efficient portfolios of 420 portfolios where each portfolio comprises of 4 stocks and 315 efficient portfolios of 1710 portfolios with each of portfolio has 3 stocks.

U.S. stock market interaction network as learned by the Boltzmann machine

DOE PAGES

Borysov, Stanislav S.; Roudi, Yasser; Balatsky, Alexander V.

2015-12-07

Here, we study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented results show that binarization preserves the correlation structure of the market. Properties of distributions of external fields and couplings as well as themore » market interaction network and industry sector clustering structure are studied for different historical dates and moving window sizes. We demonstrate that the observed positive heavy tail in distribution of couplings is related to the sparse clustering structure of the market. We also show that discrepancies between the model’s parameters might be used as a precursor of financial instabilities.« less

Alternative models of climatic effects on sockeye salmon (Oncorhynchus nerka) productivity in Bristol Bay, Alaska, and the Fraser River, British Columbia

USGS Publications Warehouse

Adkison, M.; Peterman, R.; Lapointe, M.; Gillis, D.; Korman, J.

1996-01-01

We compare alternative models of sockeye salmon (Oncorhynchus nerka) productivity (returns per spawner) using more than 30 years of catch and escapement data for Bristol Bay, Alaska, and the Fraser River, British Columbia. The models examined include several alternative forms of models that incorporate climatic influences as well as models not based on climate. For most stocks, a stationary stock-recruitment relationship explains very little of the interannual variation in productivity. In Bristol Bay, productivity co-varies among stocks and appears to be strongly related to fluctuations in climate. The best model for Bristol Bay sockeye involved a change in the 1970s in the parameters of the Ricker stock-recruitment curve; the stocks generally became more productive. In contrast, none of the models of Fraser River stocks that we examined explained much of the variability in their productivity.

Stock price analysis of sustainable foreign investment companies in Indonesia

NASA Astrophysics Data System (ADS)

Fachrudin, Khaira Amalia

2018-03-01

The stock price is determined by demand and supply in the stock market. Stock price reacts to information. Sustainable investment is an investment that considers environmental sustainability and human rights. This study aims to predict the probability of above average stock price by including the sustainability index as one of its variables. The population is all foreign investment companies in Indonesia. The target population is companies that distribute dividends – also as a sample. The analysis tool is a logistic regression. At 5% alpha, it was found that sustainability index did not have the probability to increase stock price average. The significant effects are free cash flow and cost of debt. However, sustainability index can increase the Negelkarke R square. The implication is that the awareness of sustainability is still necesary to be improved because from the research result it can be seen that investors only consider the risk and return.

The foreign exchange market: return distributions, multifractality, anomalous multifractality and the Epps effect

NASA Astrophysics Data System (ADS)

Drożdż, Stanisław; Kwapień, Jarosław; Oświȩcimka, Paweł; Rak, Rafał

2010-10-01

We present a systematic study of various statistical characteristics of high-frequency returns from the foreign exchange market. This study is based on six exchange rates forming two triangles: EUR-GBP-USD and GBP-CHF-JPY. It is shown that the exchange rate return fluctuations for all of the pairs considered are well described by the non-extensive statistics in terms of q-Gaussians. There exist some small quantitative variations in the non-extensivity q-parameter values for different exchange rates (which depend also on the time scales studied), and this can be related to the importance of a given exchange rate in the world's currency trade. Temporal correlations organize the series of returns such that they develop the multifractal characteristics for all of the exchange rates, with a varying degree of symmetry of the singularity spectrum f(α), however. The most symmetric spectrum is identified for the GBP/USD. We also form time series of triangular residual returns and find that the distributions of their fluctuations develop disproportionately heavier tails as compared to small fluctuations, which excludes description in terms of q-Gaussians. The multifractal characteristics of these residual returns reveal such anomalous properties as negative singularity exponents and even negative singularity spectra. Such anomalous multifractal measures have so far been considered in the literature in connection with diffusion-limited aggregation and with turbulence. Studying the cross-correlations among different exchange rates, we found that market inefficiency on short time scales leads to the occurrence of the Epps effect on much longer time scales, but comparable to the ones for the stock market. Although the currency market is much more liquid than the stock markets and has a much greater transaction frequency, the building up of correlations takes up to several hours—a duration that does not differ much from what is observed in the stock markets. This may suggest that non-synchronicity of transactions is not the unique source of the observed effect.

Spend Less and Get More: How to Stock Up Your Classroom without Breaking the Bank

ERIC Educational Resources Information Center

McWilliams-Abendroth, Christie

2012-01-01

The author's classroom is bare, and the school supplies she received are long gone. After realizing how much money she was spending on her classroom each year, she decided to find other resources besides her credit card to stock up her classroom. In this article, the author shares some strategies that provided more return with a lower investment.

Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications

NASA Astrophysics Data System (ADS)

Shahzad, Syed Jawad Hussain; Kumar, Ronald Ravinesh; Ali, Sajid; Ameer, Saba

2016-09-01

The interdependence of Greece and other European stock markets and the subsequent portfolio implications are examined in wavelet and variational mode decomposition domain. In applying the decomposition techniques, we analyze the structural properties of data and distinguish between short and long term dynamics of stock market returns. First, the GARCH-type models are fitted to obtain the standardized residuals. Next, different copula functions are evaluated, and based on the conventional information criteria and time varying parameter, Joe-Clayton copula is chosen to model the tail dependence between the stock markets. The short-run lower tail dependence time paths show a sudden increase in comovement during the global financial crises. The results of the long-run dependence suggest that European stock markets have higher interdependence with Greece stock market. Individual country's Value at Risk (VaR) separates the countries into two distinct groups. Finally, the two-asset portfolio VaR measures provide potential markets for Greece stock market investment diversification.

Quantifying the effect of investors' attention on stock market.

PubMed

Yang, Zhen-Hua; Liu, Jian-Guo; Yu, Chang-Rui; Han, Jing-Ti

2017-01-01

The investors' attention has been extensively used to predict the stock market. Different from existing proxies of the investors' attention, such as the Google trends, Baidu index (BI), we argue the collective attention from the stock trading platforms could reflect the investors' attention more closely. By calculated the increments of the attention volume for each stock (IAVS) from the stock trading platforms, we investigate the effect of investors' attention measured by the IAVS on the movement of the stock market. The experimental results for Chinese Securities Index 100 (CSI100) show that the BI is significantly correlated with the returns of CSI100 at 1% significance level only in 2014. However, it should be emphasized that the correlation of the new proposed measure, namely IAVS, is significantly at 1% significance level in 2014 and 2015. It shows that the effect of the measure IAVS on the movement of the stock market is more stable and significant than BI. This study yields important invest implications and better understanding of collective investors' attention.

Quantifying the effect of investors’ attention on stock market

PubMed Central

Yang, Zhen-Hua; Liu, Jian-Guo; Yu, Chang-Rui; Han, Jing-Ti

2017-01-01

The investors’ attention has been extensively used to predict the stock market. Different from existing proxies of the investors’ attention, such as the Google trends, Baidu index (BI), we argue the collective attention from the stock trading platforms could reflect the investors’ attention more closely. By calculated the increments of the attention volume for each stock (IAVS) from the stock trading platforms, we investigate the effect of investors’ attention measured by the IAVS on the movement of the stock market. The experimental results for Chinese Securities Index 100 (CSI100) show that the BI is significantly correlated with the returns of CSI100 at 1% significance level only in 2014. However, it should be emphasized that the correlation of the new proposed measure, namely IAVS, is significantly at 1% significance level in 2014 and 2015. It shows that the effect of the measure IAVS on the movement of the stock market is more stable and significant than BI. This study yields important invest implications and better understanding of collective investors’ attention. PMID:28542216

Graded Compression Stockings Prevent Post-spaceflight Orthostatic Hypotension

NASA Technical Reports Server (NTRS)

Platts, S. H.; Brown, A. K.; Locke, J.; Stenger, M. B.

2008-01-01

Post-spaceflight orthostatic intolerance is characterized by hypotension and presyncope in 20-30% of returning astronauts. Previous data from our laboratory suggests that this is largely a result of decreased venous return. Currently, NASA astronauts wear an anti-gravity suit (AGS) which consists of inflatable air bladders over the calves, thighs and abdomen, which are typically pressurized from 0.5 to 1.5 PSI (27 to 78 mmHg). ISS crew members sometimes wear Russian Kentavr suits which consist of laced compression shorts and gaiters, providing 30 mmHg nominally. While these garments are effective during reentry, there are a number of drawbacks that make them impractical for postflight use. We studied the ability of commercially available, custom fit, graded compression stockings (Jobst, 55 mmHg at ankle to 6 mmHg at top of thigh, 25 mmHg mean compression) to prevent postflight orthostatic intolerance, hypothesizing that these garments would prevent orthostatic intolerance following short duration space flight. Crew members from a single Space Shuttle flight were tilted to 80 degrees for 10 min while wearing the stockings (n=5 males) upon arrival at the clinic (2 hrs after landing). Hemodynamic data were compared to data from all crewmembers tilted (without countermeasures) since return to flight (n=9). Two-way, repeated measures ANOVA, using the entire tilt time curve (0-10 min) show that systolic blood pressure (SBP, group effect p=0.008), stroke volume (SV, group effect p=0.003), and cardiac output (CO, group effect p=0.004) were higher in crewmembers who wore the Jobst stockings. A one-way ANOVA comparing the last minute standing also showed that SV (p=0.001) and CO (p less than 0.001) were higher and SBP tended to be higher (p=0.06) in Jobst subjects compared to controls. Control subjects had a higher rate of presyncope than Jobst subjects (3/9 vs 0/5) during the tilt on landing day. Orthostatic hypotension continues to present following spaceflight, despite fluid loading and other countermeasures. This preliminary study shows that commercially available compression stockings may ameliorate this problem. These stockings are readily available, inexpensive, and can be worn for days following landing. We have observed similar protection against orthostatic intolerance in ground-based studies of hypovolemic test subjects. Further refinements to the design and compression of the stockings are in progress.

Steelhead Supplementation in Idaho Rivers : 2001 Project Progress Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrne, Alan

In 2001, Idaho Department of Fish and Game (IDFG) continued an assessment of the Sawtooth Hatchery steelhead Oncorhynchus mykiss stock to reestablish natural populations in Beaver and Frenchman creeks in the upper Salmon River. Crews stocked both streams with 20 pair of hatchery adults, and I estimated the potential smolt production from the 2000 adult outplants. n the Red River drainage, IDFG stocked Dworshak hatchery stock fingerlings and smolts from 1993 to 1999 to assess which life stage produces more progeny when the adults return to spawn. In 2001, IDFG operated the Red River weir to trap adults that returnedmore » from these stockings, but none were caught from either group. Wild steelhead populations in the Lochsa and Selway river drainages were assessed and the chinook salmon Oncorhynchus tshawytscha escapement was enumerated in Fish Creek. I estimated that 75 wild adult steelhead and 122 adult chinook salmon returned to Fish Creek in 2001. I estimated that slightly more than 30,000 juvenile steelhead migrated out of Fish Creek. This is the largest number of steelhead to migrate out of Fish Creek in a single year since I began estimating the yearly migration in 1994. Juvenile steelhead densities in Lochsa and Selway tributaries were somewhat higher in 2001 than those observed in 2000. Crews from IDFG collected over 4,800 fin samples from wild steelhead in 74 streams of the Clearwater, Snake, and Salmon river drainages and from five hatchery stocks during the summer of 2000 for a DNA analysis to assess Idaho's steelhead stock structure. The DNA analysis was subcontracted to Dr. Jennifer Nielsen, Alaska Biological Science Center, Anchorage. Her lab developed protocols to use for the analysis in 2001 and is continuing to analyze the samples. Dr. Nielsen plans to have the complete set of wild and hatchery stocks analyzed in 2002.« less

Movement of reservoir-stocked riverine fish between tailwaters and rivers

USGS Publications Warehouse

Spoelstra, J.A.; Stein, R.A.; Royle, J. Andrew; Marschall, E.A.

2008-01-01

The movement of fish from onstream impoundments into connected streams and rivers has traditionally been overlooked in fish stocking decisions but is critical to the ultimate impact of stocking riverine species into reservoirs. Hybrid saugeyes (female walleye Sander vitreus x male sauger S. canadensis) stocked into Deer Creek Reservoir, Ohio, readily move from the reservoir to the tailwater below. Downstream movement of these saugeyes from the tailwater may have consequences for native prey species and parental stocks downstream. We used fixed-station radiotelemetry to quantify the temporal movement patterns of 203 reservoir-stocked saugeyes from the tailwater of the reservoir, the stream flowing from the tailwater, and the river into which the stream flowed. From October 1998 through July 2000, most (75%) saugeyes never left the tailwater, and those that left returned 75% of the time. Overall, saugeyes spent 90% of their time in the tailwater, 7-8% of their time downstream in small streams, and 2-3% of their time farther downstream in the Scioto River (45 km downstream). No radio-tagged saugeyes moved to the Ohio River (155 km downstream). The probability of downstream movement generally increased with increasing flow and when dissolved oxygen dropped to lethal levels in summer. The probability of movement was highest in winter and spring, when it was probably related to spawning, and low in summer (except when dissolved oxygen was low) and fall. The patterns of movement seemed to reflect the relative suitability of tailwater over stream habitat. The predominant use of and return to tailwater habitat after downstream movement limited overall stream and river residence time. Although the daily movement probability for an individual was low, when we apply these rates to all of the stocked saugeyes in the Ohio River drainage, we cannot safely conclude that only small numbers move from reservoir tailwaters to downstream river systems. We recommend that managers refrain from stocking systems for which there are concerns about native species in connected drainages.

Crossover behavior of stock returns and mean square displacements of particles governed by the Langevin equation

NASA Astrophysics Data System (ADS)

Ma, Wen-Jong; Wang, Shih-Chieh; Chen, Chi-Ning; Hu, Chin-Kun

2013-06-01

It is found that the mean square log-returns calculated from the high-frequency one-day moving average of US and Taiwan stocks with the time internal τ show ballistic behavior \\theta \\tau^{\\alpha_1} with the exponent \\alpha_1 \\approx 2 for small τ and show diffusion-like behavior D \\tau^{\\alpha_2} with the exponent \\alpha_2 \\approx 1 for large τ. Such a crossover behavior can be well described by the mean square displacements of particles governed by the Langevin equation of motion. Thus, θ and D can be considered, respectively, as the temperature-like and diffusivity-like kinetic parameters of the market, and they can be used to characterize the behavior of the market.

Stock optimizing in choice when a token deposit is the operant.

PubMed

Widholm, J J; Silberberg, A; Hursh, S R; Imam, A A; Warren-Boulton, F R

2001-11-01

Each of 2 monkeys typically earned their daily food ration by depositing tokens in one of two slots. Tokens deposited in one slot dropped into a bin where they were kept (token kept). Deposits to a second slot dropped into a bin where they could be obtained again (token returned). In Experiment 1, a fixed-ratio (FR) 5 schedule that provided two food pellets was associated with each slot. Both monkeys preferred the token-returned slot. In Experiment 2, both subjects chose between unequal FR schedules with the token-returned slot always associated with the leaner schedule. When the FRs were 2 versus 3 and 2 versus 6, preferences were maintained for the token-returned slot; however, when the ratios were 2 versus 12, preference shifted to the token-kept slot. In Experiment 3, both monkeys chose between equal-valued concurrent variable-interval variable-interval schedules. Both monkeys preferred the slot that returned tokens. In Experiment 4, both monkeys chose between FRs that typically differed in size by a factor of 10. Both monkeys preferred the FR schedule that provided more food per trial. These data show that monkeys will choose so as to increase the number of reinforcers earned (stock optimizing) even when this preference reduces the rate of reinforcement (all reinforcers divided by session time).

Empirical Examination of Fundamental Indexation in the German Market

NASA Astrophysics Data System (ADS)

Mihm, Max; Locarek-Junge, Hermann

Index Funds, Exchange Traded Funds and Derivatives give investors easy access to well diversified index portfolios. These index-based investment products exhibit low fees, which make them an attractive alternative to actively managed funds. Against this background, a new class of stock indices has been established based on the concept of “Fundamental Indexation”. The selection and weighting of index constituents is conducted by means of fundamental criteria like total assets, book value or number of employees. This paper examines the performance of fundamental indices in the German equity market. For this purpose, a backtest of five fundamental indices is conducted over the last 20 years. Furthermore the index returns are analysed under the assumption of an efficient as well as an inefficient market. Index returns in efficient markets are explained by applying the three factor model for stock returns of Fama and French (J Financ Econ 33(1):3-56, 1993). The results show that the outperformance of fundamental indices is partly due to a higher risk exposure, particularly to companies with a low price to book ratio. By relaxing the assumption of market efficiency, a return drag of capitalisation weighted indices can be deduced. Given a mean-reverting movement of prices, a direct connection between market capitalisation and index weighting leads to inferior returns.

Population age structure and asset returns: an empirical investigation.

PubMed

Poterba, J M

1998-10-01

"This paper investigates the association between population age structure, particularly the share of the population in the 'prime saving years' 45-60, and the returns on stocks and bonds. The paper is motivated by the claim that the aging of the 'Baby Boom' cohort in the United States is a key factor in explaining the recent rise in asset values. It also addresses the associated claim that asset prices will decline when this large cohort reaches retirement age and begins to reduce its asset holdings. This paper begins by considering household age-asset accumulation profiles. Data from the Survey of Consumer Finances suggest that while cross-sectional age-wealth profiles peak for households in their early 60s, cohort data on the asset ownership of the same households show a much less pronounced peak.... The paper then considers the historical relationship between demographic structure and real returns on Treasury bills, long-term government bonds, and corporate stock. The results do not suggest any robust relationship between demographic structure and asset returns.... The paper concludes by discussing factors such as international capital flows and forward-looking behavior on the part of market participants that could weaken the relationship between age structure and asset returns in a single nation." excerpt

Modeling of Mean-VaR portfolio optimization by risk tolerance when the utility function is quadratic

NASA Astrophysics Data System (ADS)

Sukono, Sidi, Pramono; Bon, Abdul Talib bin; Supian, Sudradjat

2017-03-01

The problems of investing in financial assets are to choose a combination of weighting a portfolio can be maximized return expectations and minimizing the risk. This paper discusses the modeling of Mean-VaR portfolio optimization by risk tolerance, when square-shaped utility functions. It is assumed that the asset return has a certain distribution, and the risk of the portfolio is measured using the Value-at-Risk (VaR). So, the process of optimization of the portfolio is done based on the model of Mean-VaR portfolio optimization model for the Mean-VaR done using matrix algebra approach, and the Lagrange multiplier method, as well as Khun-Tucker. The results of the modeling portfolio optimization is in the form of a weighting vector equations depends on the vector mean return vector assets, identities, and matrix covariance between return of assets, as well as a factor in risk tolerance. As an illustration of numeric, analyzed five shares traded on the stock market in Indonesia. Based on analysis of five stocks return data gained the vector of weight composition and graphics of efficient surface of portfolio. Vector composition weighting weights and efficient surface charts can be used as a guide for investors in decisions to invest.

Measuring multifractality of stock price fluctuation using multifractal detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Yuan, Ying; Zhuang, Xin-tian; Jin, Xiu

2009-06-01

Analyzing the Shanghai stock price index daily returns using MF-DFA method, it is found that there are two different types of sources for multifractality in time series, namely, fat-tailed probability distributions and non-linear temporal correlations. Based on that, a sliding window of 240 frequency data in 5 trading days was used to study stock price index fluctuation. It is found that when the stock price index fluctuates sharply, a strong variability is clearly characterized by the generalized Hurst exponents h(q). Therefore, two measures, Δh and σ, based on generalized Hurst exponents were proposed to compare financial risks before and after Price Limits and Reform of Non-tradable Shares. The empirical results verify the validity of the measures, and this has led to a better understanding of complex stock markets.

What the 2008 stock market crash means for retirement security.

PubMed

Butrica, Barbara A; Smith, Karen E; Toder, Eric J

2010-10-01

The 2008 stock market crash raises concerns about retirement security, especially since the increased prevalence of 401(k) and similar retirement saving plans means that more Americans are now stakeholders in the equity market than in the past. Using a dynamic microsimulation model, this paper explores the ability of alternate future stock market scenarios to restore retirement assets. The authors find that those near retirement could fare the worst because they have no time to recoup their losses. Mid-career workers could fare better because they have more time to rebuild their wealth. They may even gain income if they buy stocks at low prices and get above-average rates of return. High-income groups will be the most affected because they are most likely to have financial assets and to be invested in the stock market.

High Quality Topic Extraction from Business News Explains Abnormal Financial Market Volatility

PubMed Central

Hisano, Ryohei; Sornette, Didier; Mizuno, Takayuki; Ohnishi, Takaaki; Watanabe, Tsutomu

2013-01-01

Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affects trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affects stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their “thematic” features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized facts in financial economies, namely that at certain times trading volumes appear to be “abnormally large,” can be partially explained by the flow of news. In this sense, our results prove that there is no “excess trading,” when restricting to times when news is genuinely novel and provides relevant financial information. PMID:23762258

Invariance in the recurrence of large returns and the validation of models of price dynamics

NASA Astrophysics Data System (ADS)

Chang, Lo-Bin; Geman, Stuart; Hsieh, Fushing; Hwang, Chii-Ruey

2013-08-01

Starting from a robust, nonparametric definition of large returns (“excursions”), we study the statistics of their occurrences, focusing on the recurrence process. The empirical waiting-time distribution between excursions is remarkably invariant to year, stock, and scale (return interval). This invariance is related to self-similarity of the marginal distributions of returns, but the excursion waiting-time distribution is a function of the entire return process and not just its univariate probabilities. Generalized autoregressive conditional heteroskedasticity (GARCH) models, market-time transformations based on volume or trades, and generalized (Lévy) random-walk models all fail to fit the statistical structure of excursions.

Analysis of stock investment selection based on CAPM using covariance and genetic algorithm approach

NASA Astrophysics Data System (ADS)

Sukono; Susanti, D.; Najmia, M.; Lesmana, E.; Napitupulu, H.; Supian, S.; Putra, A. S.

2018-03-01

Investment is one of the economic growth factors of countries, especially in Indonesia. Stocks is a form of investment, which is liquid. In determining the stock investment decisions which need to be considered by investors is to choose stocks that can generate maximum returns with a minimum risk level. Therefore, we need to know how to allocate the capital which may give the optimal benefit. This study discusses the issue of stock investment based on CAPM which is estimated using covariance and Genetic Algorithm approach. It is assumed that the stocks analyzed follow the CAPM model. To do the estimation of beta parameter on CAPM equation is done by two approach, first is to be represented by covariance approach, and second with genetic algorithm optimization. As a numerical illustration, in this paper analyzed ten stocks traded on the capital market in Indonesia. The results of the analysis show that estimation of beta parameters using covariance and genetic algorithm approach, give the same decision, that is, six underpriced stocks with buying decision, and four overpriced stocks with a sales decision. Based on the analysis, it can be concluded that the results can be used as a consideration for investors buying six under-priced stocks, and selling four overpriced stocks.

The asset pricing model of musharakah factors

NASA Astrophysics Data System (ADS)

Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md

2015-02-01

The existing three-factor model developed by Fama and French for conventional investment was formulated based on risk-free rates element in which contradict with Shariah principles. We note that the underlying principles that govern Shariah investment were mutual risk and profit sharing between parties, the assurance of fairness for all and that transactions were based on an underlying asset. In addition, the three-factor model did not exclude stock that was not permissible by Shariah such as financial services based on riba (interest), gambling operator, manufacture or sale of non-halal products or related products and other activities deemed non-permissible according to Shariah. Our approach to construct the factor model for Shariah investment was based on the basic tenets of musharakah in tabulating the factors. We start by noting that Islamic stocks with similar characteristics should have similar returns and risks. This similarity between Islamic stocks was defined by the similarity of musharakah attributes such as business, management, profitability and capital. These attributes define factor exposures (or betas) to factors. The main takeaways were that musharakah attributes we chose had explain stock returns well in cross section and were significant in different market environments. The management factor seemed to be responsible for the general dynamics of the explanatory power.

Finding hidden periodic signals in time series - an application to stock prices

NASA Astrophysics Data System (ADS)

O'Shea, Michael

2014-03-01

Data in the form of time series appear in many areas of science. In cases where the periodicity is apparent and the only other contribution to the time series is stochastic in origin, the data can be `folded' to improve signal to noise and this has been done for light curves of variable stars with the folding resulting in a cleaner light curve signal. Stock index prices versus time are classic examples of time series. Repeating patterns have been claimed by many workers and include unusually large returns on small-cap stocks during the month of January, and small returns on the Dow Jones Industrial average (DJIA) in the months June through September compared to the rest of the year. Such observations imply that these prices have a periodic component. We investigate this for the DJIA. If such a component exists it is hidden in a large non-periodic variation and a large stochastic variation. We show how to extract this periodic component and for the first time reveal its yearly (averaged) shape. This periodic component leads directly to the `Sell in May and buy at Halloween' adage. We also drill down and show that this yearly variation emerges from approximately half of the underlying stocks making up the DJIA index.

Extreme value modelling of Ghana stock exchange index.

PubMed

Nortey, Ezekiel N N; Asare, Kwabena; Mettle, Felix Okoe

2015-01-01

Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana stock exchange all-shares index (2000-2010) by applying the extreme value theory (EVT) to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before the EVT method was applied. The Peak Over Threshold approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model's goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the value at risk and expected shortfall risk measures at some high quantiles, based on the fitted GPD model.

38 CFR 12.0 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... embraces all other property of every description, including insurance policies, certificates of stock... which have never been negotiated will be returned to the issuing office for disposition. (b) Field...

Random Matrix Theory Approach to Indonesia Energy Portfolio Analysis

NASA Astrophysics Data System (ADS)

Mahardhika, Alifian; Purqon, Acep

2017-07-01

In a few years, Indonesia experienced difficulties in maintaining energy security, the problem is the decline in oil production from 1.6 million barrels per day to 861 thousand barrels per day in 2012. However, there is a difference condition in 2015 until the third week in 2016, world oil prices actually fell at the lowest price level since last 12 years. The decline in oil prices due to oversupply of oil by oil-producing countries of the world due to the instability of the world economy. Wave of layoffs in Indonesia is a response to the decline in oil prices, this led to the energy and mines portfolios Indonesia feared would not be more advantageous than the portfolio in other countries. In this research, portfolio analysis will be done on energy and mining in Indonesia by using stock price data of energy and mines in the period 26 November 2010 until April 1, 2016. It was found that the results have a wide effect of the market potential is high in the determination of the return on the portfolio energy and mines. Later, it was found that there are eight of the thirty stocks in the energy and mining portfolio of Indonesia which have a high probability of return relative to the average return of stocks in a portfolio of energy and mines.

A new look at red pine financial returns in the Lake States.

Treesearch

David C. Lothner; Dennis P. Bradley

1984-01-01

Describes the financial performance of red pine on site index 60, 70, and 80 lands by using new yield evidence and up-to-date cost and revenue assumptions. Best combinations of initial stocking, residual basal area after thinning, an rotation age are identified for two different financial criteria: soil expectation value and internal rate of return.

26 CFR 301.6104(a)-2 - Public inspection of material relating to pension and other plans.

Code of Federal Regulations, 2010 CFR

2010-04-01

... pension and other plans. 301.6104(a)-2 Section 301.6104(a)-2 Internal Revenue INTERNAL REVENUE SERVICE... and Returns Returns and Records § 301.6104(a)-2 Public inspection of material relating to pension and...— (i) A pension, profit-sharing, or stock bonus plan under section 401(a), (ii) An annuity plan under...

Economics of thinning stagnated ponderosa pine sapling stands in the pine-grass areas of central Washington.

Treesearch

Robert W. Sassaman; James W. Barrett; Justin G. Smith

1972-01-01

Present net worth values earned by investments in precommercial thinning of stagnated ponderosa pine sapling stands are reported for three stocking levels. Thirteen timber management regimes are ranked by their returns from timber only, and 22 regimes are ranked according to their returns from timber and forage, with and without the allowable cut effect.

Health inputs and cumulative health deficits among the older Chinese.

PubMed

Gu, Danan; Sautter, Jessica; Huang, Cheng; Zeng, Yi

2011-03-01

Using a health economics framework, we examined how both individual level investments at different life stages and current community-level environmental factors affect individual health stock and flows at old ages. We used a nationwide dataset from the 2002 and 2005 waves of the Chinese Longitudinal Healthy Longevity Survey, which included more than 15,000 adults aged 65 and older from 22 provinces in mainland China. We measured health stock with a cumulative health deficit index, a measure developed in geriatrics and gerontology that reflects deficits, illnesses, and functional impairment in numerous domains of health. The cumulative health deficit index has not been used in health economics before, but is a significant contribution because it captures the health stock concept very well and overcomes the problems of inconsistency resulting from the use of different measures of health stock in research. Our results show that several proxy measures for individual health investments in both childhood (nutritional status and parental survival status) and adulthood (family financial condition and access to healthcare) yielded positive returns to health stock measured by the cumulative health deficit index. Investments in social connections and healthy behaviors (religious involvement, alcohol use, and exercise) also produced positive returns in health stock. Current community-level factors such as air quality and labor force participation rate were significantly associated with levels of health deficits in old age as well. Yet, most of these individual investment and community environment variables did not significantly affect short-term health flows (improvement or deterioration in health status over three years). Our findings have important implications for developing preventive health programs in the context of population aging by focusing on policy-relevant predictors and a comprehensive indicator of health status in later life. Copyright © 2011 Elsevier Ltd. All rights reserved.

Estimating the Value-at-Risk for some stocks at the capital market in Indonesia based on ARMA-FIGARCH models

NASA Astrophysics Data System (ADS)

Sukono; Lesmana, E.; Susanti, D.; Napitupulu, H.; Hidayat, Y.

2017-11-01

Value-at-Risk has already become a standard measurement that must be carried out by the financial institution for both internal interest and regulatory. In this paper, the estimation of Value-at-Risk of some stocks with econometric models approach is analyzed. In this research, we assume that the stock return follows the time series model. To do the estimation of mean value we are using ARMA models, while to estimate the variance value we are using FIGARCH models. Furthermore, the mean value estimator and the variance are used to estimate the Value-at-Risk. The result of the analysis shows that from five stock PRUF, BBRI, MPPA, BMRI, and INDF, the Value-at-Risk obtained are 0.01791, 0.06037, 0.02550, 0.06030, and 0.02585 respectively. Since Value-at-Risk represents the maximum risk size of each stock at a 95% level of significance, then it can be taken into consideration in determining the investment policy on stocks.

Wavelet transform approach for fitting financial time series data

NASA Astrophysics Data System (ADS)

Ahmed, Amel Abdoullah; Ismail, Mohd Tahir

2015-10-01

This study investigates a newly developed technique; a combined wavelet filtering and VEC model, to study the dynamic relationship among financial time series. Wavelet filter has been used to annihilate noise data in daily data set of NASDAQ stock market of US, and three stock markets of Middle East and North Africa (MENA) region, namely, Egypt, Jordan, and Istanbul. The data covered is from 6/29/2001 to 5/5/2009. After that, the returns of generated series by wavelet filter and original series are analyzed by cointegration test and VEC model. The results show that the cointegration test affirms the existence of cointegration between the studied series, and there is a long-term relationship between the US, stock markets and MENA stock markets. A comparison between the proposed model and traditional model demonstrates that, the proposed model (DWT with VEC model) outperforms traditional model (VEC model) to fit the financial stock markets series well, and shows real information about these relationships among the stock markets.

Obesity, Gynecological Factors, and Abnormal Mammography Follow-Up in Minority and Medically Underserved Women

PubMed Central

Wujcik, Debra; Lin, Jin-Mann S.; Grau, Ana; Wilson, Veronica; Champion, Victoria; Zheng, Wei; Egan, Kathleen M.

2009-01-01

Abstract Background The relationship between obesity and screening mammography adherence has been examined previously, yet few studies have investigated obesity as a potential mediator of timely follow-up of abnormal (Breast Imaging Reporting and Data System [BIRADS-0]) mammography results in minority and medically underserved patients. Methods We conducted a retrospective cohort study of 35 women who did not return for follow-up >6 months from index abnormal mammography and 41 who returned for follow-up ≤6 months in Nashville, Tennessee. Patients with a BIRADS-0 mammography event in 2003–2004 were identified by chart review. Breast cancer risk factors were collected by telephone interview. Multivariate logistic regression was performed on selected factors with return for diagnostic follow-up. Results Obesity and gynecological history were significant predictors of abnormal mammography resolution. A significantly higher frequency of obese women delayed return for mammography resolution compared with nonobese women (64.7% vs. 35.3%). A greater number of hysterectomized women returned for diagnostic follow-up compared with their counterparts without a hysterectomy (77.8% vs. 22.2%). Obese patients were more likely to delay follow-up >6 months (adjusted OR 4.09, p = 0.02). Conversely, hysterectomized women were significantly more likely to return for timely mammography follow-up ≤6 months (adjusted OR 7.95, p = 0.007). Conclusions Study results suggest that weight status and gynecological history influence patients' decisions to participate in mammography follow-up studies. Strategies are necessary to reduce weight-related barriers to mammography follow-up in the healthcare system including provider training related to mammography screening of obese women. PMID:19558307

Volatility measurement with directional change in Chinese stock market: Statistical property and investment strategy

NASA Astrophysics Data System (ADS)

Ma, Junjun; Xiong, Xiong; He, Feng; Zhang, Wei

2017-04-01

The stock price fluctuation is studied in this paper with intrinsic time perspective. The event, directional change (DC) or overshoot, are considered as time scale of price time series. With this directional change law, its corresponding statistical properties and parameter estimation is tested in Chinese stock market. Furthermore, a directional change trading strategy is proposed for invest in the market portfolio in Chinese stock market, and both in-sample and out-of-sample performance are compared among the different method of model parameter estimation. We conclude that DC method can capture important fluctuations in Chinese stock market and gain profit due to the statistical property that average upturn overshoot size is bigger than average downturn directional change size. The optimal parameter of DC method is not fixed and we obtained 1.8% annual excess return with this DC-based trading strategy.

Network formation in a multi-asset artificial stock market

NASA Astrophysics Data System (ADS)

Wu, Songtao; He, Jianmin; Li, Shouwei; Wang, Chao

2018-04-01

A multi-asset artificial stock market is developed. In the market, stocks are assigned to a number of sectors and traded by heterogeneous investors. The mechanism of continuous double auction is employed to clear order book and form daily closed prices. Simulation results of prices at the sector level show an intra-sector similarity and inter-sector distinctiveness, and returns of individual stocks have stylized facts that are ubiquitous in the real-world stock market. We find that the market risk factor has critical impact on both network topology transition and connection formation, and that sector risk factors account for the formation of intra-sector links and sector-based local interaction. In addition, the number of community in threshold-based networks is correlated negatively and positively with the value of correlation coefficients and the ratio of intra-sector links, which are respectively determined by intensity of sector risk factors and the number of sectors.

The Dow is Killing Me: Risky Health Behaviors and the Stock Market.

PubMed

Cotti, Chad; Dunn, Richard A; Tefft, Nathan

2015-07-01

We investigate how risky health behaviors and self-reported health vary with the Dow Jones Industrial Average (DJIA) and during stock market crashes. Because stock market indices are leading indicators of economic performance, this research contributes to our understanding of the macroeconomic determinants of health. Existing studies typically rely on the unemployment rate to proxy for economic performance, but this measure captures only one of many channels through which the economic environment may influence individual health decisions. We find that large, negative monthly DJIA returns, decreases in the level of the DJIA, and stock market crashes are widely associated with worsening self-reported mental health and more cigarette smoking, binge drinking, and fatal car accidents involving alcohol. These results are consistent with predictions from rational addiction models and have implications for research on the association between consumption and stock prices. Copyright © 2014 John Wiley & Sons, Ltd.

Liquidity Dynamics in the Xetra Order Book

NASA Astrophysics Data System (ADS)

Schmidinger, Christoph

2010-09-01

In this paper we show how to reconstruct the limit order book of the 30 stocks constituting the DAX30 index based on the trading protocol of the Xetra Trading System at the Frankfurt Stock Exchange. The algorithm used is innovative as it captures all trading phases, including auctions, and delivers a reconstruction of the orderbook either from a trader's view or a supervisory view including hidden volume as well. Based on the rebuilt order book, liquidity dynamics are examined. In contrats to findings for dealer markets, past market returns play a minor role in the determination of liquidity and liquidity commonality in Xetra, a pure limit order book market. Consequently, we provide evidence that liquidity provision by multiple sources in Xetra mitigates systemic liquidity risk introduced by the interrelation of return and liquidity.

Statistical analysis on multifractal detrended cross-correlation coefficient for return interval by oriented percolation

NASA Astrophysics Data System (ADS)

Deng, Wei; Wang, Jun

2015-06-01

We investigate and quantify the multifractal detrended cross-correlation of return interval series for Chinese stock markets and a proposed price model, the price model is established by oriented percolation. The return interval describes the waiting time between two successive price volatilities which are above some threshold, the present work is an attempt to quantify the level of multifractal detrended cross-correlation for the return intervals. Further, the concept of MF-DCCA coefficient of return intervals is introduced, and the corresponding empirical research is performed. The empirical results show that the return intervals of SSE and SZSE are weakly positive multifractal power-law cross-correlated, and exhibit the fluctuation patterns of MF-DCCA coefficients. The similar behaviors of return intervals for the price model is also demonstrated.

Atlantic salmon brood stock management and breeding handbook

USGS Publications Warehouse

Kincaid, Harold L.; Stanley, Jon G.

1989-01-01

Anadromus runs of Atlantic salmon have been restored to the Connecticut, Merrimack, Pawcatuck, Penobscot, and St. Croix rivers in New England by the stocking of more than 8 million smolts since 1948. Fish-breeding methods have been developed that minimize inbreeding and domestication and enhance natural selection. Methods are available to advance the maturation of brood stock, control the sex of production lots and store gametes. Current hatchery practices emphasize the use of sea-run brood stock trapped upon return to the rivers and a limited number of captive brood stock and rejuvenated kelts. Fish are allowed to mature naturally, after which they are spawned and incubated artificially. Generally, 1-year smolts are produced, and excess fish are stocked as fry in headwater streams. Smolts are stocked during periods of rising water in spring. Self-release pools are planned that enable smolts to choose the emigration time. Culturists keep good records that permit evaluation of the performance of strains and the effects of breeding practices. As Atlantic salmon populations expand, culturists must use sound breeding methods that enhance biotic potential while maintaining genetic diversity and protecting unique gene pools.

Not all that glitters is RMT in the forecasting of risk of portfolios in the Brazilian stock market

NASA Astrophysics Data System (ADS)

Sandoval, Leonidas; Bortoluzzo, Adriana Bruscato; Venezuela, Maria Kelly

2014-09-01

Using stocks of the Brazilian stock exchange (BM&F-Bovespa), we build portfolios of stocks based on Markowitz's theory and test the predicted and realized risks. This is done using the correlation matrices between stocks, and also using Random Matrix Theory in order to clean such correlation matrices from noise. We also calculate correlation matrices using a regression model in order to remove the effect of common market movements and their cleaned versions using Random Matrix Theory. This is done for years of both low and high volatility of the Brazilian stock market, from 2004 to 2012. The results show that the use of regression to subtract the market effect on returns greatly increases the accuracy of the prediction of risk, and that, although the cleaning of the correlation matrix often leads to portfolios that better predict risks, in periods of high volatility of the market this procedure may fail to do so. The results may be used in the assessment of the true risks when one builds a portfolio of stocks during periods of crisis.

Interannual Variability of Fisheries Economic Returns and Energy Ratios Is Mostly Explained by Gear Type

PubMed Central

Trenkel, Verena M.; Daurès, Fabienne; Rochet, Marie-Joëlle; Lorance, Pascal

2013-01-01

According to portfolio theory applied to fisheries management, economic returns are stabilised by harvesting in a portfolio stocks of species whose returns are negatively correlated and for which the portfolio economic return variance is smaller than the sum of stock specific return variances. Also, variability is expected to decrease with portfolio width. Using a range of indicators, these predictions were tested for the French fishing fleets in the Bay of Biscay (Northeast Atlantic) during the period 2001–2009. For this, vessels were grouped into eight fishing fleets based on the gears used and exploited species were grouped into five functional groups. The portfolio width of fleets ranged from 1–3 functional groups, or 4–19 species. Economic fleet returns (sale revenues minus fishing costs) varied strongly between years; the interannual variability was independent of portfolio width (species or functional groups). Energy ratio expressed by the ratio between fuel energy used for fishing and energy contained in landings varied from 0.3 for purse seines to 9.7 for trawlers using bottom trawls alone or in combination with pelagic trawls independent of portfolio width. Interannual variability in total sale revenues was larger than the sum of species specific sales revenue variability, except for fleets using hooks and pelagic trawlers; it increased with the number of species exploited. In conclusion, the interannual variability of economic returns or energy ratios of French fisheries in the Bay of Biscay did not decrease with the number of species or functional groups exploited, though it varied between fleets. PMID:23922951

Indication of multiscaling in the volatility return intervals of stock markets

NASA Astrophysics Data System (ADS)

Wang, Fengzhong; Yamasaki, Kazuko; Havlin, Shlomo; Stanley, H. Eugene

2008-01-01

The distribution of the return intervals τ between price volatilities above a threshold height q for financial records has been approximated by a scaling behavior. To explore how accurate is the scaling and therefore understand the underlined nonlinear mechanism, we investigate intraday data sets of 500 stocks which consist of Standard & Poor’s 500 index. We show that the cumulative distribution of return intervals has systematic deviations from scaling. We support this finding by studying the m -th moment μm≡⟨(τ/⟨τ⟩)m⟩1/m , which show a certain trend with the mean interval ⟨τ⟩ . We generate surrogate records using the Schreiber method, and find that their cumulative distributions almost collapse to a single curve and moments are almost constant for most ranges of ⟨τ⟩ . Those substantial differences suggest that nonlinear correlations in the original volatility sequence account for the deviations from a single scaling law. We also find that the original and surrogate records exhibit slight tendencies for short and long ⟨τ⟩ , due to the discreteness and finite size effects of the records, respectively. To avoid as possible those effects for testing the multiscaling behavior, we investigate the moments in the range 10<⟨τ⟩≤100 , and find that the exponent α from the power law fitting μm˜⟨τ⟩α has a narrow distribution around α≠0 which depends on m for the 500 stocks. The distribution of α for the surrogate records are very narrow and centered around α=0 . This suggests that the return interval distribution exhibits multiscaling behavior due to the nonlinear correlations in the original volatility.

Impact of uncertainty in expected return estimation on stock price volatility

NASA Astrophysics Data System (ADS)

Kostanjcar, Zvonko; Jeren, Branko; Juretic, Zeljan

2012-11-01

We investigate the origin of volatility in financial markets by defining an analytical model for time evolution of stock share prices. The defined model is similar to the GARCH class of models, but can additionally exhibit bimodal behaviour in the supply-demand structure of the market. Moreover, it differs from existing Ising-type models. It turns out that the constructed model is a solution of a thermodynamic limit of a Gibbs probability measure when the number of traders and the number of stock shares approaches infinity. The energy functional of the Gibbs probability measure is derived from the Nash equilibrium of the underlying game.

Localized motion in random matrix decomposition of complex financial systems

NASA Astrophysics Data System (ADS)

Jiang, Xiong-Fei; Zheng, Bo; Ren, Fei; Qiu, Tian

2017-04-01

With the random matrix theory, we decompose the multi-dimensional time series of complex financial systems into a set of orthogonal eigenmode functions, which are classified into the market mode, sector mode, and random mode. In particular, the localized motion generated by the business sectors, plays an important role in financial systems. Both the business sectors and their impact on the stock market are identified from the localized motion. We clarify that the localized motion induces different characteristics of the time correlations for the stock-market index and individual stocks. With a variation of a two-factor model, we reproduce the return-volatility correlations of the eigenmodes.

Cross-sectional fluctuation scaling in the high-frequency illiquidity of Chinese stocks

NASA Astrophysics Data System (ADS)

Cai, Qing; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene

2018-03-01

Taylor's law of temporal and ensemble fluctuation scaling has been ubiquitously observed in diverse complex systems including financial markets. Stock illiquidity is an important nonadditive financial quantity, which is found to comply with Taylor's temporal fluctuation scaling law. In this paper, we perform the cross-sectional analysis of the 1 min high-frequency illiquidity time series of Chinese stocks and unveil the presence of Taylor's law of ensemble fluctuation scaling. The estimated daily Taylor scaling exponent fluctuates around 1.442. We find that Taylor's scaling exponents of stock illiquidity do not relate to the ensemble mean and ensemble variety of returns. Our analysis uncovers a new scaling law of financial markets and might stimulate further investigations for a better understanding of financial markets' dynamics.

Universal portfolios generated by weakly stationary processes

NASA Astrophysics Data System (ADS)

Tan, Choon Peng; Pang, Sook Theng

2014-12-01

Recently, a universal portfolio generated by a set of independent Brownian motions where a finite number of past stock prices are weighted by the moments of the multivariate normal distribution is introduced and studied. The multivariate normal moments as polynomials in time consequently lead to a constant rebalanced portfolio depending on the drift coefficients of the Brownian motions. For a weakly stationary process, a different type of universal portfolio is proposed where the weights on the stock prices depend only on the time differences of the stock prices. An empirical study is conducted on the returns achieved by the universal portfolios generated by the Ornstein-Uhlenbeck process on selected stock-price data sets. Promising results are demonstrated for increasing the wealth of the investor by using the weakly-stationary-process-generated universal portfolios.

Geographical distributions of lake trout strains stocked in Lake Ontario

USGS Publications Warehouse

Elrod, Joseph H.; O'Gorman, Robert; Schneider, Clifford P.; Schaner, Ted

1996-01-01

Geographical distributions of lake trout (Salvelinus namaycush) stocked at seven locations in U.S. waters and at four locations in Canadian waters of Lake Ontario were determined from fish caught with gill nets in September in 17 areas of U.S. waters and at 10 fixed locations in Canadian waters in 1986-95. For fish of a given strain stocked at a given location, geographical distributions were not different for immature males and immature females or for mature males and mature females. The proportion of total catch at the three locations nearest the stocking location was higher for mature fish than for immature fish in all 24 available comparisons (sexes combined) and was greater for fish stocked as yearlings than for those stocked as fingerlings in all eight comparisons. Mature fish were relatively widely dispersed from stocking locations indicating that their tendency to return to stocking locations for spawning was weak, and there was no appreciable difference in this tendency among strains. Mature lake trout were uniformly distributed among sampling locations, and the strain composition at stocking locations generally reflected the stocking history 5 to 6 years earlier. Few lake trout moved across Lake Ontario between the north and south shores or between the eastern outlet basin and the main lake basin. Limited dispersal from stocking sites supports the concept of stocking different genetic strains in various parts of the lake with the attributes of each strain selected to match environmental conditions in the portion of the lake where it is stocked.

Developing trading strategies based on fractal finance: An application of MF-DFA in the context of Islamic equities

NASA Astrophysics Data System (ADS)

Dewandaru, Ginanjar; Masih, Rumi; Bacha, Obiyathulla Ismath; Masih, A. Mansur. M.

2015-11-01

We provide a new contribution to trading strategies by using multi-fractal de-trended fluctuation analysis (MF-DFA), imported from econophysics, to complement various momentum strategies. The method provides a single measure that can capture both persistency and anti-persistency in stock prices, accounting for multifractality. This study uses a sample of Islamic stocks listed in the U.S. Dow Jones Islamic market for a sample period covering 16 years starting in 1996. The findings show that the MF-DFA strategy produces monthly excess returns of 6.12%, outperforming other various momentum strategies. Even though the risk of the MF-DFA strategy may be relatively higher, it can still produce a Sharpe ratio of 0.164, which is substantially higher than that of the other strategies. When we control for the MF-DFA factor with the other factors, its pure factor return is still able to yield a monthly excess return of 1.35%. Finally, we combine the momentum and MF-DFA strategies, with the proportions of 90/10, 80/20, and 70/30 and by doing so we demonstrate that the MF-DFA measure can boost the total monthly excess returns as well as Sharpe ratio. The value added is non-linear which implies that the additional returns are associated with lower incremental risk.

The predictive power of Japanese candlestick charting in Chinese stock market

NASA Astrophysics Data System (ADS)

Chen, Shi; Bao, Si; Zhou, Yu

2016-09-01

This paper studies the predictive power of 4 popular pairs of two-day bullish and bearish Japanese candlestick patterns in Chinese stock market. Based on Morris' study, we give the quantitative details of definition of long candlestick, which is important in two-day candlestick pattern recognition but ignored by several previous researches, and we further give the quantitative definitions of these four pairs of two-day candlestick patterns. To test the predictive power of candlestick patterns on short-term price movement, we propose the definition of daily average return to alleviate the impact of correlation among stocks' overlap-time returns in statistical tests. To show the robustness of our result, two methods of trend definition are used for both the medium-market-value and large-market-value sample sets. We use Step-SPA test to correct for data snooping bias. Statistical results show that the predictive power differs from pattern to pattern, three of the eight patterns provide both short-term and relatively long-term prediction, another one pair only provide significant forecasting power within very short-term period, while the rest three patterns present contradictory results for different market value groups. For all the four pairs, the predictive power drops as predicting time increases, and forecasting power is stronger for stocks with medium market value than those with large market value.

The effects of common risk factors on stock returns: A detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market.

PubMed

Kenett, Dror Y; Tumminello, Michele; Madi, Asaf; Gur-Gershgoren, Gitit; Mantegna, Rosario N; Ben-Jacob, Eshel

2010-12-20

What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001-2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market.

Volatility return intervals analysis of the Japanese market

NASA Astrophysics Data System (ADS)

Jung, W.-S.; Wang, F. Z.; Havlin, S.; Kaizoji, T.; Moon, H.-T.; Stanley, H. E.

2008-03-01

We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold q for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the return interval τ and its mean <τ>. We also find memory effects such that a large (or small) return interval follows a large (or small) interval by investigating the conditional distribution and mean return interval. The results are similar to previous studies of other markets and indicate that similar statistical features appear in different financial markets. We also compare our results between the period before and after the big crash at the end of 1989. We find that scaling and memory effects of the return intervals show similar features although the statistical properties of the returns are different.

27 CFR 46.241 - Required records.

Code of Federal Regulations, 2010 CFR

2010-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette... all controlled group members, if applicable; (d) A copy of the tax return, if the dealer filed one; (e...

27 CFR 46.241 - Required records.

Code of Federal Regulations, 2014 CFR

2014-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette... all controlled group members, if applicable; (d) A copy of the tax return, if the dealer filed one; (e...

27 CFR 46.241 - Required records.

Code of Federal Regulations, 2011 CFR

2011-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette... all controlled group members, if applicable; (d) A copy of the tax return, if the dealer filed one; (e...

27 CFR 46.241 - Required records.

Code of Federal Regulations, 2013 CFR

2013-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette... all controlled group members, if applicable; (d) A copy of the tax return, if the dealer filed one; (e...

27 CFR 46.241 - Required records.

Code of Federal Regulations, 2012 CFR

2012-04-01

... CIGARETTE PAPERS AND TUBES Floor Stocks Tax on Certain Tobacco Products, Cigarette Papers, and Cigarette... all controlled group members, if applicable; (d) A copy of the tax return, if the dealer filed one; (e...

Elements of decisional dynamics: An agent-based approach applied to artificial financial market

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Elements of decisional dynamics: An agent-based approach applied to artificial financial market.

PubMed

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2018-02-01

This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book. Finally, while putting most parameters under evolutionary control, the computational agent-based system is able to replicate several stylized facts of financial time series (distributions of stock returns showing a heavy tail with positive excess kurtosis, absence of autocorrelations in stock returns, and volatility clustering phenomenon).

Financial effects of pharmaceutical price regulation on R&D spending by EU versus US firms.

PubMed

Golec, Joseph; Vernon, John A

2010-01-01

EU countries closely regulate pharmaceutical prices, whereas the US does not. This paper shows how price constraints affect the profitability, stock returns and R&D spending of EU and US firms. Compared with EU firms, US firms are more profitable, earn higher stock returns and spend more on R&D. We tested the relationship between price regulation and R&D spending, and estimated the costs of tight EU price regulation. Although results show that EU consumers enjoyed much lower pharmaceutical price inflation, we estimated that price controls cost EU firms 46 fewer new medicines and 1680 fewer research jobs during our 19-year sample period. Had the US used controls similar to those used in the EU, we estimate it would have led to 117 fewer new medicines and 4368 fewer research jobs in the US.

Network analysis of returns and volume trading in stock markets: The Euro Stoxx case

NASA Astrophysics Data System (ADS)

Brida, Juan Gabriel; Matesanz, David; Seijas, Maria Nela

2016-02-01

This study applies network analysis to analyze the structure of the Euro Stoxx market during the long period from 2002 up to 2014. The paper generalizes previous research on stock market networks by including asset returns and volume trading as the main variables to study the financial market. A multidimensional generalization of the minimal spanning tree (MST) concept is introduced, by adding the role of trading volume to the traditional approach which only includes price returns. Additionally, we use symbolization methods to the raw data to study the behavior of the market structure in different, normal and critical, situations. The hierarchical organization of the network is derived, and the MST for different sub-periods of 2002-2014 is created to illustrate how the structure of the market evolves over time. From the structural topologies of these trees, different clusters of companies are identified and analyzed according to their geographical and economic links. Two important results are achieved. Firstly, as other studies have highlighted, at the time of the financial crisis after 2008 the network becomes a more centralized one. Secondly and most important, during our second period of analysis, 2008-2014, we observe that hierarchy becomes more country-specific where different sub-clusters of stocks belonging to France, Germany, Spain or Italy are found apart from their business sector group. This result may suggest that during this period of time financial investors seem to be worried most about country specific economic circumstances.

An agent-based approach to financial stylized facts

NASA Astrophysics Data System (ADS)

Shimokawa, Tetsuya; Suzuki, Kyoko; Misawa, Tadanobu

2007-06-01

An important challenge of the financial theory in recent years is to construct more sophisticated models which have consistencies with as many financial stylized facts that cannot be explained by traditional models. Recently, psychological studies on decision making under uncertainty which originate in Kahneman and Tversky's research attract a lot of interest as key factors which figure out the financial stylized facts. These psychological results have been applied to the theory of investor's decision making and financial equilibrium modeling. This paper, following these behavioral financial studies, would like to propose an agent-based equilibrium model with prospect theoretical features of investors. Our goal is to point out a possibility that loss-averse feature of investors explains vast number of financial stylized facts and plays a crucial role in price formations of financial markets. Price process which is endogenously generated through our model has consistencies with, not only the equity premium puzzle and the volatility puzzle, but great kurtosis, asymmetry of return distribution, auto-correlation of return volatility, cross-correlation between return volatility and trading volume. Moreover, by using agent-based simulations, the paper also provides a rigorous explanation from the viewpoint of a lack of market liquidity to the size effect, which means that small-sized stocks enjoy excess returns compared to large-sized stocks.

Canonical Sectors and Evolution of Firms in the US Stock Markets

NASA Astrophysics Data System (ADS)

Hayden, Lorien; Chachra, Ricky; Alemi, Alexander; Ginsparg, Paul; Sethna, James

2015-03-01

In this work, we show how unsupervised machine learning can provide a more objective and comprehensive broad-level sector decomposition of stocks. Classification of companies into sectors of the economy is important for macroeconomic analysis, and for investments into the sector-specific financial indices and exchange traded funds (ETFs). Historically, these major industrial classification systems and financial indices have been based on expert opinion and developed manually. Our method, in contrast, produces an emergent low-dimensional structure in the space of historical stock price returns. This emergent structure automatically identifies ``canonical sectors'' in the market, and assigns every stock a participation weight into these sectors. Furthermore, by analyzing data from different periods, we show how these weights for listed firms have evolved over time. This work was partially supported by NSF Grants DMR 1312160, OCI 0926550 and DGE-1144153 (LXH).

Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system

NASA Astrophysics Data System (ADS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-10-01

Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

A semiparametric graphical modelling approach for large-scale equity selection.

PubMed

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.

STOCK Market Differences in Correlation-Based Weighted Network

NASA Astrophysics Data System (ADS)

Youn, Janghyuk; Lee, Junghoon; Chang, Woojin

We examined the sector dynamics of Korean stock market in relation to the market volatility. The daily price data of 360 stocks for 5019 trading days (from January, 1990 to August, 2008) in Korean stock market are used. We performed the weighted network analysis and employed four measures: the average, the variance, the intensity, and the coherence of network weights (absolute values of stock return correlations) to investigate the network structure of Korean stock market. We performed regression analysis using the four measures in the seven major industry sectors and the market (seven sectors combined). We found that the average, the intensity, and the coherence of sector (subnetwork) weights increase as market becomes volatile. Except for the "Financials" sector, the variance of sector weights also grows as market volatility increases. Based on the four measures, we can categorize "Financials," "Information Technology" and "Industrials" sectors into one group, and "Materials" and "Consumer Discretionary" sectors into another group. We investigated the distributions of intrasector and intersector weights for each sector and found the differences in "Financials" sector are most distinct.

Who wins? Study of long-run trader survival in an artificial stock market

NASA Astrophysics Data System (ADS)

Cincotti, Silvano; M. Focardi, Sergio; Marchesi, Michele; Raberto, Marco

2003-06-01

We introduce a multi-asset artificial financial market with finite amount of cash and number of stocks. The background trading is characterized by a random trading strategy constrained by the finiteness of resources and by market volatility. Stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Three active trading strategies have been introduced and studied in two different market conditions: steady market and growing market with asset inflation. We show that the profitability of each strategy depends both on the periodicity of portfolio reallocation and on the market condition. The best performing strategy is the one that exploits the mean reversion characteristic of asset price processes.

Graphic warning labels and the demand for cigarettes.

PubMed

Starr, Martha A; Drake, Keith

2017-03-01

In 2010, the US Food and Drug Administration (FDA) proposed requiring tobacco companies to add graphic warning labels (GWLs) to cigarette packs. GWLs are large prominently placed warnings that use both text and photographic images to depict health risks of smoking. The companies challenged FDA's authority on First Amendment grounds; the courts accepted that FDA could compel companies to add GWLs, but argued that FDA had not established that GWLs would significantly reduce smoking. This paper adds new evidence on the question of whether GWLs would have reduced cigarette demand, by examining whether tobacco companies' share prices fell unusually after news indicating a higher likelihood of having GWLs, and rose on the opposite news. Such findings would be expected if investors viewed GWLs as likely to reduce cigarette demand. An event-study approach is used to determine whether the stock prices of US tobacco companies rose or fell unusually after news events in the period when GWLs were proposed, finalised, challenged and withdrawn. Tobacco companies' stock prices indeed realised significant abnormal returns after GWL news, consistent with expected negative effects on cigarette demand. Our estimates suggest investors expected GWLs to reduce the number of smokers by an extra 2.4-6.9 million in the 10 years after the rule took effect. These findings support the view that the GWLs proposed by FDA would have curbed cigarette consumption in the USA in an appreciable way. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Emergence and temporal structure of Lead-Lag correlations in collective stock dynamics

NASA Astrophysics Data System (ADS)

Xia, Lisi; You, Daming; Jiang, Xin; Chen, Wei

2018-07-01

Understanding the correlations among stock returns is crucial for reducing the risk of investment in stock markets. As an important stylized correlation, lead-lag effect plays a major role in analyzing market volatility and deriving trading strategies. Here, we explore historical lead-lag relationships among stocks in the Chinese stock market. Strongly positive lagged correlations can be empirically observed. We demonstrate this lead-lag phenomenon is not constant but temporally emerges during certain periods. By introducing moving time window method, we transform the lead-lag dynamics into a series of asymmetric lagged correlation matrices. Dynamic lead-lag structures are uncovered in the form of temporal network structures. We find that the size of lead-lag group experienced a rapid drop during the year 2012, which signaled a re-balance of the stock market. On the daily timescale, we find the lead-lag structure exhibits several persistent patterns, which can be characterized by the Jaccard matrix. We show significant market events can be distinguished in the Jaccard matrix diagram. Taken together, we study an integration of all the temporal networks and identify several leading stock sectors, which are in accordance with the common Chinese economic fundamentals.

Correlation and volatility in an Indian stock market: A random matrix approach

NASA Astrophysics Data System (ADS)

Kulkarni, Varsha; Deo, Nivedita

2007-11-01

We examine the volatility of an Indian stock market in terms of correlation of stocks and quantify the volatility using the random matrix approach. First we discuss trends observed in the pattern of stock prices in the Bombay Stock Exchange for the three-year period 2000 2002. Random matrix analysis is then applied to study the relationship between the coupling of stocks and volatility. The study uses daily returns of 70 stocks for successive time windows of length 85 days for the year 2001. We compare the properties of matrix C of correlations between price fluctuations in time regimes characterized by different volatilities. Our analyses reveal that (i) the largest (deviating) eigenvalue of C correlates highly with the volatility of the index, (ii) there is a shift in the distribution of the components of the eigenvector corresponding to the largest eigenvalue across regimes of different volatilities, (iii) the inverse participation ratio for this eigenvector anti-correlates significantly with the market fluctuations and finally, (iv) this eigenvector of C can be used to set up a Correlation Index, CI whose temporal evolution is significantly correlated with the volatility of the overall market index.

Fractal profit landscape of the stock market.

PubMed

Grönlund, Andreas; Yi, Il Gu; Kim, Beom Jun

2012-01-01

We investigate the structure of the profit landscape obtained from the most basic, fluctuation based, trading strategy applied for the daily stock price data. The strategy is parameterized by only two variables, p and q Stocks are sold and bought if the log return is bigger than p and less than -q, respectively. Repetition of this simple strategy for a long time gives the profit defined in the underlying two-dimensional parameter space of p and q. It is revealed that the local maxima in the profit landscape are spread in the form of a fractal structure. The fractal structure implies that successful strategies are not localized to any region of the profit landscape and are neither spaced evenly throughout the profit landscape, which makes the optimization notoriously hard and hypersensitive for partial or limited information. The concrete implication of this property is demonstrated by showing that optimization of one stock for future values or other stocks renders worse profit than a strategy that ignores fluctuations, i.e., a long-term buy-and-hold strategy.

High-frequency stock linkage and multi-dimensional stationary processes

NASA Astrophysics Data System (ADS)

Wang, Xi; Bao, Si; Chen, Jingchao

2017-02-01

In recent years, China's stock market has experienced dramatic fluctuations; in particular, in the second half of 2014 and 2015, the market rose sharply and fell quickly. Many classical financial phenomena, such as stock plate linkage, appeared repeatedly during this period. In general, these phenomena have usually been studied using daily-level data or minute-level data. Our paper focuses on the linkage phenomenon in Chinese stock 5-second-level data during this extremely volatile period. The method used to select the linkage points and the arbitrage strategy are both based on multi-dimensional stationary processes. A new program method for testing the multi-dimensional stationary process is proposed in our paper, and the detailed program is presented in the paper's appendix. Because of the existence of the stationary process, the strategy's logarithmic cumulative average return will converge under the condition of the strong ergodic theorem, and this ensures the effectiveness of the stocks' linkage points and the more stable statistical arbitrage strategy.

Returning forests analyzed with the forest identity.

PubMed

Kauppi, Pekka E; Ausubel, Jesse H; Fang, Jingyun; Mather, Alexander S; Sedjo, Roger A; Waggoner, Paul E

2006-11-14

Amid widespread reports of deforestation, some nations have nevertheless experienced transitions from deforestation to reforestation. In a causal relationship, the Forest Identity relates the carbon sequestered in forests to the changing variables of national or regional forest area, growing stock density per area, biomass per growing stock volume, and carbon concentration in the biomass. It quantifies the sources of change of a nation's forests. The Identity also logically relates the quantitative impact on forest expanse of shifting timber harvest to regions and plantations where density grows faster. Among 50 nations with extensive forests reported in the Food and Agriculture Organization's comprehensive Global Forest Resources Assessment 2005, no nation where annual per capita gross domestic product exceeded 4,600 dollars had a negative rate of growing stock change. Using the Forest Identity and national data from the Assessment report, a single synoptic chart arrays the 50 nations with coordinates of the rates of change of basic variables, reveals both clusters of nations and outliers, and suggests trends in returning forests and their attributes. The Forest Identity also could serve as a tool for setting forest goals and illuminating how national policies accelerate or retard the forest transitions that are diffusing among nations.

Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach

NASA Astrophysics Data System (ADS)

Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar

2010-10-01

To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.

Effects of fire interval restoration on carbon and nitrogen in sedimentary- and volcanic-derived soils of the Mogollon Rim, Arizona

Treesearch

Dan Neary; Steven T. Overby; Sally M. Haase

2003-01-01

Prescribed fire was returned into over-stocked ponderosa pine stands on the Mogollon Rim of Arizona for the purpose of restoring fire into the ecosystem and removing fuel buildups. Prescribed fires have been ignited at intervals of 1, 2, 4, 6, 8, and 10 years to determine the best fire return interval for Southwest ponderosa pine ecosystems. Two sites were treated; one...

A wavelet based approach to measure and manage contagion at different time scales

NASA Astrophysics Data System (ADS)

Berger, Theo

2015-10-01

We decompose financial return series of US stocks into different time scales with respect to different market regimes. First, we examine dependence structure of decomposed financial return series and analyze the impact of the current financial crisis on contagion and changing interdependencies as well as upper and lower tail dependence for different time scales. Second, we demonstrate to which extent the information of different time scales can be used in the context of portfolio management. As a result, minimizing the variance of short-run noise outperforms a portfolio that minimizes the variance of the return series.

Dynamical Stochastic Processes of Returns in Financial Markets

NASA Astrophysics Data System (ADS)

Kim, Kyungsik; Kim, Soo Yong; Lim, Gyuchang; Zhou, Junyuan; Yoon, Seung-Min

2006-03-01

We show how the evolution of probability distribution functions of the returns from the tick data of the Korean treasury bond futures (KTB) and the S&P 500 stock index can be described by means of the Fokker-Planck equation. We derive the Fokker- Planck equation from the estimated Kramers-Moyal coefficients estimated directly from the empirical data. By analyzing the statistics of the returns, we present the quantitative deterministic and random influences on both financial time series, for which we can give a simple physical interpretation. Finally, we remark that the diffusion coefficient should be significantly considered to make a portfolio.

Critical comparison of several order-book models for stock-market fluctuations

NASA Astrophysics Data System (ADS)

Slanina, F.

2008-01-01

Far-from-equilibrium models of interacting particles in one dimension are used as a basis for modelling the stock-market fluctuations. Particle types and their positions are interpreted as buy and sel orders placed on a price axis in the order book. We revisit some modifications of well-known models, starting with the Bak-Paczuski-Shubik model. We look at the four decades old Stigler model and investigate its variants. One of them is the simplified version of the Genoa artificial market. The list of studied models is completed by the models of Maslov and Daniels et al. Generically, in all cases we compare the return distribution, absolute return autocorrelation and the value of the Hurst exponent. It turns out that none of the models reproduces satisfactorily all the empirical data, but the most promising candidates for further development are the Genoa artificial market and the Maslov model with moderate order evaporation.

Multiscaling and clustering of volatility

NASA Astrophysics Data System (ADS)

Pasquini, Michele; Serva, Maurizio

1999-07-01

The dynamics of prices in stock markets has been studied intensively both experimentally (data analysis) and theoretically (models). Nevertheless, while the distribution of returns of the most important indices is known to be a truncated Lévy, the behaviour of volatility correlations is still poorly understood. What is well known is that absolute returns have memory on a long time range, this phenomenon is known in financial literature as clustering of volatility. In this paper we show that volatility correlations are power laws with a non-unique scaling exponent. This kind of multiscale phenomenology is known to be relevant in fully developed turbulence and in disordered systems and it is pointed out here for the first time for a financial series. In our study we consider the New York Stock Exchange (NYSE) daily index, from January 1966 to June 1998, for a total of 8180 working days.

Influence of the Investor's Behavior on the Complexity of the Stock Market

NASA Astrophysics Data System (ADS)

Atman, A. P. F.; Gonçalves, Bruna Amin

2012-04-01

One of the pillars of the finance theory is the efficient-market hypothesis, which is used to analyze the stock market. However, in recent years, this hypothesis has been questioned by a number of studies showing evidence of unusual behaviors in the returns of financial assets ("anomalies") caused by behavioral aspects of the economic agents. Therefore, it is time to initiate a debate about the efficient-market hypothesis and the "behavioral finances." We here introduce a cellular automaton model to study the stock market complexity, considering different behaviors of the economical agents. From the analysis of the stationary standard of investment observed in the simulations and the Hurst exponents obtained for the term series of stock index, we draw conclusions concerning the complexity of the model compared to real markets. We also investigate which conditions of the investors are able to influence the efficient market hypothesis statements.

Dependency structure and scaling properties of financial time series are related

PubMed Central

Morales, Raffaello; Di Matteo, T.; Aste, Tomaso

2014-01-01

We report evidence of a deep interplay between cross-correlations hierarchical properties and multifractality of New York Stock Exchange daily stock returns. The degree of multifractality displayed by different stocks is found to be positively correlated to their depth in the hierarchy of cross-correlations. We propose a dynamical model that reproduces this observation along with an array of other empirical properties. The structure of this model is such that the hierarchical structure of heterogeneous risks plays a crucial role in the time evolution of the correlation matrix, providing an interpretation to the mechanism behind the interplay between cross-correlation and multifractality in financial markets, where the degree of multifractality of stocks is associated to their hierarchical positioning in the cross-correlation structure. Empirical observations reported in this paper present a new perspective towards the merging of univariate multi scaling and multivariate cross-correlation properties of financial time series. PMID:24699417

Quantifying the Behavior of Stock Correlations Under Market Stress

PubMed Central

Preis, Tobias; Kenett, Dror Y.; Stanley, H. Eugene; Helbing, Dirk; Ben-Jacob, Eshel

2012-01-01

Understanding correlations in complex systems is crucial in the face of turbulence, such as the ongoing financial crisis. However, in complex systems, such as financial systems, correlations are not constant but instead vary in time. Here we address the question of quantifying state-dependent correlations in stock markets. Reliable estimates of correlations are absolutely necessary to protect a portfolio. We analyze 72 years of daily closing prices of the 30 stocks forming the Dow Jones Industrial Average (DJIA). We find the striking result that the average correlation among these stocks scales linearly with market stress reflected by normalized DJIA index returns on various time scales. Consequently, the diversification effect which should protect a portfolio melts away in times of market losses, just when it would most urgently be needed. Our empirical analysis is consistent with the interesting possibility that one could anticipate diversification breakdowns, guiding the design of protected portfolios. PMID:23082242

Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2016-08-01

We study stock market instability by using cross-correlations constructed from the return time series of 366 stocks traded on the Tokyo Stock Exchange from January 5, 1998 to December 30, 2013. To investigate the dynamical evolution of the cross-correlations, crosscorrelation matrices are calculated with a rolling window of 400 days. To quantify the volatile market stages where the potential risk is high, we apply the principal components analysis and measure the cumulative risk fraction (CRF), which is the system variance associated with the first few principal components. From the CRF, we detected three volatile market stages corresponding to the bankruptcy of Lehman Brothers, the 2011 Tohoku Region Pacific Coast Earthquake, and the FRB QE3 reduction observation in the study period. We further apply the random matrix theory for the risk analysis and find that the first eigenvector is more equally de-localized when the market is volatile.

Dependency structure and scaling properties of financial time series are related

NASA Astrophysics Data System (ADS)

Morales, Raffaello; Di Matteo, T.; Aste, Tomaso

2014-04-01

We report evidence of a deep interplay between cross-correlations hierarchical properties and multifractality of New York Stock Exchange daily stock returns. The degree of multifractality displayed by different stocks is found to be positively correlated to their depth in the hierarchy of cross-correlations. We propose a dynamical model that reproduces this observation along with an array of other empirical properties. The structure of this model is such that the hierarchical structure of heterogeneous risks plays a crucial role in the time evolution of the correlation matrix, providing an interpretation to the mechanism behind the interplay between cross-correlation and multifractality in financial markets, where the degree of multifractality of stocks is associated to their hierarchical positioning in the cross-correlation structure. Empirical observations reported in this paper present a new perspective towards the merging of univariate multi scaling and multivariate cross-correlation properties of financial time series.

A semiparametric graphical modelling approach for large-scale equity selection

PubMed Central

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption. PMID:28316507

Implications of deregulation in natural gas industry on utility risks and returns

NASA Astrophysics Data System (ADS)

Addepalli, Rajendra P.

This thesis examines the changes in risk and required return on capital for local distribution utility companies in the increasingly competitive natural gas industry. The deregulation in the industry impacts the LDCs in several ways. First, with the introduction of competition consumers have been given choices among suppliers besides the traditional monopoly, the local utility, for purchasing their natural gas supply needs. Second, with the introduction of competition, some of the interstate pipelines were stuck with 'Take Or Pay' contracts and other costs that resulted in 'stranded costs', which have been passed on to customers of the pipeline including the LDCs. Third, the new obligation for the LDCs to purchase gas from the market, as opposed to buying it from pipelines and passing on the costs to its customers, brought opportunities and risks as well. Finally, with the introduction of competition, in some states LDCs have been allowed to enter into unregulated ventures to increase their profits. In the thesis we first develop a multifactor model (MFM) to explain historical common stock returns of individual utilities and of utility portfolios. We use 'rolling regression' analysis to analyze how different variables explain the variation in stock returns over time. Second, we conduct event studies to analyze the events in the deregulation process that had significant impacts on the LDC returns. Finally we assess the changes in risk and required return on capital for the LDCs over a 15 year time frame, covering the deregulation period. We employ four aspects in the examination of risk and return profile of the utilities: measuring (a) changes in required return on common equity and Weighted Average Cost of Capital, (b) changes in risk premium (WACC less an interest rate proxy), (c) changes in utility bond ratings, and (d) changes in dividend payments, new debt and equity issuances. We perform regression analysis to explain the changes in the required WACC using new security issuances, dividend payments and revenues of the companies.

Time-scale effects on the gain-loss asymmetry in stock indices

NASA Astrophysics Data System (ADS)

Sándor, Bulcsú; Simonsen, Ingve; Nagy, Bálint Zsolt; Néda, Zoltán

2016-08-01

The gain-loss asymmetry, observed in the inverse statistics of stock indices is present for logarithmic return levels that are over 2 % , and it is the result of the non-Pearson-type autocorrelations in the index. These non-Pearson-type correlations can be viewed also as functionally dependent daily volatilities, extending for a finite time interval. A generalized time-window shuffling method is used to show the existence of such autocorrelations. Their characteristic time scale proves to be smaller (less than 25 trading days) than what was previously believed. It is also found that this characteristic time scale has decreased with the appearance of program trading in the stock market transactions. Connections with the leverage effect are also established.

Measuring information interactions on the ordinal pattern of stock time series

NASA Astrophysics Data System (ADS)

Zhao, Xiaojun; Shang, Pengjian; Wang, Jing

2013-02-01

The interactions among time series as individual components of complex systems can be quantified by measuring to what extent they exchange information among each other. In many applications, one focuses not on the original series but on its ordinal pattern. In such cases, trivial noises appear more likely to be filtered and the abrupt influence of extreme values can be weakened. Cross-sample entropy and inner composition alignment have been introduced as prominent methods to estimate the information interactions of complex systems. In this paper, we modify both methods to detect the interactions among the ordinal pattern of stock return and volatility series, and we try to uncover the information exchanges across sectors in Chinese stock markets.

Stock markets and criticality in the current economic crisis

NASA Astrophysics Data System (ADS)

da Silva, Roberto; Zembrzuski, Marcelo; Correa, Fabio C.; Lamb, Luis C.

2010-12-01

We show that the current economic crisis has led the market to exhibit a non-critical behavior. We do so by analyzing the quantitative parameters of time series from the main assets of the Brazilian Stock Market BOVESPA. By monitoring global persistence we show a deviation of power law behavior during the crisis in a strong analogy with spin systems (from where this concept was originally conceived). Such behavior is corroborated by an emergent heavy tail of absolute return distribution and also by the magnitude autocorrelation exponent. Comparisons with universal exponents obtained in the international stock markets are also performed. This suggests how a thorough analysis of suitable exponents can bring a possible way of forecasting market crises characterized by non-criticality.

Equation-based model for the stock market

NASA Astrophysics Data System (ADS)

Xavier, Paloma O. C.; Atman, A. P. F.; de Magalhães, A. R. Bosco

2017-09-01

We propose a stock market model which is investigated in the forms of difference and differential equations whose variables correspond to the demand or supply of each agent and to the price. In the model, agents are driven by the behavior of their trust contact network as well by fundamental analysis. By means of the deterministic version of the model, the connection between such drive mechanisms and the price is analyzed: imitation behavior promotes market instability, finitude of resources is associated to stock index stability, and high sensitivity to the fair price provokes price oscillations. Long-range correlations in the price temporal series and heavy-tailed distribution of returns are observed for the version of the model which considers different proposals for stochasticity of microeconomic and macroeconomic origins.

Structure of public transit costs in the presence of multiple serial correlation

DOT National Transportation Integrated Search

1999-12-01

Most studies indicate that public transit systems operate under increasing returns to capital stock utilization and are significantly overcapitalized. Existing flexible form time series analyses, however, fail to correct for serial correlation. In th...

Market capitalization of the trucking industry sector, 2005

DOT National Transportation Integrated Search

2006-08-01

This report focuses on the market valuation of the overall trucking industry sector and each segment within it. In the past, while the focus has been on stock price appreciation or depreciation, this report emphasizes market capitalization returns. S...

A combination SMS and transportation reimbursement intervention to improve HIV care following abnormal CD4 test results in rural Uganda: a prospective observational cohort study.

PubMed

Siedner, Mark J; Santorino, Data; Lankowski, Alexander J; Kanyesigye, Michael; Bwana, Mwebesa B; Haberer, Jessica E; Bangsberg, David R

2015-07-06

Up to 50 % of HIV-infected persons in sub-Saharan Africa are lost from care between HIV diagnosis and antiretroviral therapy (ART) initiation. Structural barriers, including cost of transportation to clinic and poor communication systems, are major contributors. We conducted a prospective, pragmatic, before-and-after clinical trial to evaluate a combination mobile health and transportation reimbursement intervention to improve care at a publicly operated HIV clinic in Uganda. Patients undergoing CD4 count testing were enrolled, and clinicians selected a result threshold that would prompt early return for ART initiation or further care. Participants enrolled in the pre-intervention period (January - August 2012) served as a control group. Participants in the intervention period (September 2012 - November 2013) were randomized to receive daily short message service (SMS) messages for up to seven days in one of three formats: 1) messages reporting an abnormal result directly, 2) personal identification number-protected messages reporting an abnormal result, or 3) messages reading "ABCDEFG" to confidentially convey an abnormal result. Participants returning within seven days of their first message received transportation reimbursements (about $6USD). Our primary outcomes of interest were time to return to clinic and time to ART initiation. There were 45 participants in the pre-intervention period and 138 participants in the intervention period (46, 49, and 43 in the direct, PIN, and coded groups, respectively) with low CD4 count results. Median time to clinic return was 33 days (IQR 11-49) in the pre-intervention period and 6 days (IQR 3-16) in the intervention period (P < 0.001); and median time to ART initiation was 47 days (IQR 11-75) versus 12 days (IQR 5-19), (P < 0.001). In multivariable models, participants in the intervention period had earlier return to clinic (AHR 2.32, 95 %CI 1.53 to 3.51) and earlier time to ART initiation (AHR 2.27, 95 %CI 1.38 to 3.72). All three randomized message formats improved time to return to clinic and time to ART initiation (P < 0.01 for all comparisons versus the pre-intervention period). A combination of an SMS laboratory result communication system and transportation reimbursements significantly decreased time to clinic return and time to ART initiation after abnormal CD4 test results. Clinicaltrials.gov NCT01579214 , approved 13 April 2012.

Financial market dynamics: superdiffusive or not?

NASA Astrophysics Data System (ADS)

Devi, Sandhya

2017-08-01

The behavior of stock market returns over a period of 1-60 d has been investigated for S&P 500 and Nasdaq within the framework of nonextensive Tsallis statistics. Even for such long terms, the distributions of the returns are non-Gaussian. They have fat tails indicating that the stock returns do not follow a random walk model. In this work, a good fit to a Tsallis q-Gaussian distribution is obtained for the distributions of all the returns using the method of Maximum Likelihood Estimate. For all the regions of data considered, the values of the scaling parameter q, estimated from 1 d returns, lie in the range 1.4-1.65. The estimated inverse mean square deviations (beta) show a power law behavior in time with exponent values between  -0.91 and  -1.1 indicating normal to mildly subdiffusive behavior. Quite often, the dynamics of market return distributions is modelled by a Fokker-Plank (FP) equation either with a linear drift and a nonlinear diffusion term or with just a nonlinear diffusion term. Both of these cases support a q-Gaussian distribution as a solution. The distributions obtained from current estimated parameters are compared with the solutions of the FP equations. For negligible drift term, the inverse mean square deviations (betaFP) from the FP model follow a power law with exponent values between  -1.25 and  -1.48 indicating superdiffusion. When the drift term is non-negligible, the corresponding betaFP do not follow a power law and become stationary after certain characteristic times that depend on the values of the drift parameter and q. Neither of these behaviors is supported by the results of the empirical fit.

Fuzzy bi-objective linear programming for portfolio selection problem with magnitude ranking function

NASA Astrophysics Data System (ADS)

Kusumawati, Rosita; Subekti, Retno

2017-04-01

Fuzzy bi-objective linear programming (FBOLP) model is bi-objective linear programming model in fuzzy number set where the coefficients of the equations are fuzzy number. This model is proposed to solve portfolio selection problem which generate an asset portfolio with the lowest risk and the highest expected return. FBOLP model with normal fuzzy numbers for risk and expected return of stocks is transformed into linear programming (LP) model using magnitude ranking function.

Market Correlation Structure Changes Around the Great Crash: A Random Matrix Theory Analysis of the Chinese Stock Market

NASA Astrophysics Data System (ADS)

Han, Rui-Qi; Xie, Wen-Jie; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.

Crash and Wait? The impact of the Great Recession on Retirement Planning of Older Americans

PubMed Central

McFall, Brooke Helppie

2012-01-01

This study uses data from pre- and post-crash surveys from the Cognitive Economics study to examine the impact of recent stock and labor market wealth losses on the planned retirement ages of older Americans. Regression estimates imply that the average wealth loss between July 2008 and May/June 2009 is associated with an increase in planned retirement age of approximately 2.5 months. Furthermore, pessimism about future stock market returns is found to amplify the impact of wealth losses on retirement timing. PMID:23413315

Comparing minimum spanning trees of the Italian stock market using returns and volumes

NASA Astrophysics Data System (ADS)

Coletti, Paolo

2016-12-01

We have built the network of the top 100 Italian quoted companies in the decade 2001-2011 using four different methods, comparing the resulting minimum spanning trees for methods and industry sectors. Our starting method is based on Person's correlation of log-returns used by several other authors in the last decade. The second one is based on the correlation of symbolized log-returns, the third of log-returns and traded money and the fourth one uses a combination of log-returns with traded money. We show that some sectors correspond to the network's clusters while others are scattered, in particular the trading and apparel sectors. We analyze the different graph's measures for the four methods showing that the introduction of volumes induces larger distances and more homogeneous trees without big clusters.

Fractal Profit Landscape of the Stock Market

PubMed Central

Grönlund, Andreas; Yi, Il Gu; Kim, Beom Jun

2012-01-01

We investigate the structure of the profit landscape obtained from the most basic, fluctuation based, trading strategy applied for the daily stock price data. The strategy is parameterized by only two variables, p and q Stocks are sold and bought if the log return is bigger than p and less than –q, respectively. Repetition of this simple strategy for a long time gives the profit defined in the underlying two-dimensional parameter space of p and q. It is revealed that the local maxima in the profit landscape are spread in the form of a fractal structure. The fractal structure implies that successful strategies are not localized to any region of the profit landscape and are neither spaced evenly throughout the profit landscape, which makes the optimization notoriously hard and hypersensitive for partial or limited information. The concrete implication of this property is demonstrated by showing that optimization of one stock for future values or other stocks renders worse profit than a strategy that ignores fluctuations, i.e., a long-term buy-and-hold strategy. PMID:22558079

Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects

NASA Astrophysics Data System (ADS)

Pan, Zhiyuan; Liu, Li

2018-02-01

In this paper, we extend the GARCH-MIDAS model proposed by Engle et al. (2013) to account for the leverage effect in short-term and long-term volatility components. Our in-sample evidence suggests that both short-term and long-term negative returns can cause higher future volatility than positive returns. Out-of-sample results show that the predictive ability of GARCH-MIDAS is significantly improved after taking the leverage effect into account. The leverage effect for short-term volatility component plays more important role than the leverage effect for long-term volatility component in affecting out-of-sample forecasting performance.

Market dynamics and stock price volatility

NASA Astrophysics Data System (ADS)

Li, H.; Rosser, J. B., Jr.

2004-06-01

This paper presents a possible explanation for some of the empirical properties of asset returns within a heterogeneous-agents framework. The model turns out, even if we assume the input fundamental value follows an simple Gaussian distribution lacking both fat tails and volatility dependence, these features can show up in the time series of asset returns. In this model, the profit comparison and switching between heterogeneous play key roles, which build a connection between endogenous market and the emergence of stylized facts.

Feasibility of dsRNA treatment for post-clearing SPF shrimp stocks of newly discovered viral infections using Laem Singh virus (LSNV) as a model.

PubMed

Saksmerprome, Vanvimon; Charoonnart, Patai; Flegel, Timothy W

2017-05-02

Using post-larvae derived from specific pathogen free (SPF) stocks in penaeid shrimp farming has led to a dramatic increase in production. At the same time, new pathogens of farmed shrimp are continually being discovered. Sometimes these pathogens are carried by shrimp and other crustaceans as persistent infections without gross signs of disease. Thus it is that a 5-generation stock of Penaeus monodon SPF for several pathogens was found, post-stock-development, to be persistently-infected with newly-discovered Laem Singh virus (LSNV). In this situation, the stock developers were faced with destroying their existing stock (developed over a long period at considerable cost) and starting the whole stock development process anew in order to add LSNV to its SPF list. As an alternative, it was hypothesized that injection of complementary dsRNA into viral-infected broodstock prior to mating might inhibit replication of the target virus sufficiently to reduce or eliminate its transmission to their offspring. Subsequent selection of uninfected offspring would allow for post-clearing of LSNV from the existing stock and for conversion of the stock to LSNV-free status. Testing this hypothesis using the LSNV-infected stock described above, we found that transmission was substantially reduced in several treated broodstock compared to much higher transmission in buffer-injected broodstock. Based on these results, the model is proposed for post-clearing of SPF stocks using dsRNA treatment. The model may also be applicable to post-clearing of exceptional, individual performers from grow-out ponds for return to a nucleus breeding center. Copyright © 2017 Elsevier B.V. All rights reserved.

Financial consequences of commercial thinning regimes in young-growth Douglas-fir

Treesearch

Robert M. Randall

1977-01-01

Commercial thinning in fully-stocked normal Douglas-fir stands of merchantable size is evaluated and compared to the alternatives of leaving stands to grow unthinned or of liquidating them. Comparisons are made in terms of volume production and financial returns.

Frequency aspects of information transmission in a network of three western equity markets

NASA Astrophysics Data System (ADS)

Schmidbauer, Harald; Rösch, Angi; Uluceviz, Erhan

2017-11-01

Cycles in the behavior of stock markets have been widely documented. There is an increasing body of literature on whether stock markets anticipate business cycles or its turning points. Several recent studies assert that financial integration impacts positively on business cycle comovements of economies. We consider three western equity markets, represented by their respective stock indices: DJIA (USA), FTSE 100 (UK), and Euro Stoxx 50 (euro area). Connecting these three markets together via vector autoregressive processes in index returns, we construct ;propagation values; to measure and trace, on a daily basis, the relative importance of a market as a volatility creator within the network, where volatility is due to a return shock in a market. A cross-wavelet analysis reveals the joint frequency structure of pairs of the propagation value series, in particular whether or not two series tend to move in the same direction at a given frequency. Our main findings are: (i) From 2001 onwards, the daily propagation values of markets have been fluctuating much less than before, and high frequencies have become less pronounced; (ii) the European markets are in phase at business cycle frequency, while the US market is not in phase with either European market; (iii) in 2008, the euro area has taken over the leading role. This approach not only provides new insight into the time-dependent interplay of equity markets, but it can also replicate certain findings of traditional business cycle research, and it has the advantage of using only readily available stock market data.

The stability of portfolio investment in stock crashes

NASA Astrophysics Data System (ADS)

Li, Yun-Xian; Qian, Zhen-Wei; Li, Jiang-Cheng; Tang, Nian-Sheng; Mei, Dong-Cheng

2016-08-01

The stability of portfolio investment in stock market crashes with Markowitz portfolio is investigated by the method of theoretical and empirical simulation. From numerical simulation of the mean escape time (MET), we conclude that: (i) The increasing number (Np) of stocks in Markowitz portfolio induces a maximum in the curve of MET versus the initial position; (ii) A critical value of Np in the behavior of MET versus the long-run variance or amplitude of volatility fluctuations maximumlly enhances the stability of portfolio investment. When Np takes value below the critical value, the increasing Np enhances the stability of portfolio investment, but restrains it when Np takes value above the critical value. In addition, a good agreement of both the MET and probability density functions of returns is found between real data and theoretical results.

Effect of intravaginal clindamycin cream on pregnancy outcome and on abnormal vaginal microbial flora of pregnant women.

PubMed

Rosenstein, I J; Morgan, D J; Lamont, R F; Sheehan, M; Doré, C J; Hay, P E; Taylor-Robinson, D

2000-01-01

To determine whether intravaginal clindamycin cream reduces the incidence of abnormal pregnancy outcome in women with abnormal vaginal microbial flora graded as intermediate or BV and to investigate the effect of the antibiotic on vaginal microbial flora. A prospective cohort study of pregnant women in an antenatal clinic of a district general hospital. The subjects were 268 women who had abnormal vaginal microbial flora at first clinic visit by examination of a Gram-stained vaginal smear and 34 women with a normal vaginal flora. Two hundred and thirty-seven women were evaluable. Women with abnormal Gram-stained smears (graded as II or III) on clinic recall were randomised to receive treatment (intravaginal clindamycin cream) or placebo and followed to assess outcome of pregnancy, vaginal flora, and detection of Mycoplasma hominis and Ureaplasma urealyticum after treatment. Abnormal outcomes of pregnancy were not significantly different in treated and placebo groups by Chi square (P = 0.2). However, women with grade III flora responded better to clindamycin than women with grade II flora by numbers of abnormal outcomes (P = 0.03) and return to normal vaginal flora (P = 0.01) (logistic regression analysis model). This may be due to differences in vaginal bacterial species in these grades. Women whose abnormal vaginal flora had spontaneously returned to normal on follow-up and were therefore not treated (revertants) had as many abnormal outcomes as placebos suggesting that damage by abnormal bacterial species occurred early in pregnancy. Gram-stain screening distinguishing grade II from grade III flora may be helpful in prescribing treatment other than clindamycin for women with grade II flora. Earlier diagnosis and treatment may be more effective in preventing an abnormal outcome, possibly as soon as pregnancy is diagnosed or even offered as a pre-conception screen.

Assessing the stock market volatility for different sectors in Malaysia by using standard deviation and EWMA methods

NASA Astrophysics Data System (ADS)

Saad, Shakila; Ahmad, Noryati; Jaffar, Maheran Mohd

2017-11-01

Nowadays, the study on volatility concept especially in stock market has gained so much attention from a group of people engaged in financial and economic sectors. The applications of volatility concept in financial economics can be seen in valuation of option pricing, estimation of financial derivatives, hedging the investment risk and etc. There are various ways to measure the volatility value. However for this study, two methods are used; the simple standard deviation and Exponentially Weighted Moving Average (EWMA). The focus of this study is to measure the volatility on three different sectors of business in Malaysia, called primary, secondary and tertiary by using both methods. The daily and annual volatilities of different business sector based on stock prices for the period of 1 January 2014 to December 2014 have been calculated in this study. Result shows that different patterns of the closing stock prices and return give different volatility values when calculating using simple method and EWMA method.

Sector strength and efficiency on developed and emerging financial markets

NASA Astrophysics Data System (ADS)

Fiedor, Paweł

2014-11-01

In this paper we analyse the importance of sectors and market efficiency on developed and emerging financial markets. To perform this we analyse New York Stock Exchange between 2004 and 2013 and Warsaw Stock Exchange between 2000 and 2013. To find out the importance of sectors we construct minimal spanning trees for annual time series consisting of daily log returns and calculate centrality measures for all stocks, which we then aggregate by sectors. Such analysis is of interest to analysts for whom the knowledge of the influence of particular groups of stocks to the market behaviour is crucial. We also analyse the predictability of price changes on those two markets formally, using the information-theoretic concept of entropy rate, to find out the differences in market efficiency between a developed and an emerging market, and between sectors themselves. We postulate that such analysis is important to the study of financial markets as it can contribute to the profitability of investments, particularly in the case of algorithmic trading.

Population characteristics of channel catfish near the northern edge of their distribution: implications for management

USGS Publications Warehouse

Carter-Lynn, K. P.; Quist, Michael C.

2015-01-01

Channel catfish, Ictalurus punctatus (Rafinesque), populations in six lakes in northern Idaho, USA, were sampled to describe their population characteristics. During the summers of 2011 and 2012, 4864 channel catfish were sampled. Channel catfish populations had low to moderate catch rates, and length structure was dominated by fish <400 mm. Channel catfish were in good body condition. All populations were maintained by stocking age-1 or age-2 fish. Growth of fish reared in thermally enriched environments prior to stocking was fast compared to other North American channel catfish populations. After stocking, growth of channel catfish declined rapidly. Once stocked, cold water temperatures, prey resources and (or) genetic capabilities limited growth. Total annual mortality of age 2 and older channel catfish was generally <40%. Tag returns indicated that angler exploitation was low, varying from 0 to 43% among lakes. This research provides insight on factors regulating channel catfish population dynamics and highlights important considerations associated with their ecology and management.

Post-hit dynamics of price limit hits in the Chinese stock markets

NASA Astrophysics Data System (ADS)

Wu, Ting; Wang, Yue; Li, Ming-Xia

2017-01-01

Price limit trading rules are useful to cool off traders short-term trading mania on individual stocks. The price dynamics approaching the limit boards are known as the magnet effect. However, the price dynamics after opening price limit hits are not well investigated. Here, we provide a detailed analysis on the price dynamics after the hits of up-limit or down-limit is open based on all A-share stocks traded in the Chinese stock markets. A "W" shape is found in the expected return, which reveals high probability of a continuous price limit hit on the following day. We also find that price dynamics after opening limit hits are dependent on the market trends. The time span of continuously hitting the price limit is found to an influence factor of the expected profit after the limit hit is open. Our analysis provides a better understanding of the price dynamics around the limit boards and contributes potential practical values for investors.

Just how good an investment is the biopharmaceutical sector?

PubMed

Thakor, Richard T; Anaya, Nicholas; Zhang, Yuwei; Vilanilam, Christian; Siah, Kien Wei; Wong, Chi Heem; Lo, Andrew W

2017-12-01

Uncertainty surrounding the risk and reward of investments in biopharmaceutical companies poses a challenge to those interested in funding such enterprises. Using data on publicly traded stocks, we track the performance of 1,066 biopharmaceutical companies from 1930 to 2015-the most comprehensive financial analysis of this sector to date. Our systematic exploration of methods for distinguishing biotech and pharmaceutical companies yields a dynamic, more accurate classification method. We find that the performance of the biotech sector is highly sensitive to the presence of a few outlier companies, and confirm that nearly all biotech companies are loss-making enterprises, exhibiting high stock volatility. In contrast, since 2000, pharmaceutical companies have become increasingly profitable, with risk-adjusted returns consistently outperforming the market. The performance of all biopharmaceutical companies is subject not only to factors arising from their drug pipelines (idiosyncratic risk), but also from general economic conditions (systematic risk). The risk associated with returns has profound implications both for patterns of investment and for funding innovation in biomedical R&D.

Temporal Structure of Volatility Fluctuations

NASA Astrophysics Data System (ADS)

Wang, Fengzhong; Yamasaki, Kazuko; Stanley, H. Eugene; Havlin, Shlomo

Volatility fluctuations are of great importance for the study of financial markets, and the temporal structure is an essential feature of fluctuations. To explore the temporal structure, we employ a new approach based on the return interval, which is defined as the time interval between two successive volatility values that are above a given threshold. We find that the distribution of the return intervals follows a scaling law over a wide range of thresholds, and over a broad range of sampling intervals. Moreover, this scaling law is universal for stocks of different countries, for commodities, for interest rates, and for currencies. However, further and more detailed analysis of the return intervals shows some systematic deviations from the scaling law. We also demonstrate a significant memory effect in the return intervals time organization. We find that the distribution of return intervals is strongly related to the correlations in the volatility.

Investment strategy due to the minimization of portfolio noise level by observations of coarse-grained entropy

NASA Astrophysics Data System (ADS)

Urbanowicz, Krzysztof; Hołyst, Janusz A.

2004-12-01

Using a recently developed method of noise level estimation that makes use of properties of the coarse-grained entropy, we have analyzed the noise level for the Dow Jones index and a few stocks from the New York Stock Exchange. We have found that the noise level ranges from 40% to 80% of the signal variance. The condition of a minimal noise level has been applied to construct optimal portfolios from selected shares. We show that the implementation of a corresponding threshold investment strategy leads to positive returns for historical data.

Dynamical stochastic processes of returns in financial markets

NASA Astrophysics Data System (ADS)

Lim, Gyuchang; Kim, SooYong; Yoon, Seong-Min; Jung, Jae-Won; Kim, Kyungsik

2007-03-01

We study the evolution of probability distribution functions of returns, from the tick data of the Korean treasury bond (KTB) futures and the S&P 500 stock index, which can be described by means of the Fokker-Planck equation. We show that the Fokker-Planck equation and the Langevin equation from the estimated Kramers-Moyal coefficients can be estimated directly from the empirical data. By analyzing the statistics of the returns, we present quantitatively the deterministic and random influences on financial time series for both markets, for which we can give a simple physical interpretation. We particularly focus on the diffusion coefficient, which may be important for the creation of a portfolio.

On the probability distribution of stock returns in the Mike-Farmer model

NASA Astrophysics Data System (ADS)

Gu, G.-F.; Zhou, W.-X.

2009-02-01

Recently, Mike and Farmer have constructed a very powerful and realistic behavioral model to mimick the dynamic process of stock price formation based on the empirical regularities of order placement and cancelation in a purely order-driven market, which can successfully reproduce the whole distribution of returns, not only the well-known power-law tails, together with several other important stylized facts. There are three key ingredients in the Mike-Farmer (MF) model: the long memory of order signs characterized by the Hurst index Hs, the distribution of relative order prices x in reference to the same best price described by a Student distribution (or Tsallis’ q-Gaussian), and the dynamics of order cancelation. They showed that different values of the Hurst index Hs and the freedom degree αx of the Student distribution can always produce power-law tails in the return distribution fr(r) with different tail exponent αr. In this paper, we study the origin of the power-law tails of the return distribution fr(r) in the MF model, based on extensive simulations with different combinations of the left part L(x) for x < 0 and the right part R(x) for x > 0 of fx(x). We find that power-law tails appear only when L(x) has a power-law tail, no matter R(x) has a power-law tail or not. In addition, we find that the distributions of returns in the MF model at different timescales can be well modeled by the Student distributions, whose tail exponents are close to the well-known cubic law and increase with the timescale.

26 CFR 1.6046-1 - Returns as to organization or reorganization of foreign corporations and as to acquisitions of...

Code of Federal Regulations, 2014 CFR

2014-04-01

... as in Example 5 except that, in addition, on November 1, 2015, D donates 4% of the outstanding stock... (whether by the whole or half blood), his spouse, his ancestors, and his lineal descendants. However, when...

Topics in Finance Part IV--Valuation

ERIC Educational Resources Information Center

Laux, Judy

2010-01-01

This article looks at security valuation from the perspective of the financial manager, accenting the relationships to stockholder wealth maximization (SWM), risk and return, and potential agency problems. It also covers some of the pertinent literature related to how investors and creditors price the stocks and bonds of corporations.

Corporation Accounting, Business Education: 7709.31.

ERIC Educational Resources Information Center

Carino, Mariano G.

The course aims to help students develop an understanding of the organization of corporations, corporate stock and bond transactions, fiscal reports, income tax returns, and dividends. Students also analyze financial statements and complete a corporation practice set. An outline of course content includes: (1) equipment and supplies, (2)…

Factor investing based on Musharakah principle

NASA Astrophysics Data System (ADS)

Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md; Amin, Mohd Nazrul Mohd

2015-10-01

Shariah stock investing has become a widely discussed topic in financial industry as part of today's investment strategy. The strategy primarily applies market capitalization allocations. However, some researchers have argued that market capitalization weighting is inherently flawed and have advocated replacing market capitalization allocations with factor allocations. In this paper, we discuss the rationale for factor investing based on Musharakah principle. The essential elements or factors of Musharakah principle such as business sector, management capability, profitability growth and capital efficiency are embedded in the Shariah-compliant stock. We then transform these factors into indexation for better analysis and performance measurement. Investment universe for this research covers Malaysian stocks for the period of January 2009 to December 2013. We found out that these factor indexes have historically earned excess returns over market capitalization weighted indexes and experienced higher Sharpe Ratios.

Evaluation of offshore stocking of Lake Trout in Lake Ontario

USGS Publications Warehouse

Lantry, B.F.; O'Gorman, R.; Strang, T.G.; Lantry, J.R.; Connerton, M.J.; Schanger, T.

2011-01-01

Restoration stocking of hatchery-reared lake trout Salvelinus namaycush has occurred in Lake Ontario since 1973. In U.S. waters, fish stocked through 1990 survived well and built a large adult population. Survival of yearlings stocked from shore declined during 1990–1995, and adult numbers fell during 1998–2005. Offshore stocking of lake trout was initiated in the late 1990s in response to its successful mitigation of predation losses to double-crested cormorants Phalacrocorax auritus and the results of earlier studies that suggested it would enhance survival in some cases. The current study was designed to test the relative effectiveness of three stocking methods at a time when poststocking survival for lake trout was quite low and losses due to fish predators was a suspected factor. The stocking methods tested during 2000–2002 included May offshore, May onshore, and June onshore. Visual observations during nearshore stockings and hydroacoustic observations of offshore stockings indicated that release methods were not a direct cause of fish mortality. Experimental stockings were replicated for 3 years at one site in the southwest and for 2 years at one site in the southeast. Offshore releases used a landing craft to transport hatchery trucks from 3 to 6 km offshore out to 55–60-m-deep water. For the southwest site, offshore stocking significantly enhanced poststocking survival. Among the three methods, survival ratios were 1.74 : 1.00 : 1.02 (May offshore : May onshore : June onshore). Although not statistically significant owing to the small samples, the trends were similar for the southeast site, with survival ratios of 1.67 : 1.00 : 0.72. Consistent trends across years and sites indicated that offshore stocking of yearling lake trout during 2000–2002 provided nearly a twofold enhancement in survival; however, this increase does not appear to be great enough to achieve the 12-fold enhancement necessary to return population abundance to restoration targets.

Value-at-Risk analysis using ARMAX GARCHX approach for estimating risk of banking subsector stock return’s

NASA Astrophysics Data System (ADS)

Dewi Ratih, Iis; Sutijo Supri Ulama, Brodjol; Prastuti, Mike

2018-03-01

Value at Risk (VaR) is one of the statistical methods used to measure market risk by estimating the worst losses in a given time period and level of confidence. The accuracy of this measuring tool is very important in determining the amount of capital that must be provided by the company to cope with possible losses. Because there is a greater losses to be faced with a certain degree of probability by the greater risk. Based on this, VaR calculation analysis is of particular concern to researchers and practitioners of the stock market to be developed, thus getting more accurate measurement estimates. In this research, risk analysis of stocks in four banking sub-sector, Bank Rakyat Indonesia, Bank Mandiri, Bank Central Asia and Bank Negara Indonesia will be done. Stock returns are expected to be influenced by exogenous variables, namely ICI and exchange rate. Therefore, in this research, stock risk estimation are done by using VaR ARMAX-GARCHX method. Calculating the VaR value with the ARMAX-GARCHX approach using window 500 gives more accurate results. Overall, Bank Central Asia is the only bank had the estimated maximum loss in the 5% quantile.

Modeling Markov switching ARMA-GARCH neural networks models and an application to forecasting stock returns.

PubMed

Bildirici, Melike; Ersin, Özgür

2014-01-01

The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100). Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray's MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray's MS-GARCH model. Therefore, the models are promising for various economic applications.

Modeling Markov Switching ARMA-GARCH Neural Networks Models and an Application to Forecasting Stock Returns

PubMed Central

Bildirici, Melike; Ersin, Özgür

2014-01-01

The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100). Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray's MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray's MS-GARCH model. Therefore, the models are promising for various economic applications. PMID:24977200

Time-bound product returns and optimal order quantities for mass merchandisers

NASA Astrophysics Data System (ADS)

Yu, Min-Chun; Goh, Mark

2012-01-01

The return guidelines for a mass merchandiser usually entail a grace period, a markdown on the original price and the condition of the returned items. This research utilises eight scenarios formed from the variation of possible return guidelines to model the cost functions of single-product categories for a typical mass merchandiser. Models for the eight scenarios are developed and solved with the objective of maximising the expected profit so as to obtain closed form solutions for the associated optimal order quantity. An illustrative example and sensitivity analysis are provided to demonstrate the applicability of the model. Our results show that merchandisers who allow for returns within a time window, albeit with a penalty cost imposed and the returned products being recoverable, should plan for larger order amounts as such products do not affect the business. Similarly, the merchandisers who allow for returns beyond a grace period and without any penalty charges, but where the returned products are irrecoverable, should manage their stocks in this category more judiciously by ordering as little as possible so as to limit the number of returns and carefully consider the effects of their customer satisfaction-guaranteed policies, if any.

Analysis of cyclical behavior in time series of stock market returns

NASA Astrophysics Data System (ADS)

Stratimirović, Djordje; Sarvan, Darko; Miljković, Vladimir; Blesić, Suzana

2018-01-01

In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time-dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differentiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.

41 CFR 101-27.507 - Transportation and other costs.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 2 2010-07-01 2010-07-01 true Transportation and other costs. 101-27.507 Section 101-27.507 Public Contracts and Property Management Federal Property... MANAGEMENT 27.5-Return of GSA Stock Items § 101-27.507 Transportation and other costs. Transportation costs...

New Fund Allows Colleges to Pool Resources for Large-Scale Real-Estate Investments.

ERIC Educational Resources Information Center

McMillen, Liz

1988-01-01

The Real Estate Investment Trust, a companion organization to the Common Trust, allows colleges to commit as little as $50,000 for investments in commercial properties at minimum risk, which could protect endowments while providing returns comparable to those of the stock market. (MSE)

A College with a Small Endowment Moves Away from Cautious Investments.

ERIC Educational Resources Information Center

Nicklin, Julie L.

1997-01-01

Merrimack College (Massachusetts) has abandoned conservative strategies for investing its $16-million endowment, investing more in international stocks and bonds, real estate projects, and small companies to raise annual returns and increase endowment value. The small, Catholic college is heavily dependent on tuition. The diversification plan…

41 CFR 101-27.507 - Transportation and other costs.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 41 Public Contracts and Property Management 2 2014-07-01 2012-07-01 true Transportation and other costs. 101-27.507 Section 101-27.507 Public Contracts and Property Management Federal Property... MANAGEMENT 27.5-Return of GSA Stock Items § 101-27.507 Transportation and other costs. Transportation costs...

41 CFR 101-27.507 - Transportation and other costs.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 41 Public Contracts and Property Management 2 2011-07-01 2007-07-01 true Transportation and other costs. 101-27.507 Section 101-27.507 Public Contracts and Property Management Federal Property... MANAGEMENT 27.5-Return of GSA Stock Items § 101-27.507 Transportation and other costs. Transportation costs...

Financial Planning Strategies for Senior Military Officers.

DTIC Science & Technology

1986-05-15

being offered has declined significantly. In that preferred shares are a sort of hybrid of common stocks and bonds. they offer a middle of the road...2. Total return no-load mutual funds should be your first consideraticn in selectirg an investment veiclE . Avoid speculative, non-liquid investments

41 CFR 101-27.505 - Notice to activity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 2 2010-07-01 2010-07-01 true Notice to activity. 101-27.505 Section 101-27.505 Public Contracts and Property Management Federal Property Management...-Return of GSA Stock Items § 101-27.505 Notice to activity. GSA will provide notice to the offering...

Bipolarity in planarians is not induced by space travel.

PubMed

Sluys, Ronald; Stocchino, Giacinta A

2017-08-01

Available evidence strongly suggests that alternative, Earth-bound explanations should be sought first for the occurrence of a single bipolar planarian flatworm returning from space travel. Double-headed worms have been amply documented as arising under experimental conditions as well as spontaneously in stock cultures of planarians.

Timber management guide for shortleaf pine and oak-pine types in Missouri.

Treesearch

K.A. Brinkman; N.F. Rogers

1967-01-01

Summarizes recommended management practices for the shortleaf pine and oak-pine types in Missouri. Describes sites and soils, and silvical characteristics of pine; discusses rotations, cutting cycles, stocking levels, growing space requirements, and regeneration techniques; and prescribes treatments for stands with specified characteristics to maximize returns from...

Influence of combined iron supplementation and simulated hypoxia on the haematological module of the athlete biological passport.

PubMed

Garvican-Lewis, Laura A; Vuong, Victor L; Govus, Andrew D; Schumacher, Yorck Olaf; Hughes, David; Lovell, Greg; Eichner, Daniel; Gore, Christopher J

2018-04-01

The integrity of the athlete biological passport (ABP) is underpinned by understanding normal fluctuations of its biomarkers to environmental or medical conditions, for example, altitude training or iron deficiency. The combined impact of altitude and iron supplementation on the ABP was evaluated in endurance-trained athletes (n = 34) undertaking 3 weeks of simulated live-high: train-low (14 h.d -1 , 3000 m). Athletes received either oral, intravenous (IV) or placebo iron supplementation, commencing 2 weeks prior and continuing throughout hypoxic exposure. Venous blood was sampled twice prior, weekly during, and up to 6 weeks after altitude. Individual ABP thresholds for haemoglobin concentration ([Hb]), reticulocyte percentage (%retic), and OFF score were calculated using the adaptive model and assessed at 99% and 99.9% specificity. Eleven athletes returned values outside of the calculated reference ranges at 99%, with 8 at 99.9%. The percentage of athletes exceeding the thresholds in each group was similar, but IV returned the most individual occurrences. A similar frequency of abnormalities occurred across the 3 biomarkers, with abnormal [Hb] and OFF score values arising mainly during-, and %retic values mainly post- altitude. Removing samples collected during altitude from the model resulted in 10 athletes returning abnormal values at 99% specificity, 2 of whom had not triggered the model previously. In summary, the abnormalities observed in response to iron supplementation and hypoxia were not systematic and mostly in line with expected physiological adaptations. They do not represent a uniform weakness in the ABP. Nevertheless, altitude training and iron supplementation should be carefully considered by experts evaluating abnormal ABP profiles. Copyright © 2017 John Wiley & Sons, Ltd.

Stock or cash? The trade-offs for buyers and sellers in mergers and acquisitions.

PubMed

Rappaport, A; Sirower, M L

1999-01-01

In 1988, less than 2% of large deals were paid for entirely in stock; by 1998, that number had risen to 50%. The shift has profound ramifications for shareholders of both the acquiring and acquired companies. In this article, the authors provide a framework and two simple tools to guide boards of both companies through the issues they need to consider when making decisions about how to pay for--and whether to accept--a deal. First an acquirer has to decide whether to finance the deal using stock or pay cash. Second, if the acquirer decides to issue stock, it then must decide whether to offer a fixed value of shares or a fixed number of them. Offering cash places all the potential risks and rewards with the acquirer--and sends a strong signal to the markets that it has confidence in the value not only of the deal but in its own stock. By issuing shares, however, an acquirer in essence offers to share the newly merged company with the stockholders of the acquired company--a signal the market often interprets as a lack of confidence in the value of the acquirer's stock. Offering a fixed number of shares reinforces that impression because it requires the selling stockholders to share the risk that the value of the acquirer's stock will decline before the deal goes through. Offering a fixed value of shares sends a more confident signal to the markets, as the acquirer assumes all of that risk. The choice between cash and stock should never be made without full and careful consideration of the potential consequences. The all-too-frequent disappointing returns from stock transactions underscore how important the method of payment truly is.

Preliminary work of mangrove ecosystem carbon stock mapping in small island using remote sensing: above and below ground carbon stock mapping on medium resolution satellite image

NASA Astrophysics Data System (ADS)

Wicaksono, Pramaditya; Danoedoro, Projo; Hartono, Hartono; Nehren, Udo; Ribbe, Lars

2011-11-01

Mangrove forest is an important ecosystem located in coastal area that provides various important ecological and economical services. One of the services provided by mangrove forest is the ability to act as carbon sink by sequestering CO2 from atmosphere through photosynthesis and carbon burial on the sediment. The carbon buried on mangrove sediment may persist for millennia before return to the atmosphere, and thus act as an effective long-term carbon sink. Therefore, it is important to understand the distribution of carbon stored within mangrove forest in a spatial and temporal context. In this paper, an effort to map carbon stocks in mangrove forest is presented using remote sensing technology to overcome the handicap encountered by field survey. In mangrove carbon stock mapping, the use of medium spatial resolution Landsat 7 ETM+ is emphasized. Landsat 7 ETM+ images are relatively cheap, widely available and have large area coverage, and thus provide a cost and time effective way of mapping mangrove carbon stocks. Using field data, two image processing techniques namely Vegetation Index and Linear Spectral Unmixing (LSU) were evaluated to find the best method to explain the variation in mangrove carbon stocks using remote sensing data. In addition, we also tried to estimate mangrove carbon sequestration rate via multitemporal analysis. Finally, the technique which produces significantly better result was used to produce a map of mangrove forest carbon stocks, which is spatially extensive and temporally repetitive.

Rapid carbon loss and slow recovery following permafrost thaw in boreal peatlands

USGS Publications Warehouse

Jones, Miriam C.; Harden, Jennifer W.; O'Donnell, Jonathan A.; Manies, Kristen L.; Jorgenson, Torre; Treat, Claire C.; Ewing, Stephanie

2017-01-01

Permafrost peatlands store one-third of the total carbon (C) in the atmosphere and are increasingly vulnerable to thaw as high-latitude temperatures warm. Large uncertainties remain about C dynamics following permafrost thaw in boreal peatlands. We used a chronosequence approach to measure C stocks in forested permafrost plateaus (forest) and thawed permafrost bogs, ranging in thaw age from young (<10 years) to old (>100 years) from two interior Alaska chronosequences. Permafrost originally aggraded simultaneously with peat accumulation (syngenetic permafrost) at both sites. We found that upon thaw, C loss of the forest peat C is equivalent to ~30% of the initial forest C stock and is directly proportional to the prethaw C stocks. Our model results indicate that permafrost thaw turned these peatlands into net C sources to the atmosphere for a decade following thaw, after which post-thaw bog peat accumulation returned sites to net C sinks. It can take multiple centuries to millennia for a site to recover its prethaw C stocks; the amount of time needed for them to regain their prethaw C stocks is governed by the amount of C that accumulated prior to thaw. Consequently, these findings show that older peatlands will take longer to recover prethaw C stocks, whereas younger peatlands will exceed prethaw stocks in a matter of centuries. We conclude that the loss of sporadic and discontinuous permafrost by 2100 could result in a loss of up to 24 Pg of deep C from permafrost peatlands.

Transfer of risk: "right to sue" legislation and managed care organization stock performance.

PubMed

Weeks, W B; Nells, T; Wallace, A E

2001-01-01

We examined whether Congress's consideration of legislation that gave consumers the right to sue managed care organizations impacted the performance of these companies' stocks relative to that of the market. For each company examined, the total return related to such legislation was negative and substantially lower than that expected from the market model; losses in market value were from 17 percent to 48 percent for individual companies and 22 percent for a capitalization-weighted portfolio. The study suggests that equity markets responded to the proposed legislation quickly and that the impact of proposed legislation is felt through loss of market value and increased corporate risk.

Effects of long memory in the order submission process on the properties of recurrence intervals of large price fluctuations

NASA Astrophysics Data System (ADS)

Meng, Hao; Ren, Fei; Gu, Gao-Feng; Xiong, Xiong; Zhang, Yong-Jie; Zhou, Wei-Xing; Zhang, Wei

2012-05-01

Understanding the statistical properties of recurrence intervals (also termed return intervals in econophysics literature) of extreme events is crucial to risk assessment and management of complex systems. The probability distributions and correlations of recurrence intervals for many systems have been extensively investigated. However, the impacts of microscopic rules of a complex system on the macroscopic properties of its recurrence intervals are less studied. In this letter, we adopt an order-driven stock model to address this issue for stock returns. We find that the distributions of the scaled recurrence intervals of simulated returns have a power-law scaling with stretched exponential cutoff and the intervals possess multifractal nature, which are consistent with empirical results. We further investigate the effects of long memory in the directions (or signs) and relative prices of the order flow on the characteristic quantities of these properties. It is found that the long memory in the order directions (Hurst index Hs) has a negligible effect on the interval distributions and the multifractal nature. In contrast, the power-law exponent of the interval distribution increases linearly with respect to the Hurst index Hx of the relative prices, and the singularity width of the multifractal nature fluctuates around a constant value when Hx<0.7 and then increases with Hx. No evident effects of Hs and Hx are found on the long memory of the recurrence intervals. Our results indicate that the nontrivial properties of the recurrence intervals of returns are mainly caused by traders' behaviors of persistently placing new orders around the best bid and ask prices.

Effect of External Economic-Field Cycle and Market Temperature on Stock-Price Hysteresis: Monte Carlo Simulation on the Ising Spin Model

NASA Astrophysics Data System (ADS)

Punya Jaroenjittichai, Atchara; Laosiritaworn, Yongyut

2017-09-01

In this work, the stock-price versus economic-field hysteresis was investigated. The Ising spin Hamiltonian was utilized as the level of ‘disagreement’ in describing investors’ behaviour. The Ising spin directions were referred to an investor’s intention to perform his action on trading his stock. The periodic economic variation was also considered via the external economic-field in the Ising model. The stochastic Monte Carlo simulation was performed on Ising spins, where the steady-state excess demand and supply as well as the stock-price were extracted via the magnetization. From the results, the economic-field parameters and market temperature were found to have significant effect on the dynamic magnetization and stock-price behaviour. Specifically, the hysteresis changes from asymmetric to symmetric loops with increasing market temperature and economic-field strength. However, the hysteresis changes from symmetric to asymmetric loops with increasing the economic-field frequency, when either temperature or economic-field strength is large enough, and returns to symmetric shape at very high frequencies. This suggests competitive effects among field and temperature factors on the hysteresis characteristic, implying multi-dimensional complicated non-trivial relationship among inputs-outputs. As is seen, the results reported (over extensive range) can be used as basis/guideline for further analysis/quantifying how economic-field and market-temperature affect the stock-price distribution on the course of economic cycle.

Multiscale volatility duration characteristics on financial multi-continuum percolation dynamics

NASA Astrophysics Data System (ADS)

Wang, Min; Wang, Jun

A random stock price model based on the multi-continuum percolation system is developed to investigate the nonlinear dynamics of stock price volatility duration, in an attempt to explain various statistical facts found in financial data, and have a deeper understanding of mechanisms in the financial market. The continuum percolation system is usually referred to be a random coverage process or a Boolean model, it is a member of a class of statistical physics systems. In this paper, the multi-continuum percolation (with different values of radius) is employed to model and reproduce the dispersal of information among the investors. To testify the rationality of the proposed model, the nonlinear analyses of return volatility duration series are preformed by multifractal detrending moving average analysis and Zipf analysis. The comparison empirical results indicate the similar nonlinear behaviors for the proposed model and the actual Chinese stock market.

Changes of hierarchical network in local and world stock market

NASA Astrophysics Data System (ADS)

Patwary, Enayet Ullah; Lee, Jong Youl; Nobi, Ashadun; Kim, Doo Hwan; Lee, Jae Woo

2017-10-01

We consider the cross-correlation coefficients of the daily returns in the local and global stock markets. We generate the minimal spanning tree (MST) using the correlation matrix. We observe that the MSTs change their structure from chain-like networks to star-like networks during periods of market uncertainty. We quantify the measure of the hierarchical network utilizing the value of the hierarchy measured by the hierarchical path. The hierarchy and betweenness centrality characterize the state of the market regarding the impact of crises. During crises, the non-financial company is established as the central node of the MST. However, before the crisis and during stable periods, the financial company is occupying the central node of the MST in the Korean and the U.S. stock markets. The changes in the network structure and the central node are good indicators of an upcoming crisis.

Effect of intravaginal clindamycin cream on pregnancy outcome and on abnormal vaginal microbial flora of pregnant women.

PubMed Central

Rosenstein, I J; Morgan, D J; Lamont, R F; Sheehan, M; Doré, C J; Hay, P E; Taylor-Robinson, D

2000-01-01

OBJECTIVES: To determine whether intravaginal clindamycin cream reduces the incidence of abnormal pregnancy outcome in women with abnormal vaginal microbial flora graded as intermediate or BV and to investigate the effect of the antibiotic on vaginal microbial flora. METHODS: A prospective cohort study of pregnant women in an antenatal clinic of a district general hospital. The subjects were 268 women who had abnormal vaginal microbial flora at first clinic visit by examination of a Gram-stained vaginal smear and 34 women with a normal vaginal flora. Two hundred and thirty-seven women were evaluable. Women with abnormal Gram-stained smears (graded as II or III) on clinic recall were randomised to receive treatment (intravaginal clindamycin cream) or placebo and followed to assess outcome of pregnancy, vaginal flora, and detection of Mycoplasma hominis and Ureaplasma urealyticum after treatment. RESULTS: Abnormal outcomes of pregnancy were not significantly different in treated and placebo groups by Chi square (P = 0.2). However, women with grade III flora responded better to clindamycin than women with grade II flora by numbers of abnormal outcomes (P = 0.03) and return to normal vaginal flora (P = 0.01) (logistic regression analysis model). This may be due to differences in vaginal bacterial species in these grades. Women whose abnormal vaginal flora had spontaneously returned to normal on follow-up and were therefore not treated (revertants) had as many abnormal outcomes as placebos suggesting that damage by abnormal bacterial species occurred early in pregnancy. CONCLUSIONS: Gram-stain screening distinguishing grade II from grade III flora may be helpful in prescribing treatment other than clindamycin for women with grade II flora. Earlier diagnosis and treatment may be more effective in preventing an abnormal outcome, possibly as soon as pregnancy is diagnosed or even offered as a pre-conception screen. PMID:10968599

Structural changes in the minimal spanning tree and the hierarchical network in the Korean stock market around the global financial crisis

NASA Astrophysics Data System (ADS)

Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo

2015-04-01

This paper considers stock prices in the Korean stock market during the 2008 global financial crisis by focusing on three time periods: before, during, and after the crisis. Complex networks are extracted from cross-correlation coefficients between the normalized logarithmic return of the stock price time series of firms. The minimal spanning trees (MSTs) and the hierarchical network (HN) are generated from cross-correlation coefficients. Before and after the crisis, securities firms are located at the center of the MST. During the crisis, however, the center of the MST changes to a firm in heavy industry and construction. During the crisis, the MST shrinks in comparison to that before and that after the crisis. This topological change in the MST during the crisis reflects a distinct effect of the global financial crisis. The cophenetic correlation coefficient increases during the crisis, indicating an increase in the hierarchical structure during in this period. When crisis hits the market, firms behave synchronously, and their correlations are higher than those during a normal period.

An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

NASA Astrophysics Data System (ADS)

Hsu, Chih-Ming

2014-12-01

Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

41 CFR 101-27.506 - Determination of acceptability for credit.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-INVENTORY MANAGEMENT 27.5-Return of GSA Stock Items § 101-27.506 Determination of acceptability for credit... 41 Public Contracts and Property Management 2 2010-07-01 2010-07-01 true Determination of acceptability for credit. 101-27.506 Section 101-27.506 Public Contracts and Property Management Federal...

41 CFR 101-27.500 - Scope and applicability of subpart.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MANAGEMENT 27.5-Return of GSA Stock Items § 101-27.500 Scope and applicability of subpart. This subpart sets... 41 Public Contracts and Property Management 2 2010-07-01 2010-07-01 true Scope and applicability of subpart. 101-27.500 Section 101-27.500 Public Contracts and Property Management Federal Property...

77 FR 64768 - Regulations Regarding the Application of Section 172(h) Including Consolidated Groups; Correction

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-23

... treatment of multiple step plans for the acquisition of stock and CERTs involving members of a consolidated... language ``Service, 1111 Constitution Avenue NW.,'' is corrected to read ``Service, 1111 Constitution... from the bottom of the page, the language ``return group; (4) application of these'' is corrected to...

76 FR 40774 - Proposed Collection; Comment Request for Form 8621

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-11

... 8621, Return by a Shareholder of a Passive Foreign Investment Company or Qualified Electing Fund. DATES... Passive Foreign Investment Company or Qualified Electing Fund. OMB Number: 1545-1002. Form Number: 8621. Abstract: Form 8621 is filed by a U.S. shareholder who owns stock in a foreign investment company. The form...

26 CFR 1.852-7 - Additional information required in returns of shareholders.

Code of Federal Regulations, 2010 CFR

2010-04-01

... (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES Regulated Investment Companies and Real Estate Investment... refuses to comply with the demand of a regulated investment company for the written statements which § 1... claiming to be a regulated investment company; (b) The dates of acquisition of any such stock during such...

26 CFR 1.355-5 - Records to be kept and information to be filed.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Records to be kept and information to be filed. (a) Distributing corporation—(1) In general. Every corporation that makes a distribution (the distributing corporation) of stock or securities of a controlled... (IF ANY) OF TAXPAYER], A DISTRIBUTING CORPORATION,” on or with its return for the year of the...

Promoting Student Success: What SHEEOs and System Heads Can Do. Occasional Paper No. 14

ERIC Educational Resources Information Center

Ewell, Peter T.

2005-01-01

States benefit considerably when their stocks of "educational capital" grow. From a workforce and tax revenue standpoint, state rates of return on baccalaureate education are far higher than those associated with any other educational step. Additional benefits attributable to higher education--ranging from enhancements in citizen participation…

Lunar Analog

NASA Technical Reports Server (NTRS)

Cromwell, Ronita L.

2009-01-01

In this viewgraph presentation, a ground-based lunar analog is developed for the return of manned space flight to the Moon. The contents include: 1) Digital Astronaut; 2) Bed Design; 3) Lunar Analog Feasibility Study; 4) Preliminary Data; 5) Pre-pilot Study; 6) Selection of Stockings; 7) Lunar Analog Pilot Study; 8) Bed Design for Lunar Analog Pilot.

Linking market interaction intensity of 3D Ising type financial model with market volatility

NASA Astrophysics Data System (ADS)

Fang, Wen; Ke, Jinchuan; Wang, Jun; Feng, Ling

2016-11-01

Microscopic interaction models in physics have been used to investigate the complex phenomena of economic systems. The simple interactions involved can lead to complex behaviors and help the understanding of mechanisms in the financial market at a systemic level. This article aims to develop a financial time series model through 3D (three-dimensional) Ising dynamic system which is widely used as an interacting spins model to explain the ferromagnetism in physics. Through Monte Carlo simulations of the financial model and numerical analysis for both the simulation return time series and historical return data of Hushen 300 (HS300) index in Chinese stock market, we show that despite its simplicity, this model displays stylized facts similar to that seen in real financial market. We demonstrate a possible underlying link between volatility fluctuations of real stock market and the change in interaction strengths of market participants in the financial model. In particular, our stochastic interaction strength in our model demonstrates that the real market may be consistently operating near the critical point of the system.

Quantitative relations between risk, return and firm size

NASA Astrophysics Data System (ADS)

Podobnik, B.; Horvatic, D.; Petersen, A. M.; Stanley, H. E.

2009-03-01

We analyze —for a large set of stocks comprising four financial indices— the annual logarithmic growth rate R and the firm size, quantified by the market capitalization MC. For the Nasdaq Composite and the New York Stock Exchange Composite we find that the probability density functions of growth rates are Laplace ones in the broad central region, where the standard deviation σ(R), as a measure of risk, decreases with the MC as a power law σ(R)~(MC)- β. For both the Nasdaq Composite and the S&P 500, we find that the average growth rate langRrang decreases faster than σ(R) with MC, implying that the return-to-risk ratio langRrang/σ(R) also decreases with MC. For the S&P 500, langRrang and langRrang/σ(R) also follow power laws. For a 20-year time horizon, for the Nasdaq Composite we find that σ(R) vs. MC exhibits a functional form called a volatility smile, while for the NYSE Composite, we find power law stability between σ(r) and MC.

Juvenile Chinook Salmon abundance in the northern Bering Sea: Implications for future returns and fisheries in the Yukon River

NASA Astrophysics Data System (ADS)

Murphy, James M.; Howard, Kathrine G.; Gann, Jeanette C.; Cieciel, Kristin C.; Templin, William D.; Guthrie, Charles M.

2017-01-01

Juvenile Chinook Salmon (Oncorhynchus tshawytscha) abundance in the northern Bering Sea is used to provide insight into future returns and fisheries in the Yukon River. The status of Yukon River Chinook Salmon is of concern due to recent production declines and subsequent closures of commercial, sport, and personal use fisheries, and severe restrictions on subsistence fisheries in the Yukon River. Surface trawl catch data, mixed layer depth adjustments, and genetic stock mixtures are used to estimate juvenile abundance for the Canadian-origin stock group from the Yukon River. Abundance ranged from a low of 0.62 million in 2012 to a high of 2.58 million in 2013 with an overall average of 1.5 million from 2003 to 2015. Although abundance estimates indicate that average survival is relatively low (average of 5.2%), juvenile abundance was significantly correlated (r=0.87, p=0.005) with adult returns, indicating that much of the variability in survival occurs during early life-history stages (freshwater and initial marine). Juvenile abundance in the northern Bering Sea has increased since 2013 due to an increase in early life-history survival (average juveniles-per-spawner increased from 29 to 59). The increase in juvenile abundance is projected to produce larger runs and increased subsistence fishing opportunities for Chinook Salmon in the Yukon River as early as 2016.

Financial Stylized Facts in the Word of Mouth Model

NASA Astrophysics Data System (ADS)

Misawa, Tadanobu; Watanabe, Kyoko; Shimokawa, Tetsuya

Recently, we proposed an agent-based model called the word of mouth model to analyze the influence of an information transmission process to price formation in financial markets. Especially, the short-term predictability of asset return was focused on and an explanation in the view of information transmission was provided to the question why the predictability was much clearly observed in the small-sized stocks. This paper, to extend the previous study, demonstrates that the word of mouth model also has a consistency with other important financial stylized facts. This strengthens the possibility that the information transmission among investors plays a crucial role in price formation. Concretely, this paper addresses two famous statistical features of returns; the leptokurtic distribution of return and the autocorrelation of return volatility. The reasons why these statistical facts receive especial attentions of researchers among financial stylized facts are their statistical robustness and practical importance, such as the applications to the derivative pricing problems.

Scalability of a Methodology for Generating Technical Trading Rules with GAPs Based on Risk-Return Adjustment and Incremental Training

NASA Astrophysics Data System (ADS)

de La Cal, E. A.; Fernández, E. M.; Quiroga, R.; Villar, J. R.; Sedano, J.

In previous works a methodology was defined, based on the design of a genetic algorithm GAP and an incremental training technique adapted to the learning of series of stock market values. The GAP technique consists in a fusion of GP and GA. The GAP algorithm implements the automatic search for crisp trading rules taking as objectives of the training both the optimization of the return obtained and the minimization of the assumed risk. Applying the proposed methodology, rules have been obtained for a period of eight years of the S&P500 index. The achieved adjustment of the relation return-risk has generated rules with returns very superior in the testing period to those obtained applying habitual methodologies and even clearly superior to Buy&Hold. This work probes that the proposed methodology is valid for different assets in a different market than previous work.

Probability distribution of extreme share returns in Malaysia

NASA Astrophysics Data System (ADS)

Zin, Wan Zawiah Wan; Safari, Muhammad Aslam Mohd; Jaaman, Saiful Hafizah; Yie, Wendy Ling Shin

2014-09-01

The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.

Statistical regularities in the return intervals of volatility

NASA Astrophysics Data System (ADS)

Wang, F.; Weber, P.; Yamasaki, K.; Havlin, S.; Stanley, H. E.

2007-01-01

We discuss recent results concerning statistical regularities in the return intervals of volatility in financial markets. In particular, we show how the analysis of volatility return intervals, defined as the time between two volatilities larger than a given threshold, can help to get a better understanding of the behavior of financial time series. We find scaling in the distribution of return intervals for thresholds ranging over a factor of 25, from 0.6 to 15 standard deviations, and also for various time windows from one minute up to 390 min (an entire trading day). Moreover, these results are universal for different stocks, commodities, interest rates as well as currencies. We also analyze the memory in the return intervals which relates to the memory in the volatility and find two scaling regimes, ℓ<ℓ* with α1=0.64±0.02 and ℓ> ℓ* with α2=0.92±0.04; these exponent values are similar to results of Liu et al. for the volatility. As an application, we use the scaling and memory properties of the return intervals to suggest a possibly useful method for estimating risk.

To stock or not to stock? Assessing restoration potential of a remnant American shad spawning run with hatchery supplementation

USGS Publications Warehouse

Bailey, Michael M.; Zydlewski, Joseph D.

2013-01-01

Hatchery supplementation has been widely used as a restoration technique for American Shad Alosa sapidissima on the East Coast of the USA, but results have been equivocal. In the Penobscot River, Maine, dam removals and other improvements to fish passage will likely reestablish access to the majority of this species’ historic spawning habitat. Additional efforts being considered include the stocking of larval American Shad. The decision about whether to stock a river system undergoing restoration should be made after evaluating the probability of natural recolonization and examining the costs and benefits of potentially accelerating recovery using a stocking program. However, appropriate evaluation can be confounded by a dearth of information about the starting population size and age structure of the remnant American Shad spawning run in the river. We used the Penobscot River as a case study to assess the theoretical sensitivity of recovery time to either scenario (stocking or not) by building a deterministic model of an American Shad population. This model is based on the best available estimates of size at age, fecundity, rate of iteroparity, and recruitment. Density dependence was imposed, such that the population reached a plateau at an arbitrary recovery goal of 633,000 spawning adults. Stocking had a strong accelerating effect on the time to modeled recovery (as measured by the time to reach 50% of the recovery goal) in the base model, but stocking had diminishing effects with larger population sizes. There is a diminishing return to stocking when the starting population is modestly increased. With a low starting population (a spawning run of 1,000), supplementation with 12 million larvae annually accelerated modeled recovery by 12 years. Only a 2-year acceleration was observed if the starting population was 15,000. Such a heuristic model may aid managers in assessing the costs and benefits of stocking by incorporating a structured decision framework.

The impact of expatriates directors on the Indonesian company’s performance

NASA Astrophysics Data System (ADS)

Ronyastra, I. M.

2017-11-01

This research examined the impact of employing expatriates as board of directors (BOD) to the financial performance of Indonesian companies. Using samples from Kompas 100 index in Indonesian Stock Exchange, the research performed analyses on three performance indicators i.e. Return on Asset (ROA), Return on Equity (ROE), and Tobin’s Q. Binary variable of whether a company employing expatriate and the proportion of expatriate in the BOD were used as the proxy for the independent variable. The research did not find enough evidence to support the hypothesis that employing expatriate in the BOD would make the financial performance different.

Multifractal analysis of the Korean agricultural market

NASA Astrophysics Data System (ADS)

Kim, Hongseok; Oh, Gabjin; Kim, Seunghwan

2011-11-01

We have studied the long-term memory effects of the Korean agricultural market using the detrended fluctuation analysis (DFA) method. In general, the return time series of various financial data, including stock indices, foreign exchange rates, and commodity prices, are uncorrelated in time, while the volatility time series are strongly correlated. However, we found that the return time series of Korean agricultural commodity prices are anti-correlated in time, while the volatility time series are correlated. The n-point correlations of time series were also examined, and it was found that a multifractal structure exists in Korean agricultural market prices.

Femoroacetabular Impingement in Professional Football Players: Return to Play and Predictors of Career Length After Hip Arthroscopy.

PubMed

Menge, Travis J; Bhatia, Sanjeev; McNamara, Shannen C; Briggs, Karen K; Philippon, Marc J

2017-07-01

Previous studies have shown hip arthroscopy to be a highly effective treatment for symptomatic femoroacetabular impingement (FAI) in a wide range of athletes; however, the rate of return to play and length of career after hip arthroscopy in professional football players are unknown. To determine how many athletes returned to professional football and the number of seasons they played after surgery. Case series; Level of evidence, 4. Fifty-one professional football players (60 hips) underwent hip arthroscopy for FAI between 2000 and 2014 by a single surgeon. Return to play was defined as competing in a preseason or regular season professional football game after surgery. Data were retrospectively obtained for each player from NFL.com , ESPN.com , individual team websites, and/or CFL.ca . We found that 87% (52/60) of the arthroscopic procedures allowed professional football players to return to play in a preseason or regular season game. Athletes who returned played an average of 38 games during 3.2 seasons after arthroscopy, with an average total career length of 7.4 seasons. Ninety-two percent (48/52) of players who returned had a minimum total career length of 3 years. When participants were analyzed by position, linemen were less likely to return after hip arthroscopy compared with other players (odds ratio 5.6; 95% CI, 1.1-35; P = .04). All quarterbacks and tight ends returned to play after surgery. No significant difference in return to play rate was found between athletes who underwent microfracture and those who did not (25% vs 38%, P = .698). Hip arthroscopy for treatment of FAI and associated pathologic abnormalities in professional football players resulted in a high rate of return to play. The study's findings demonstrate that 87% of the arthroscopic procedures allowed professional football players to return to play, linemen were less likely to return compared with other positions, and the presence of microfracture did not significantly affect the return to play rate. These findings support hip arthroscopy as an effective procedure to treat FAI and related pathologic abnormalities in the professional football player, and this information is important for proper counseling of athletes with FAI.

Significant clinical practice cost savings through downsizing office supply inventory and just in time ordering.

PubMed

Gonzalez, Chris M; Jang, Tom; Raines, Melanie; Lys, Thomas Z; Schaeffer, Anthony J

2006-07-01

Cost containment in the office is becoming more important secondary to increasing overhead costs and lower reimbursement. In an attempt to limit these particular expenditures we analyzed and restructured our methods of ordering, storing and distributing office supply inventory. In a large academic practice with 11 urologists and approximately 20,000 annual patient visits an attempt was made to decrease overhead costs using the principle of just in time inventory popularized by large manufacturing companies. We initially issued a return of excess and/or unused supplies from our office inventory stock room. Our main supply room was then centralized to contain office supplies for up to 4 weeks. The 12 individual clinic rooms were stocked with appropriate supplies to last 1 week. Limited access to the main supply room was established and a supply manager was established to log all input and output. The initial credit for the return of unused/overstocked supplies was $10,107 in January 2004. Annual office supply charges in calendar year 2004 were $87,444 compared to charges in calendar year 2003 of $175,340. No stock outs occurred during year 2004 and all standing delivery orders were terminated. The total number of patient visits in calendar year 2004 was 20,170 compared to 19,455 in calendar year 2003. Decreasing overall inventory through accurate demand forecasting, judicious accounting, office supply centralization and just in time ordering is a potential area for significant overhead cost savings in a clinical practice.

Comparative study on DuPont analysis and DEA models for measuring stock performance using financial ratio

NASA Astrophysics Data System (ADS)

Arsad, Roslah; Shaari, Siti Nabilah Mohd; Isa, Zaidi

2017-11-01

Determining stock performance using financial ratio is challenging for many investors and researchers. Financial ratio can indicate the strengths and weaknesses of a company's stock performance. There are five categories of financial ratios namely liquidity, efficiency, leverage, profitability and market ratios. It is important to interpret the ratio correctly for proper financial decision making. The purpose of this study is to compare the performance of listed companies in Bursa Malaysia using Data Envelopment Analysis (DEA) and DuPont analysis Models. The study is conducted in 2015 involving 116 consumer products companies listed in Bursa Malaysia. The estimation method of Data Envelopment Analysis computes the efficiency scores and ranks the companies accordingly. The Alirezaee and Afsharian's method of analysis based Charnes, Cooper and Rhodes (CCR) where Constant Return to Scale (CRS) is employed. The DuPont analysis is a traditional tool for measuring the operating performance of companies. In this study, DuPont analysis is used to evaluate three different aspects such as profitability, efficiency of assets utilization and financial leverage. Return on Equity (ROE) is also calculated in DuPont analysis. This study finds that both analysis models provide different rankings of the selected samples. Hypothesis testing based on Pearson's correlation, indicates that there is no correlation between rankings produced by DEA and DuPont analysis. The DEA ranking model proposed by Alirezaee and Asharian is unstable. The method cannot provide complete ranking because the values of Balance Index is equal and zero.

Effect of mature body weight and stocking rate on cow and calf performance, cow herd efficiency, and economics in the southeastern United States.

PubMed

Beck, P A; Stewart, C B; Gadberry, M S; Haque, M; Biermacher, J

2016-04-01

Eight 4-ha mixed warm-season grass pastures in southwestern Arkansas (33°40'4″ N, 93°35'24″ W, and elevation 107 m) were stocked with either large mature size (571 kg [SD 55.2] BW) or small mature size (463 kg [SD 58.2] BW) spring-calving cows at 4 stocking rates (SR; 1, 1.5, 2, or 2.5 cow-calf pairs/ha) over 4 yr to test the effects of SR and mature body size on cow and calf performance and system economics. Each pasture received 112 kg/ha N as ammonium nitrate in May and was broadcast seeded to annual ryegrass ( Lam.) in mid October each fall along with 112 kg/ha N as ammonium nitrate. Data were analyzed by regression to determine the effects of cow size and SR on calf performance, cow BW change, calf gain, weaning weight per hectare, hay feeding requirements, and net returns. As SR increased, cow BW and BCS at weaning decreased ( < 0.01) by 26 kg and 0.36 condition scores, respectively, for each additional cow stocked per hectare ( = 0.44). Calf BW at weaning in October increased ( < 0.01) 19 kg for each 100-kg increase in cow BW but was not affected ( = 0.66) by SR. As cow BW increased, calf BW at weaning per 100 kg cow BW decreased ( < 0.01) 6.7 kg for each 100-kg increase in cow BW but was not affected ( = 0.44) by SR. Neither cow BW nor SR affected ( ≥ 0.53) pregnancy percentage, which averaged 88% over the 4-yr experiment. Calf BW weaned per hectare was not affected ( = 0.75) by cow BW but linearly increased ( < 0.01) by 217 kg for each additional cow per hectare SR. Hay feeding days and cost of hay per cow increased ( ≤ 0.05) and kilograms of hay offered per cow tended ( = 0.09) to linearly increase with increasing SR, yet cow BW had no effects ( > 0.22). Although there were no effects ( ≥ 0.38) of cow BW on carrying cost or net returns, increasing SR decreased ( < 0.01) total expenses by US$102/cow and increased net returns by $70/cow and $438/ha for each cow per hectare increase in SR. These data indicate that increasing cow size can increase weaning BW of calves but does not affect total production per hectare or profitability, even though weaning weight efficiency ratios were reduced. Increasing SR reduced cow BW and BCS at weaning and increased feeding of conserved forages but did not affect pregnancy rates and led to increases in total calf BW weaned per hectare and net returns.

Rapid carbon loss and slow recovery following permafrost thaw in boreal peatlands.

PubMed

Jones, Miriam C; Harden, Jennifer; O'Donnell, Jonathan; Manies, Kristen; Jorgenson, Torre; Treat, Claire; Ewing, Stephanie

2017-03-01

Permafrost peatlands store one-third of the total carbon (C) in the atmosphere and are increasingly vulnerable to thaw as high-latitude temperatures warm. Large uncertainties remain about C dynamics following permafrost thaw in boreal peatlands. We used a chronosequence approach to measure C stocks in forested permafrost plateaus (forest) and thawed permafrost bogs, ranging in thaw age from young (<10 years) to old (>100 years) from two interior Alaska chronosequences. Permafrost originally aggraded simultaneously with peat accumulation (syngenetic permafrost) at both sites. We found that upon thaw, C loss of the forest peat C is equivalent to ~30% of the initial forest C stock and is directly proportional to the prethaw C stocks. Our model results indicate that permafrost thaw turned these peatlands into net C sources to the atmosphere for a decade following thaw, after which post-thaw bog peat accumulation returned sites to net C sinks. It can take multiple centuries to millennia for a site to recover its prethaw C stocks; the amount of time needed for them to regain their prethaw C stocks is governed by the amount of C that accumulated prior to thaw. Consequently, these findings show that older peatlands will take longer to recover prethaw C stocks, whereas younger peatlands will exceed prethaw stocks in a matter of centuries. We conclude that the loss of sporadic and discontinuous permafrost by 2100 could result in a loss of up to 24 Pg of deep C from permafrost peatlands. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

The Forsyth County Cervical Cancer Prevention Project--II. Compliance with screening follow-up of abnormal cervical smears.

PubMed

Michielutte, R; Dignan, M; Bahnson, J; Wells, H B

1994-12-01

The Forsyth County Cervical Cancer Prevention Project was a community-wide cancer education program to address the problem of cervical cancer incidence and mortality among minority women in Forsyth County, North Carolina. This paper reports program results with regard to increasing compliance with follow-up for abnormal cervical smears. An analysis of trends prior to and after implementation of the educational program was conducted in one private and two public health primary care clinics to provide an assessment of impact of the project in improving compliance with follow-up among black women. A similar analysis also was conducted for white women. The results of medical record reviews of follow-up procedures for 878 abnormal cervical smears suggested a modest program effect among black women. The percentage of black women who returned for follow-up and treatment of an abnormal cervical smear significantly increased during the time the program was in effect. The trend analysis further indicated that the decline did not begin prior to the intervention period and was maintained throughout the duration of the intervention. No significant change in the percentage who returned for follow-up was found for white women.

A new enhanced index tracking model in portfolio optimization with sum weighted approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

The behaviour of share returns of football clubs: An econophysics approach

NASA Astrophysics Data System (ADS)

Ferreira, Paulo; Loures, Luís; Nunes, José Rato; Dionísio, Andreia

2017-04-01

Football is a sport that moves thousands of people and millions of euros. Since 1983, several clubs entered the stock markets with shares, and now twenty two clubs are listed in the Stoxx Football Index. In this study, we analyse the behaviour of the return rates of such shares, with Detrended Fluctuation Analysis and Detrended Cross-Correlation Analysis (and its correlation coefficient). With Detrended Fluctuation Analysis, we are able to observe that the shares of several clubs are far from the behaviour of a random walk, which is expected by the theory. Using Detrended Cross-Correlation Analysis, we calculate the cross correlations of clubs' returns with national indexes and then with the Stoxx Football Index. Although almost all of them are positive, they do not seem to be strong.

A normality bias in legal decision making.

PubMed

Prentice, Robert A; Koehler, Jonathan J

2003-03-01

It is important to understand how legal fact finders determine causation and assign blame. However, this process is poorly understood. Among the psychological factors that affect decision makers are an omission bias (a tendency to blame actions more than inactions [omissions] for bad results), and a normality bias (a tendency to react more strongly to bad outcomes that spring from abnormal rather than normal circumstances). The omission and normality biases often reinforce one another when inaction preserves the normal state and when action creates an abnormal state. But what happens when these biases push in opposite directions as they would when inaction promotes an abnormal state or when action promotes a normal state? Which bias exerts the stronger influence on the judgments and behaviors of legal decision makers? The authors address this issue in two controlled experiments. One experiment involves medical malpractice and the other involves stockbroker negligence. They find that jurors pay much more attention to the normality of conditions than to whether those conditions arose through acts or omissions. Defendants who followed a nontraditional medical treatment regime or who chose a nontraditional stock portfolio received more blame and more punishment for bad outcomes than did defendants who obtained equally poor results after recommending a traditional medical regime or a traditional stock portfolio. Whether these recommendations entailed an action or an omission was essentially irrelevant. The Article concludes with a discussion of the implications of a robust normality bias for American jurisprudence.

Portfolio optimization and the random magnet problem

NASA Astrophysics Data System (ADS)

Rosenow, B.; Plerou, V.; Gopikrishnan, P.; Stanley, H. E.

2002-08-01

Diversification of an investment into independently fluctuating assets reduces its risk. In reality, movements of assets are mutually correlated and therefore knowledge of cross-correlations among asset price movements are of great importance. Our results support the possibility that the problem of finding an investment in stocks which exposes invested funds to a minimum level of risk is analogous to the problem of finding the magnetization of a random magnet. The interactions for this "random magnet problem" are given by the cross-correlation matrix C of stock returns. We find that random matrix theory allows us to make an estimate for C which outperforms the standard estimate in terms of constructing an investment which carries a minimum level of risk.

Controlled-risk foreign investment strategy can boost yields.

PubMed

Simms, R A

2000-06-01

Healthcare organizations that have invested in the U.S. stock market have enjoyed high returns in recent years. After such a performance, many investment managers see little reason to investigate overseas markets, believing that the U.S. market will continue to be profitable and economic uncertainties make overseas markets too risky. However, in 1999, markets in Europe, Australia, and the Far East outperformed the S&P 500 for the first time in five years. In addition, signs such as mounting price/earnings ratios may indicate that the U.S. stock market will be less profitable than it has been in recent years. Consequently, investment managers should revisit the idea of international investing.

Modified multidimensional scaling approach to analyze financial markets.

PubMed

Yin, Yi; Shang, Pengjian

2014-06-01

Detrended cross-correlation coefficient (σDCCA) and dynamic time warping (DTW) are introduced as the dissimilarity measures, respectively, while multidimensional scaling (MDS) is employed to translate the dissimilarities between daily price returns of 24 stock markets. We first propose MDS based on σDCCA dissimilarity and MDS based on DTW dissimilarity creatively, while MDS based on Euclidean dissimilarity is also employed to provide a reference for comparisons. We apply these methods in order to further visualize the clustering between stock markets. Moreover, we decide to confront MDS with an alternative visualization method, "Unweighed Average" clustering method, for comparison. The MDS analysis and "Unweighed Average" clustering method are employed based on the same dissimilarity. Through the results, we find that MDS gives us a more intuitive mapping for observing stable or emerging clusters of stock markets with similar behavior, while the MDS analysis based on σDCCA dissimilarity can provide more clear, detailed, and accurate information on the classification of the stock markets than the MDS analysis based on Euclidean dissimilarity. The MDS analysis based on DTW dissimilarity indicates more knowledge about the correlations between stock markets particularly and interestingly. Meanwhile, it reflects more abundant results on the clustering of stock markets and is much more intensive than the MDS analysis based on Euclidean dissimilarity. In addition, the graphs, originated from applying MDS methods based on σDCCA dissimilarity and DTW dissimilarity, may also guide the construction of multivariate econometric models.

Tagging methods for estimating population size and mortality rates of inland striped bass populations

USGS Publications Warehouse

Hightower, Joseph E.; Pollock, Kenneth H.

2013-01-01

Striped bass Morone saxatilis in inland reservoirs play an important role ecologically and in supporting recreational fishing. To manage these populations, biologists need information about abundance and mortality. Abundance estimates can be used to assess the effectiveness of stocking programs that maintain most reservoir striped bass populations. Mortality estimates can indicate the relative impact of fishing versus natural mortality and the need for harvest regulation. The purpose of this chapter is to evaluate tagging studies as a way of obtaining information about abundance and mortality. These approaches can be grouped into three broad categories: tag recapture, tag return, and telemetry. Tag-recapture methods are typically used to estimate population size and other demographic parameters but are often difficult to apply in large systems. A fishing tournament can be an effective way of generating tagging or recapture effort in large systems, compared to using research sampling only. Tag-return methods that rely on angler harvest and catch and release can be used to estimate fishing (F) and natural (M) mortality rates and are a practical approach in large reservoirs. The key to success in tag-return studies is to build in auxiliary studies to estimate short-term tagging mortality, short- and longterm tag loss, reporting rate, and mortality associated with catch and release. F and M can also be estimated using telemetry tags. Advantages of this approach are that angler nonreporting does not bias estimates and fish with transmitters provide useful ecological data. Cost can be a disadvantage of telemetry studies; thus, combining telemetry tags with conventional tag returns in an integrated analysis is often the optimal approach. In summary, tagging methods can be a powerful tool for assessing the effectiveness of inland striped bass stocking programs and the relative impact of fishing versus natural mortality

26 CFR 1.1502-19 - Excess loss accounts.

Code of Federal Regulations, 2010 CFR

2010-04-01

... purpose contrary to the purposes of this section, to avoid the effect of the rules of this section or apply the rules of this section to avoid the effect of any other provision of the consolidated return... consolidated taxable income M's negative adjustments with respect to S's stock (e.g., under § 1.1502-32 from S...

Lumber recovery from small-diameter ponderosa pine from Flagstaff, Arizona

Treesearch

Eini C. Lowell; David W. Green

2001-01-01

Thousands of acres of densely stocked ponderosa pine forests surround Flagstaff, AZ. These stands are at high risk of fire, insect, and disease outbreak. Stand density management activity can be expensive, but product recovery from the thinned material could help defray removal costs. This project evaluated the yield and economic return of lumber recovered from small-...

77 FR 38347 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-27

... Component of the Alpha Pair. To calculate the daily total return today of a Target Component or a Benchmark... Benchmark Component, respectively, would be subtracted from today's closing market price for the Target...''). The Price Difference would be added to any declared dividend, if today were an ``ex-dividend'' date...

26 CFR 1.857-9 - Information required in returns of shareholders.

Code of Federal Regulations, 2012 CFR

2012-04-01

... (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES (CONTINUED) Real Estate Investment Trusts § 1.857-9... a real estate investment trust the written statements required under § 1.857-8 to be demanded by... holding shares of stock in any trust claiming to be a real estate investment trust who is not the actual...

26 CFR 1.857-9 - Information required in returns of shareholders.

Code of Federal Regulations, 2011 CFR

2011-04-01

... (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES (CONTINUED) Real Estate Investment Trusts § 1.857-9... a real estate investment trust the written statements required under § 1.857-8 to be demanded by... holding shares of stock in any trust claiming to be a real estate investment trust who is not the actual...

26 CFR 1.857-9 - Information required in returns of shareholders.

Code of Federal Regulations, 2010 CFR

2010-04-01

... (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES Real Estate Investment Trusts § 1.857-9 Information required... any trust claiming to be a real estate investment trust who is not the actual owner of such stock, the... estate investment trust the written statements required under § 1.857-8 to be demanded by such trust from...

26 CFR 1.857-9 - Information required in returns of shareholders.

Code of Federal Regulations, 2013 CFR

2013-04-01

... (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES (CONTINUED) Real Estate Investment Trusts § 1.857-9... a real estate investment trust the written statements required under § 1.857-8 to be demanded by... holding shares of stock in any trust claiming to be a real estate investment trust who is not the actual...

26 CFR 1.857-9 - Information required in returns of shareholders.

Code of Federal Regulations, 2014 CFR

2014-04-01

... (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES (CONTINUED) Real Estate Investment Trusts § 1.857-9... a real estate investment trust the written statements required under § 1.857-8 to be demanded by... holding shares of stock in any trust claiming to be a real estate investment trust who is not the actual...

Intermediate Term Forecasting Techniques for Management.

DTIC Science & Technology

1984-06-01

of Market Efficiency", Chiras and ranaster (1978) used actual option prices to calculate implied variances of future stock returns. They found a...of F*nance, v. 2 5 , p p . 6 5 -8 1 , M a r c h 1 9 1 0 .- .... . . . 23. Chiras D. P. and Nanaster, S., "The Infcrmation Content of Otion Prices and

Simulating Timber and Deer Food Potential In Loblolly Pine Plantations

Treesearch

Clifford A. Myers

1977-01-01

This computer program analyzes both timber and deer food production on managed forests, providing estimates of the number of acres required per deer for each week or month, yearly timber cuts, and current timber growing stock, as well as a cost and return analysis of the timber operation. Input variables include stand descriptors, controls on management, stumpage...

26 CFR 1.368-3 - Records to be kept and information to be filed with returns.

Code of Federal Regulations, 2010 CFR

2010-04-01

... such parties; (2) The date of the reorganization; (3) The aggregate fair market value and basis, determined immediately before the exchange, of the assets, stock or securities of the target corporation... all of the parties to the reorganization; (2) The date of the reorganization; and (3) The fair market...

Probability of Regenerating a Normal Limb After Bite Injury in the Mexican Axolotl (Ambystoma mexicanum).

PubMed

Thompson, Sierra; Muzinic, Laura; Muzinic, Christopher; Niemiller, Matthew L; Voss, S Randal

2014-06-01

Multiple factors are thought to cause limb abnormalities in amphibian populations by altering processes of limb development and regeneration. We examined adult and juvenile axolotls ( Ambystoma mexicanum ) in the Ambystoma Genetic Stock Center (AGSC) for limb and digit abnormalities to investigate the probability of normal regeneration after bite injury. We observed that 80% of larval salamanders show evidence of bite injury at the time of transition from group housing to solitary housing. Among 717 adult axolotls that were surveyed, which included solitary-housed males and group-housed females, approximately half presented abnormalities, including examples of extra or missing digits and limbs, fused digits, and digits growing from atypical anatomical positions. Bite injury likely explains these limb defects, and not abnormal development, because limbs with normal anatomy regenerated after performing rostral amputations. We infer that only 43% of AGSC larvae will present four anatomically normal looking adult limbs after incurring a bite injury. Our results show regeneration of normal limb anatomy to be less than perfect after bite injury.

Side-scan sonar mapping of lake trout spawning habitat in northern Lake Michigan

USGS Publications Warehouse

Edsall, Thomas A.; Poe, Thomas P.; Nester, Robert T.; Brown, Charles L.

1989-01-01

Native stocks of lake trout Salvelinus namaycush were virtually or completely extirpated from the lower four Great Lakes by the early 1960s. The failure of early attempts to reestablish self-sustaining populations of lake trout was attributed partly to the practice of stocking hatcheryreared juveniles at locations and over substrates that had not been used in the past for spawning by native fish. Subsequent attempts to improve the selection of stocking locations were impeded by the lack of reliable information on the distribution of substrates on historical spawning grounds. Here we demonstrate the potential of side-scan sonar to substantially expand the data base needed to pinpoint the location of substrates where lake trout eggs, fry, or juveniles could be stocked to maximize survival and help ensure that survivors returning to spawn would encounter suitable substrates. We also describe the substrates and bathymetry of large areas on historical lake trout spawning grounds in the Fox Island Lake Trout Sanctuary in northern Lake Michigan. These areas could be used to support a contemporary self-sustaining lake trout population in the sanctuary and perhaps also in adjacent waters.

Extraction of phase information in daily stock prices

NASA Astrophysics Data System (ADS)

Fujiwara, Yoshi; Maekawa, Satoshi

2000-06-01

It is known that, in an intermediate time-scale such as days, stock market fluctuations possess several statistical properties that are common to different markets. Namely, logarithmic returns of an asset price have (i) truncated Pareto-Lévy distribution, (ii) vanishing linear correlation, (iii) volatility clustering and its power-law autocorrelation. The fact (ii) is a consequence of nonexistence of arbitragers with simple strategies, but this does not mean statistical independence of market fluctuations. Little attention has been paid to temporal structure of higher-order statistics, although it contains some important information on market dynamics. We applied a signal separation technique, called Independent Component Analysis (ICA), to actual data of daily stock prices in Tokyo and New York Stock Exchange (TSE/NYSE). ICA does a linear transformation of lag vectors from time-series to find independent components by a nonlinear algorithm. We obtained a similar impulse response for these dataset. If it were a Martingale process, it can be shown that impulse response should be a delta-function under a few conditions that could be numerically checked and as was verified by surrogate data. This result would provide information on the market dynamics including speculative bubbles and arbitrating processes. .

Predicted effects of prescribed burning and harvesting on forest recovery and sustainability in southwest Georgia, USA.

PubMed

Garten, Charles T

2006-12-01

A model-based analysis of the effect of prescribed burning and forest thinning or clear-cutting on stand recovery and sustainability was conducted at Fort Benning, GA, in the southeastern USA. Two experiments were performed with the model. In the first experiment, forest recovery from degraded soils was predicted for 100 years with or without prescribed burning. In the second experiment simulations began with 100 years of predicted stand growth, then forest sustainability was predicted for an additional 100 years under different combinations of prescribed burning and forest harvesting. Three levels of fire intensity (low, medium, and high), that corresponded to 17%, 33%, and 50% consumption of the forest floor C stock by fire, were evaluated at 1-, 2-, and 3-year fire return intervals. Relative to the control (no fire), prescribed burning with a 2- or 3-year return interval caused only a small reduction in predicted steady state soil C stocks (< or =25%) and had no effect on steady state tree wood biomass, regardless of fire intensity. Annual high intensity burns did adversely impact forest recovery and sustainability (after harvesting) on less sandy soils, but not on more sandy soils that had greater N availability. Higher intensity and frequency of ground fires increased the chance that tree biomass would not return to pre-harvest levels. Soil N limitation was indicated as the cause of unsustainable forests when prescribed burns were too frequent or too intense to permit stand recovery.

Issues in assessing the contribution of research and development to productivity growth

NASA Technical Reports Server (NTRS)

Griliches, Z.

1979-01-01

The article outlines the production function approach to the estimation of the returns to R&D and then proceeds to discuss in turn two very difficult problems: the measurement of output in R&D intensive industries and the definition and measurement of the stock of R&D 'capital'. Multicollinearity and simultaneity are taken up in the next section and another section is devoted to estimation and inference problems arising more specifically in the R&D context. Several recent studies of returns to R&D are then surveyed, and the paper concludes with suggestions for ways of expanding the current data base in this field.

Stock and option portfolio using fuzzy logic approach

NASA Astrophysics Data System (ADS)

Sumarti, Novriana; Wahyudi, Nanang

2014-03-01

Fuzzy Logic in decision-making process has been widely implemented in various problems in industries. It is the theory of imprecision and uncertainty that was not based on probability theory. Fuzzy Logic adds values of degree between absolute true and absolute false. It starts with and builds on a set of human language rules supplied by the user. The fuzzy systems convert these rules to their mathematical equivalents. This could simplify the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. In this paper we examine the decision making process of stock and option trading by the usage of MACD (Moving Average Convergence Divergence) technical analysis and Option Pricing with Fuzzy Logic approach. MACD technical analysis is for the prediction of the trends of underlying stock prices, such as bearish (going downward), bullish (going upward), and sideways. By using Fuzzy C-Means technique and Mamdani Fuzzy Inference System, we define the decision output where the value of MACD is high then decision is "Strong Sell", and the value of MACD is Low then the decision is "Strong Buy". We also implement the fuzzification of the Black-Scholes option-pricing formula. The stock and options methods are implemented on a portfolio of one stock and its options. Even though the values of input data, such as interest rates, stock price and its volatility, cannot be obtain accurately, these fuzzy methods can give a belief degree of the calculated the Black-Scholes formula so we can make the decision on option trading. The results show the good capability of the methods in the prediction of stock price trends. The performance of the simulated portfolio for a particular period of time also shows good return.

Migratory urge and gll Na+,K+-ATPase activity of hatchery-reared Atlantic salmon smolts from the Dennys and Penobscot River stocks, Maine

USGS Publications Warehouse

Spencer, Randall C.; Zydlewski, Joseph D.; Zydlewski, Gayle B.

2010-01-01

Hatchery-reared Atlantic salmon Salmo salar smolts produced from captive-reared Dennys River and sea-run Penobscot River broodstock are released into their source rivers in Maine. The adult return rate of Dennys smolts is comparatively low, and disparity in smolt quality between stocks resulting from genetic or broodstock rearing effects is plausible. Smolt behavior and physiology were assessed during sequential 14-d trials conducted in seminatural annular tanks with circular flow. “Migratory urge” (downstream movement) was monitored remotely using passive integrated transponder tags, and gill Na+,K+-ATPase activity was measured at the beginning and end of the trials to provide an index of smolt development. The migratory urge of both stocks was low in early April, increased 20-fold through late May, and declined by the end of June. The frequency and seasonal distribution of downstream movement were independent of stock. In March and April, initial gill Na+,K+-ATPase activities of Penobscot River smolts were lower than those of Dennys River smolts. For these trials, however, Penobscot River smolts increased enzyme activity after exposure to the tank, whereas Dennys River smolts did not, resulting in similar activities between stocks at the end of all trials. There was no clear relationship between migratory urge and gill Na+,K+-ATPase activity. Gill Na+,K+-ATPase activity of both stocks increased in advance of migratory urge and then declined while migratory urge was increasing. Maximum movement was observed from 2 h after sunset through 1 h after sunrise but varied seasonally. Dennys River smolts were slightly more nocturnal than Penobscot River smolts. These data suggest that Dennys and Penobscot River stocks are not markedly different in either physiological or behavioral expression of smolting.

Ergodicity of financial indices

NASA Astrophysics Data System (ADS)

Kolesnikov, A. V.; Rühl, T.

2010-05-01

We introduce the concept of the ensemble averaging for financial markets. We address the question of equality of ensemble and time averaging in their sequence and investigate if these averagings are equivalent for large amount of equity indices and branches. We start with the model of Gaussian-distributed returns, equal-weighted stocks in each index and absence of correlations within a single day and show that even this oversimplified model captures already the run of the corresponding index reasonably well due to its self-averaging properties. We introduce the concept of the instant cross-sectional volatility and discuss its relation to the ordinary time-resolved counterpart. The role of the cross-sectional volatility for the description of the corresponding index as well as the role of correlations between the single stocks and the role of non-Gaussianity of stock distributions is briefly discussed. Our model reveals quickly and efficiently some anomalies or bubbles in a particular financial market and gives an estimate of how large these effects can be and how quickly they disappear.

Interest and Inflation Risk: Investor Behavior

PubMed Central

González, María de la O; Jareño, Francisco; Skinner, Frank S.

2016-01-01

We examine investor behavior under interest and inflation risk in different scenarios. To that end, we analyze the relation between stock returns and unexpected changes in nominal and real interest rates and inflation for the US stock market. This relation is examined in detail by breaking the results down from the US stock market level to sector, sub-sector, and to individual industries as the ability of different industries to absorb unexpected changes in interest rates and inflation can vary by industry and by contraction and expansion sub-periods. While most significant relations are conventionally negative, some are consistently positive. This suggests some relevant implications on investor behavior. Thus, investments in industries with this positive relation can form a safe haven from unexpected changes in real and nominal interest rates. Gold has an insignificant beta during recessionary conditions hinting that Gold can be a safe haven during recessions. However, Gold also has a consistent negative relation to unexpected changes in inflation thereby damaging the claim that Gold is a hedge against inflation. PMID:27047418

Effects of fundamentals acquisition and strategy switch on stock price dynamics

NASA Astrophysics Data System (ADS)

Wu, Songtao; He, Jianmin; Li, Shouwei

2018-02-01

An agent-based artificial stock market is developed to simulate trading behavior of investors. In the market, acquisition and employment of information about fundamentals and strategy switch are investigated to explain stock price dynamics. Investors could obtain the information from both market and neighbors resided on their social networks. Depending on information status and performances of different strategies, an informed investor may switch to the strategy of fundamentalist. This in turn affects the information acquisition process, since fundamentalists are more inclined to search and spread the information than chartists. Further investigation into price dynamics generated from three typical networks, i.e. regular lattice, small-world network and random graph, are conducted after general relation between network structures and price dynamics is revealed. In each network, integrated effects of different combinations of information efficiency and switch intensity are investigated. Results have shown that, along with increasing switch intensity, market and social information efficiency play different roles in the formation of price distortion, standard deviation and kurtosis of returns.

Interest and Inflation Risk: Investor Behavior.

PubMed

González, María de la O; Jareño, Francisco; Skinner, Frank S

2016-01-01

We examine investor behavior under interest and inflation risk in different scenarios. To that end, we analyze the relation between stock returns and unexpected changes in nominal and real interest rates and inflation for the US stock market. This relation is examined in detail by breaking the results down from the US stock market level to sector, sub-sector, and to individual industries as the ability of different industries to absorb unexpected changes in interest rates and inflation can vary by industry and by contraction and expansion sub-periods. While most significant relations are conventionally negative, some are consistently positive. This suggests some relevant implications on investor behavior. Thus, investments in industries with this positive relation can form a safe haven from unexpected changes in real and nominal interest rates. Gold has an insignificant beta during recessionary conditions hinting that Gold can be a safe haven during recessions. However, Gold also has a consistent negative relation to unexpected changes in inflation thereby damaging the claim that Gold is a hedge against inflation.