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Sample records for stock market index

  1. 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.

  2. 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.

  3. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

    PubMed

    Qiu, Mingyue; Song, Yu

    2016-01-01

    In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

  4. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model

    PubMed Central

    Qiu, Mingyue; Song, Yu

    2016-01-01

    In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders’ expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day’s price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately. PMID:27196055

  5. Study on Market Stability and Price Limit of Chinese Stock Index Futures Market: An Agent-Based Modeling Perspective

    PubMed Central

    2015-01-01

    This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures. PMID:26571135

  6. Study on Market Stability and Price Limit of Chinese Stock Index Futures Market: An Agent-Based Modeling Perspective.

    PubMed

    Xiong, Xiong; Nan, Ding; Yang, Yang; Yongjie, Zhang

    2015-01-01

    This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures.

  7. Study on Market Stability and Price Limit of Chinese Stock Index Futures Market: An Agent-Based Modeling Perspective.

    PubMed

    Xiong, Xiong; Nan, Ding; Yang, Yang; Yongjie, Zhang

    2015-01-01

    This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures. PMID:26571135

  8. Generalized Weierstrass-Mandelbrot Function Model for Actual Stocks Markets Indexes with Nonlinear Characteristics

    NASA Astrophysics Data System (ADS)

    Zhang, L.; Yu, C.; Sun, J. Q.

    2015-03-01

    It is difficult to simulate the dynamical behavior of actual financial markets indexes effectively, especially when they have nonlinear characteristics. So it is significant to propose a mathematical model with these characteristics. In this paper, we investigate a generalized Weierstrass-Mandelbrot function (WMF) model with two nonlinear characteristics: fractal dimension D where 2 > D > 1.5 and Hurst exponent (H) where 1 > H > 0.5 firstly. And then we study the dynamical behavior of H for WMF as D and the spectrum of the time series γ change in three-dimensional space, respectively. Because WMF and the actual stock market indexes have two common features: fractal behavior using fractal dimension and long memory effect by Hurst exponent, we study the relationship between WMF and the actual stock market indexes. We choose a random value of γ and fixed value of D for WMF to simulate the S&P 500 indexes at different time ranges. As shown in the simulation results of three-dimensional space, we find that γ is important in WMF model and different γ may have the same effect for the nonlinearity of WMF. Then we calculate the skewness and kurtosis of actual Daily S&P 500 index in different time ranges which can be used to choose the value of γ. Based on these results, we choose appropriate γ, D and initial value into WMF to simulate Daily S&P 500 indexes. Using the fit line method in two-dimensional space for the simulated values, we find that the generalized WMF model is effective for simulating different actual stock market indexes in different time ranges. It may be useful for understanding the dynamical behavior of many different financial markets.

  9. Distribution characteristics of stock market liquidity

    NASA Astrophysics Data System (ADS)

    Luo, Jiawen; Chen, Langnan; Liu, Hao

    2013-12-01

    We examine the distribution characteristics of stock market liquidity by employing the generalized additive models for location, scale and shape (GAMLSS) model and three-minute frequency data from Chinese stock markets. We find that the BCPE distribution within the GAMLSS framework fits the distributions of stock market liquidity well with the diagnosis test. We also find that the stock market index exhibits a significant impact on the distributions of stock market liquidity. The stock market liquidity usually exhibits a positive skewness, but a normal distribution at a low level of stock market index and a high-peak and fat-tail shape at a high level of stock market index.

  10. Trading Rules on Stock Markets Using Genetic Network Programming with Reinforcement Learning and Importance Index

    NASA Astrophysics Data System (ADS)

    Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki

    Genetic Network Programming (GNP) is an evolutionary computation which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, it has been clarified that GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is a new element which is a criterion for decision making. In this paper, we combined GNP-IMX with Actor-Critic (GNP-IMX&AC) and create trading rules on stock markets. Evolution-based methods evolve their programs after enough period of time because they must calculate fitness values, however reinforcement learning can change programs during the period, therefore the trading rules can be created efficiently. In the simulation, the proposed method is trained using the stock prices of 10 brands in 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. The simulation results show that the proposed method can obtain larger profits than GNP-IMX without AC and Buy&Hold.

  11. How long the singular value decomposed entropy predicts the stock market? - Evidence from the Dow Jones Industrial Average Index

    NASA Astrophysics Data System (ADS)

    Gu, Rongbao; Shao, Yanmin

    2016-07-01

    In this paper, a new concept of multi-scales singular value decomposition entropy based on DCCA cross correlation analysis is proposed and its predictive power for the Dow Jones Industrial Average Index is studied. Using Granger causality analysis with different time scales, it is found that, the singular value decomposition entropy has predictive power for the Dow Jones Industrial Average Index for period less than one month, but not for more than one month. This shows how long the singular value decomposition entropy predicts the stock market that extends Caraiani's result obtained in Caraiani (2014). On the other hand, the result also shows an essential characteristic of stock market as a chaotic dynamic system.

  12. Stock Market Savvy.

    ERIC Educational Resources Information Center

    Okula, Susan

    2003-01-01

    This issue of Keying In, the newsletter of the National Business Education Association, focuses upon teaching young adults how to develop both investment strategies and an understanding of the stock market. The first article, "Sound Investing Know-How: A Must for Today's Young Adults," describes how young adults can plan for their own financial…

  13. 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.

  14. 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.

  15. 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.

  16. Market Confidence Predicts Stock Price: Beyond Supply and Demand.

    PubMed

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Zhang, Yuqing

    2016-01-01

    Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize market confidence, i.e., the ratio of the number of traders who is active in two successive trading days to the number of active traders in a certain trading day. Strong Granger causality is found between the index of market confidence and stock price. We further predict stock price by incorporating the index of market confidence into a neural network based on time series of stock price. Experimental results on 50 stocks in two Chinese Stock Exchanges demonstrate that the accuracy of stock price prediction is significantly improved by the inclusion of the market confidence index. This study sheds light on using cross-day trading behavior to characterize market confidence and to predict stock price. PMID:27391816

  17. Market Confidence Predicts Stock Price: Beyond Supply and Demand.

    PubMed

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Zhang, Yuqing

    2016-01-01

    Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize market confidence, i.e., the ratio of the number of traders who is active in two successive trading days to the number of active traders in a certain trading day. Strong Granger causality is found between the index of market confidence and stock price. We further predict stock price by incorporating the index of market confidence into a neural network based on time series of stock price. Experimental results on 50 stocks in two Chinese Stock Exchanges demonstrate that the accuracy of stock price prediction is significantly improved by the inclusion of the market confidence index. This study sheds light on using cross-day trading behavior to characterize market confidence and to predict stock price.

  18. Market Confidence Predicts Stock Price: Beyond Supply and Demand

    PubMed Central

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Zhang, Yuqing

    2016-01-01

    Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize market confidence, i.e., the ratio of the number of traders who is active in two successive trading days to the number of active traders in a certain trading day. Strong Granger causality is found between the index of market confidence and stock price. We further predict stock price by incorporating the index of market confidence into a neural network based on time series of stock price. Experimental results on 50 stocks in two Chinese Stock Exchanges demonstrate that the accuracy of stock price prediction is significantly improved by the inclusion of the market confidence index. This study sheds light on using cross-day trading behavior to characterize market confidence and to predict stock price. PMID:27391816

  19. Stocks low, marketers confident

    SciTech Connect

    Mantho, M.

    1997-01-01

    This has been a nerve wracking season as we looked at inadequate inventory spurring prices ever upward. We have watched the American Petroleum Association`s figures on refiner stocks with considerable dismay as they consistantly fell behind year ago inventory. The anxiety extended to how much oil was in marketers` bulkplants and finally in customer tanks. And so, we asked our reporting panel to help us get a fix on how much oil was available for our customers. We asked the questions in early November and so all our figures are for that month. First we asked the capacity of their bulk tanks. And then how many gallons they had on hand November 1, 1996 and the same date of 1995. From these figures, we were able to get estimates of oil inventories. Marketers bulk tanks were 47.5% filled on November 1 which meant that there was on hand at this level, 36 gallons of heating oil for each customer. At that point in the season, customer tanks were 58% filled which translated into 218 gallons.

  20. 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.

  1. 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

  2. Scaling analysis of stock markets.

    PubMed

    Bu, Luping; Shang, Pengjian

    2014-06-01

    In this paper, we apply the detrended fluctuation analysis (DFA), local scaling detrended fluctuation analysis (LSDFA), and detrended cross-correlation analysis (DCCA) to investigate correlations of several stock markets. DFA method is for the detection of long-range correlations used in time series. LSDFA method is to show more local properties by using local scale exponents. DCCA method is a developed method to quantify the cross-correlation of two non-stationary time series. We report the results of auto-correlation and cross-correlation behaviors in three western countries and three Chinese stock markets in periods 2004-2006 (before the global financial crisis), 2007-2009 (during the global financial crisis), and 2010-2012 (after the global financial crisis) by using DFA, LSDFA, and DCCA method. The findings are that correlations of stocks are influenced by the economic systems of different countries and the financial crisis. The results indicate that there are stronger auto-correlations in Chinese stocks than western stocks in any period and stronger auto-correlations after the global financial crisis for every stock except Shen Cheng; The LSDFA shows more comprehensive and detailed features than traditional DFA method and the integration of China and the world in economy after the global financial crisis; When it turns to cross-correlations, it shows different properties for six stock markets, while for three Chinese stocks, it reaches the weakest cross-correlations during the global financial crisis.

  3. Scaling analysis of stock markets.

    PubMed

    Bu, Luping; Shang, Pengjian

    2014-06-01

    In this paper, we apply the detrended fluctuation analysis (DFA), local scaling detrended fluctuation analysis (LSDFA), and detrended cross-correlation analysis (DCCA) to investigate correlations of several stock markets. DFA method is for the detection of long-range correlations used in time series. LSDFA method is to show more local properties by using local scale exponents. DCCA method is a developed method to quantify the cross-correlation of two non-stationary time series. We report the results of auto-correlation and cross-correlation behaviors in three western countries and three Chinese stock markets in periods 2004-2006 (before the global financial crisis), 2007-2009 (during the global financial crisis), and 2010-2012 (after the global financial crisis) by using DFA, LSDFA, and DCCA method. The findings are that correlations of stocks are influenced by the economic systems of different countries and the financial crisis. The results indicate that there are stronger auto-correlations in Chinese stocks than western stocks in any period and stronger auto-correlations after the global financial crisis for every stock except Shen Cheng; The LSDFA shows more comprehensive and detailed features than traditional DFA method and the integration of China and the world in economy after the global financial crisis; When it turns to cross-correlations, it shows different properties for six stock markets, while for three Chinese stocks, it reaches the weakest cross-correlations during the global financial crisis. PMID:24985421

  4. Scaling analysis of stock markets

    NASA Astrophysics Data System (ADS)

    Bu, Luping; Shang, Pengjian

    2014-06-01

    In this paper, we apply the detrended fluctuation analysis (DFA), local scaling detrended fluctuation analysis (LSDFA), and detrended cross-correlation analysis (DCCA) to investigate correlations of several stock markets. DFA method is for the detection of long-range correlations used in time series. LSDFA method is to show more local properties by using local scale exponents. DCCA method is a developed method to quantify the cross-correlation of two non-stationary time series. We report the results of auto-correlation and cross-correlation behaviors in three western countries and three Chinese stock markets in periods 2004-2006 (before the global financial crisis), 2007-2009 (during the global financial crisis), and 2010-2012 (after the global financial crisis) by using DFA, LSDFA, and DCCA method. The findings are that correlations of stocks are influenced by the economic systems of different countries and the financial crisis. The results indicate that there are stronger auto-correlations in Chinese stocks than western stocks in any period and stronger auto-correlations after the global financial crisis for every stock except Shen Cheng; The LSDFA shows more comprehensive and detailed features than traditional DFA method and the integration of China and the world in economy after the global financial crisis; When it turns to cross-correlations, it shows different properties for six stock markets, while for three Chinese stocks, it reaches the weakest cross-correlations during the global financial crisis.

  5. 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.

  6. Quantum Brownian motion model for the stock market

    NASA Astrophysics Data System (ADS)

    Meng, Xiangyi; Zhang, Jian-Wei; Guo, Hong

    2016-06-01

    It is believed by the majority today that the efficient market hypothesis is imperfect because of market irrationality. Using the physical concepts and mathematical structures of quantum mechanics, we construct an econophysical framework for the stock market, based on which we analogously map massive numbers of single stocks into a reservoir consisting of many quantum harmonic oscillators and their stock index into a typical quantum open system-a quantum Brownian particle. In particular, the irrationality of stock transactions is quantitatively considered as the Planck constant within Heisenberg's uncertainty relationship of quantum mechanics in an analogous manner. We analyze real stock data of Shanghai Stock Exchange of China and investigate fat-tail phenomena and non-Markovian behaviors of the stock index with the assistance of the quantum Brownian motion model, thereby interpreting and studying the limitations of the classical Brownian motion model for the efficient market hypothesis from a new perspective of quantum open system dynamics.

  7. Alternation of different fluctuation regimes in the stock market dynamics

    NASA Astrophysics Data System (ADS)

    Kwapień, J.; Drożdż, S.; Speth, J.

    2003-12-01

    Based on the tick-by-tick stock prices from the German and American stock markets, we study the statistical properties of the distribution of the individual stocks and the index returns in highly collective and noisy intervals of trading, separately. We show that periods characterized by the strong inter-stock couplings can be associated with the distributions of index fluctuations which reveal more pronounced tails than in the case of weaker couplings in the market. During periods of strong correlations in the German market these distributions can even reveal an apparent Lévy-stable component.

  8. A controllable laboratory stock market for modeling real stock markets

    NASA Astrophysics Data System (ADS)

    An, Kenan; Li, Xiaohui; Yang, Guang; Huang, Jiping

    2013-10-01

    Based on the different research approaches, econophysics can be divided into three directions: empirical econophysics, computational econophysics, and experimental econophysics. Because empirical econophysics lacks controllability that is needed to study the impacts of different external conditions and computational econophysics has to adopt artificial decision-making processes that are often deviated from those of real humans, experimental econophysics tends to overcome these problems by offering controllability and using real humans in laboratory experiments. However, to our knowledge, the existing laboratory experiments have not convincingly reappeared the stylized facts (say, scaling) that have been revealed for real economic/financial markets by econophysicists. A most important reason is that in these experiments, discrete trading time makes these laboratory markets deviated from real markets where trading time is naturally continuous. Here we attempt to overcome this problem by designing a continuous double-auction stock-trading market and conducting several human experiments in laboratory. As an initial work, the present artificial financial market can reproduce some stylized facts related to clustering and scaling. Also, it predicts some other scaling in human behavior dynamics that is hard to achieve in real markets due to the difficulty in getting the data. Thus, it becomes possible to study real stock markets by conducting controlled experiments on such laboratory stock markets producing high frequency data.

  9. Does the singular value decomposition entropy have predictive power for stock market? - Evidence from the Shenzhen stock market

    NASA Astrophysics Data System (ADS)

    Gu, Rongbao; Xiong, Wei; Li, Xinjie

    2015-12-01

    This paper analyzes the predictive ability of the singular value decomposition entropy for the Shenzhen Component Index based on different scales. It is found that, the predictive ability of the entropy for the index is affected by the width of moving time windows and the structural break in stock market. By moving time windows with one year, the predictive power of singular value decomposition entropy of Shenzhen stock market for its component index is found after the reform of non-tradable shares.

  10. 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.

  11. Online Stock Market Games for High Schools.

    ERIC Educational Resources Information Center

    Lopus, Jane; Placone, Dennis

    2002-01-01

    Identifies a Web site providing information about stock market simulations for high school economics courses. Divides the information into two tables: (1) the structure of online stock market games; and (2) the determination of portfolio values of online stock market games. States that changes and updates are available at Web sites. (JEH)

  12. Persistent collective trend in stock markets

    NASA Astrophysics Data System (ADS)

    Balogh, Emeric; Simonsen, Ingve; Nagy, Bálint Zs.; Néda, Zoltán

    2010-12-01

    Empirical evidence is given for a significant difference in the collective trend of the share prices during the stock index rising and falling periods. Data on the Dow Jones Industrial Average and its stock components are studied between 1991 and 2008. Pearson-type correlations are computed between the stocks and averaged over stock pairs and time. The results indicate a general trend: whenever the stock index is falling the stock prices are changing in a more correlated manner than in case the stock index is ascending. A thorough statistical analysis of the data shows that the observed difference is significant, suggesting a constant fear factor among stockholders.

  13. The lead-lag relationship between stock index and stock index futures: A thermal optimal path method

    NASA Astrophysics Data System (ADS)

    Gong, Chen-Chen; Ji, Shen-Dan; Su, Li-Ling; Li, Sai-Ping; Ren, Fei

    2016-02-01

    The study of lead-lag relationship between stock index and stock index futures is of great importance for its wide application in hedging and portfolio investments. Previous works mainly use conventional methods like Granger causality test, GARCH model and error correction model, and focus on the causality relation between the index and futures in a certain period. By using a non-parametric approach-thermal optimal path (TOP) method, we study the lead-lag relationship between China Securities Index 300 (CSI 300), Hang Seng Index (HSI), Standard and Poor 500 (S&P 500) Index and their associated futures to reveal the variance of their relationship over time. Our finding shows evidence of pronounced futures leadership for well established index futures, namely HSI and S&P 500 index futures, while index of developing market like CSI 300 has pronounced leadership. We offer an explanation based on the measure of an indicator which quantifies the differences between spot and futures prices for the surge of lead-lag function. Our results provide new perspectives for the understanding of the dynamical evolution of lead-lag relationship between stock index and stock index futures, which is valuable for the study of market efficiency and its applications.

  14. Abnormal statistical properties of stock indexes during a financial crash

    NASA Astrophysics Data System (ADS)

    Li, Wei-Shen; Liaw, Sy-Sang

    2015-03-01

    We investigate minute indexes of stock markets in 10 countries during financial crashes by dividing them into several stages according to their stock price tendencies: plunging stage (stage 1), fluctuating or rebounding stage (stage 2), and soaring stage (stage 3). The tail distributions of the returns satisfy a power law for developed markets but show a dual power-law structure for emerging markets. Prominent dual fractal structures are found during the plunging stage in developed markets, and after the plunging stage in emerging markets. The fractal analysis on the sign series of the returns yields similar dual fractal properties. The magnitude series of the returns provides surprising results during a crash. We find that developed markets have strong and weak long-range persistence in plunging and soaring stage respectively, while emerging markets behave oppositely. These results indicate that different types of markets are influenced strongly by the external shock of a crisis at different stages.

  15. 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

  16. Taxonomy of stock market indices

    NASA Astrophysics Data System (ADS)

    Bonanno, Giovanni; Vandewalle, Nicolas; Mantegna, Rosario N.

    2000-12-01

    We investigate sets of financial nonredundant and nonsynchronously recorded time series. The sets are composed by a number of stock market indices located all over the world in five continents. By properly selecting the time horizon of returns and by using a reference currency we find a meaningful taxonomy. The detection of such a taxonomy proves that interpretable information can be stored in a set of nonsynchronously recorded time series.

  17. On the Feed-back Mechanism of Chinese Stock Markets

    NASA Astrophysics Data System (ADS)

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

    Feed-back models in the stock markets research imply an adjustment process toward investors' expectation for current information and past experiences. Error-correction and cointegration are often used to evaluate the long-run relation. The Efficient Capital Market Hypothesis, which had ignored the effect of the accumulation of information, cannot explain some anomalies such as bubbles and partial predictability in the stock markets. In order to investigate the feed-back mechanism and to determine an effective model, we use daily data of the stock index of two Chinese stock markets with the expectational model, which is one kind of geometric lag models. Tests and estimations of error-correction show that long-run equilibrium seems to be seldom achieved in Chinese stock markets. Our result clearly shows the common coefficient of expectations and fourth-order autoregressive disturbance exist in the two Chinese stock markets. Furthermore, we find the same coefficient of expectations has an autoregressive effect on disturbances in the two Chinese stock markets. Therefore the presence of such feed-back is also supported in Chinese stock markets.

  18. Modeling the stock market prior to large crashes

    NASA Astrophysics Data System (ADS)

    Johansen, A.; Sornette, D.

    We propose that the minimal requirements for a model of stock market price fluctuations should comprise time asymmetry, robustness with respect to connectivity between agents, ``bounded rationality'' and a probabilistic description. We also compare extensively two previously proposed models of log-periodic behavior of the stock market index prior to a large crash. We find that the model which follows the above requirements outperforms the other with a high statistical significance.

  19. Corruption and stock market development: A quantitative approach

    NASA Astrophysics Data System (ADS)

    Bolgorian, Meysam

    2011-11-01

    Studying the relation between corruption and economic factors and examining its consequences for economic development have attracted many economists and physicists in recent years. The purpose of this paper is to focus on the role of stock market development on corruption. Analyzing a data set of corruption and stock market development measures such as market capitalization and total value of share trading for 46 countries around the world for the period 2007-2009, we examine the dependence of the Corruption Perception Index (CPI) on stock market development. Our findings suggest that there exists a power-law dependence between corruption and stock market development. We also observe a negative relation between level of corruption and financial system improvement.

  20. Scaling and Predictability in Stock Markets: A Comparative Study

    PubMed Central

    Zhang, Huishu; Wei, Jianrong; Huang, Jiping

    2014-01-01

    Most people who invest in stock markets want to be rich, thus, many technical methods have been created to beat the market. If one knows the predictability of the price series in different markets, it would be easier for him/her to make the technical analysis, at least to some extent. Here we use one of the most basic sold-and-bought trading strategies to establish the profit landscape, and then calculate the parameters to characterize the strength of predictability. According to the analysis of scaling of the profit landscape, we find that the Chinese individual stocks are harder to predict than US ones, and the individual stocks are harder to predict than indexes in both Chinese stock market and US stock market. Since the Chinese (US) stock market is a representative of emerging (developed) markets, our comparative study on the markets of these two countries is of potential value not only for conducting technical analysis, but also for understanding physical mechanisms of different kinds of markets in terms of scaling. PMID:24632944

  1. Scaling and predictability in stock markets: a comparative study.

    PubMed

    Zhang, Huishu; Wei, Jianrong; Huang, Jiping

    2014-01-01

    Most people who invest in stock markets want to be rich, thus, many technical methods have been created to beat the market. If one knows the predictability of the price series in different markets, it would be easier for him/her to make the technical analysis, at least to some extent. Here we use one of the most basic sold-and-bought trading strategies to establish the profit landscape, and then calculate the parameters to characterize the strength of predictability. According to the analysis of scaling of the profit landscape, we find that the Chinese individual stocks are harder to predict than US ones, and the individual stocks are harder to predict than indexes in both Chinese stock market and US stock market. Since the Chinese (US) stock market is a representative of emerging (developed) markets, our comparative study on the markets of these two countries is of potential value not only for conducting technical analysis, but also for understanding physical mechanisms of different kinds of markets in terms of scaling. PMID:24632944

  2. Does Stock Market Performance Influence Retirement Intentions?

    ERIC Educational Resources Information Center

    Goda, Gopi Shah; Shoven, John B.; Slavov, Sita Nataraj

    2012-01-01

    Media reports predicted that the stock market decline in October 2008 would cause changes in retirement intentions, due to declines in retirement assets. We use panel data from the Health and Retirement Study to investigate the relationship between stock market performance and retirement intentions during 1998-2008, a period that includes the…

  3. Stock market stability: Diffusion entropy analysis

    NASA Astrophysics Data System (ADS)

    Li, Shouwei; Zhuang, Yangyang; He, Jianmin

    2016-05-01

    In this article, we propose a method to analyze the stock market stability based on diffusion entropy, and conduct an empirical analysis of Dow Jones Industrial Average. Empirical results show that this method can reflect the volatility and extreme cases of the stock market.

  4. Recurrence quantification analysis of global stock markets

    NASA Astrophysics Data System (ADS)

    Bastos, João A.; Caiado, Jorge

    2011-04-01

    This study investigates the presence of deterministic dependencies in international stock markets using recurrence plots and recurrence quantification analysis (RQA). The results are based on a large set of free float-adjusted market capitalization stock indices, covering a period of 15 years. The statistical tests suggest that the dynamics of stock prices in emerging markets is characterized by higher values of RQA measures when compared to their developed counterparts. The behavior of stock markets during critical financial events, such as the burst of the technology bubble, the Asian currency crisis, and the recent subprime mortgage crisis, is analyzed by performing RQA in sliding windows. It is shown that during these events stock markets exhibit a distinctive behavior that is characterized by temporary decreases in the fraction of recurrence points contained in diagonal and vertical structures.

  5. Scaling behavior in ranking mobility of Chinese stock market

    NASA Astrophysics Data System (ADS)

    Wu, Ke; Xiong, Wanting; Weng, Xin; Wang, Yougui

    2014-08-01

    As an aggregate measure of the variations in individuals, the analysis of mobility provides a substantial and comprehensive perspective into the complexity of socio-economic systems. In this paper, we introduced the ranking mobility index to measure the ranking variations of the stocks in Chinese stock market over time. Using the daily data of 837 constituent stocks of the Shanghai A-Stock Composite Index from January 1, 2002 to December 31, 2012, we examined respectively the dependence of ranking mobility with respect to the absolute return, trading volume and turnover ratio on the sampling time interval. The scaling property is observed in all three relations. The fact of long relaxation times gives evidence of long memory property in the stock ranking orders.

  6. Spillovers among regional and international stock markets

    NASA Astrophysics Data System (ADS)

    Huen, Tan Bee; Arsad, Zainudin; Chun, Ooi Po

    2014-07-01

    Realizing the greater risk by the increase in the level of financial market integration, this study investigates the dynamic of international and regional stock markets co-movement among Asian countries with the world leading market, the US. The data utilized in this study comprises of weekly closing prices for four stock indices, that consists of two developing markets (Malaysia and China) and two developed markets (Japan and the US), and encompasses the period from January 1996 to December 2012. Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model with the BEKK parameterization is employed to investigate the mean and volatility spillover effects among the selected stock indices. The results show significant mean spillover not only from the larger developed markets to smaller developing markets but also from the smaller developing markets to larger developed markets. Volatility spillover between the developed markets is found to be smaller than that between the developing markets. Conditional correlations among the stock markets are found to increase over the sample period. The findings of significant mean and volatility spillovers are considered as bad news for international investors as it reduces the benefit from portfolio diversification but act as useful information for investors to be more aware in diversifying their investment or stock selection.

  7. Level crossing analysis of the stock markets

    NASA Astrophysics Data System (ADS)

    Jafari, G. R.; Movahed, M. S.; Fazeli, S. M.; Rahimi Tabar, M. Reza; Masoudi, S. F.

    2006-06-01

    We investigate the average frequency of positive slope να+ crossing for the returns of market prices. The method is based on stochastic processes in which no scaling feature is explicitly required. Using this method we define a new quantity to quantify the stage of development and activity of stock exchanges. We compare the Tehran and western stock markets and show that some, such as the Tehran (TEPIX) and New Zealand (NZX) stock exchanges, are emerging, and also that TEPIX is a non-active market and is financially motivated to absorb capital.

  8. A Tale of Two Stock Markets

    ERIC Educational Resources Information Center

    Armstrong, Michelle Hine; Piercey, Victor I.; Greene-Hunley, Stephanie

    2015-01-01

    This article describes two different projects using the stock market as a context for learning. For both projects, students "bought" shares in individual companies, tracked stock prices for a period of time, and then "sold" their shares at a gain or loss. The projects are adaptable for students in late elementary school through…

  9. Complexity in the Chinese stock market and its relationships with monetary policy intensity

    NASA Astrophysics Data System (ADS)

    Ying, Shangjun; Fan, Ying

    2014-01-01

    This paper introduces how to formulate the CSI300 evolving stock index using the Paasche compiling technique of weighed indexes after giving the GCA model. It studies dynamics characteristics of the Chinese stock market and its relationships with monetary policy intensity, based on the evolving stock index. It concludes by saying that it is possible to construct a dynamics equation of the Chinese stock market using three variables, and that it is useless to regular market-complexity according to changing intensity of external factors from a chaos point of view.

  10. Heterogeneous information-based artificial stock market

    NASA Astrophysics Data System (ADS)

    Pastore, S.; Ponta, L.; Cincotti, S.

    2010-05-01

    In this paper, an information-based artificial stock market is considered. The market is populated by heterogeneous agents that are seen as nodes of a sparsely connected graph. Agents trade a risky asset in exchange for cash. Besides the amount of cash and assets owned, each agent is characterized by a sentiment. Moreover, agents share their sentiments by means of interactions that are identified by the graph. Interactions are unidirectional and are supplied with heterogeneous weights. The agent's trading decision is based on sentiment and, consequently, the stock price process depends on the propagation of information among the interacting agents, on budget constraints and on market feedback. A central market maker (clearing house mechanism) determines the price process at the intersection of the demand and supply curves. Both closed- and open-market conditions are considered. The results point out the validity of the proposed model of information exchange among agents and are helpful for understanding the role of information in real markets. Under closed market conditions, the interaction among agents' sentiments yields a price process that reproduces the main stylized facts of real markets, e.g. the fat tails of the returns distributions and the clustering of volatility. Within open-market conditions, i.e. with an external cash inflow that results in asset price inflation, also the unitary root stylized fact is reproduced by the artificial stock market. Finally, the effects of model parameters on the properties of the artificial stock market are also addressed.

  11. 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.

  12. The Stock Market Game: A Simulation of Stock Market Trading. Grades 5-8.

    ERIC Educational Resources Information Center

    Draze, Dianne

    This guide to a unit on a simulation game about the stock market contains an instructional text and two separate simulations. Through directed lessons and reproducible worksheets, the unit teaches students about business ownership, stock exchanges, benchmarks, commissions, why prices change, the logistics of buying and selling stocks, and how to…

  13. Relationships among energy price shocks, stock market, and the macroeconomy: evidence from China.

    PubMed

    Cong, Rong-Gang; Shen, Shaochuan

    2013-01-01

    This paper investigates the interactive relationships among China energy price shocks, stock market, and the macroeconomy using multivariate vector autoregression. The results indicate that there is a long cointegration among them. A 1% rise in the energy price index can depress the stock market index by 0.54% and the industrial value-adding growth by 0.037%. Energy price shocks also cause inflation and have a 5-month lag effect on stock market, which may result in the stock market "underreacting." The energy price can explain stock market fluctuations better than the interest rate over a longer time period. Consequently, investors should pay greater attention to the long-term effect of energy on the stock market.

  14. Relationships among Energy Price Shocks, Stock Market, and the Macroeconomy: Evidence from China

    PubMed Central

    Cong, Rong-Gang; Shen, Shaochuan

    2013-01-01

    This paper investigates the interactive relationships among China energy price shocks, stock market, and the macroeconomy using multivariate vector autoregression. The results indicate that there is a long cointegration among them. A 1% rise in the energy price index can depress the stock market index by 0.54% and the industrial value-adding growth by 0.037%. Energy price shocks also cause inflation and have a 5-month lag effect on stock market, which may result in the stock market “underreacting.” The energy price can explain stock market fluctuations better than the interest rate over a longer time period. Consequently, investors should pay greater attention to the long-term effect of energy on the stock market. PMID:23690737

  15. Stock market return distributions: From past to present

    NASA Astrophysics Data System (ADS)

    Drożdż, S.; Forczek, M.; Kwapień, J.; Oświeçimka, P.; Rak, R.

    2007-09-01

    We show that recent stock market fluctuations are characterized by the cumulative distributions whose tails on short, minute time scales exhibit power scaling with the scaling index α>3 and this index tends to increase quickly with decreasing sampling frequency. Our study is based on high-frequency recordings of the S&P500, DAX and WIG20 indices over the interval May 2004-May 2006. Our findings suggest that dynamics of the contemporary market may differ from the one observed in the past. This effect indicates a constantly increasing efficiency of world markets.

  16. Clustering stock market companies via chaotic map synchronization

    NASA Astrophysics Data System (ADS)

    Basalto, N.; Bellotti, R.; De Carlo, F.; Facchi, P.; Pascazio, S.

    2005-01-01

    A pairwise clustering approach is applied to the analysis of the Dow Jones index companies, in order to identify similar temporal behavior of the traded stock prices. To this end, the chaotic map clustering algorithm is used, where a map is associated to each company and the correlation coefficients of the financial time series to the coupling strengths between maps. The simulation of a chaotic map dynamics gives rise to a natural partition of the data, as companies belonging to the same industrial branch are often grouped together. The identification of clusters of companies of a given stock market index can be exploited in the portfolio optimization strategies.

  17. Time-varying long term memory in the European Union stock markets

    NASA Astrophysics Data System (ADS)

    Sensoy, Ahmet; Tabak, Benjamin M.

    2015-10-01

    This paper proposes a new efficiency index to model time-varying inefficiency in stock markets. We focus on European stock markets and show that they have different degrees of time-varying efficiency. We observe that the 2008 global financial crisis has an adverse effect on almost all EU stock markets. However, the Eurozone sovereign debt crisis has a significant adverse effect only on the markets in France, Spain and Greece. For the late members, joining EU does not have a uniform effect on stock market efficiency. Our results have important implications for policy makers, investors, risk managers and academics.

  18. 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

  19. Quantifying the Behavior of Stock Correlations Under Market Stress

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

    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.

  20. Quantifying the behavior of stock correlations under market stress.

    PubMed

    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.

  1. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... marketable stock means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as... section 1298(a), stock in any passive foreign investment company, that stock will be treated as marketable... owns directly or indirectly, as defined in section 1298(a), stock in any passive foreign...

  2. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... marketable stock means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as... section 1298(a), stock in any passive foreign investment company, that stock will be treated as marketable... owns directly or indirectly, as defined in section 1298(a), stock in any passive foreign...

  3. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... marketable stock means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as... section 1298(a), stock in any passive foreign investment company, that stock will be treated as marketable... owns directly or indirectly, as defined in section 1298(a), stock in any passive foreign...

  4. The Stock Market: Risk vs. Uncertainty.

    ERIC Educational Resources Information Center

    Griffitts, Dawn

    2002-01-01

    This economics education publication focuses on the U.S. stock market and the risk and uncertainty that an individual faces when investing in the market. The material explains that risk and uncertainty relate to the same underlying concept randomness. It defines and discusses both concepts and notes that although risk is quantifiable, uncertainty…

  5. 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. PMID:26327593

  6. 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

  7. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 26 Internal Revenue 11 2010-04-01 2010-04-01 true Definition of marketable stock. 1.1296-2 Section... Definition of marketable stock. (a) General rule. For purposes of section 1296, the term marketable stock means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as defined...

  8. Influence network in the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gao, Ya-Chun; Zeng, Yong; Cai, Shi-Min

    2015-03-01

    In a stock market, the price fluctuations are interactive, that is, one listed company can influence others. In this paper, we seek to study the influence relationships among listed companies by constructing a directed network on the basis of the Chinese stock market. This influence network shows distinct topological properties. In particular, a few large companies that can lead the tendency of the stock market are recognized. Furthermore, by analyzing the subnetworks of listed companies distributed in several significant economic sectors, it is found that the influence relationships are totally different from one economic sector to another, of which three types of connectivity as well as hub-like listed companies are identified. In addition, the rankings of listed companies obtained from the centrality metrics of the influence network are compared with those according to the assets, which gives inspiration to uncover and understand the importance of listed companies on the stock market. These empirical results are meaningful in providing these topological properties of the Chinese stock market and economic sectors as well as revealing the interactive influence relationships among listed companies.

  9. Empirical investigation of stock price dynamics in an emerging market

    NASA Astrophysics Data System (ADS)

    Palágyi, Zoltán; Mantegna, Rosario N.

    1999-07-01

    We study the development of an emerging market - the Budapest Stock Exchange - by investigating the time evolution of some statistical properties of heavily traded stocks. Moving quarter by quarter over a period of two and a half years we analyze the scaling properties of the standard deviation of intra-day log-price changes. We observe scaling using both seconds and ticks as units of time. For the investigated stocks a Levy shape is a good approximation to the probability density function of tick-by-tick log-price changes in each quarter: the index of the distribution follows an increasing trend, suggesting it could be used as a measure of market efficiency.

  10. Damped oscillations in the ratios of stock market indices

    NASA Astrophysics Data System (ADS)

    Wu, Ming-Chya

    2012-02-01

    A stock market index is an average of a group of stock prices with weights. Different stock market indices derived from various combinations of stocks may share similar trends in certain periods, while it is not expected that there are fixed relations among them. Here we report our investigations on the daily index data of Dow Jones Industry Average (DJIA), NASDAQ, and S&P500 from 1971/02/05 to 2011/06/30. By analyzing the index ratios using the empirical mode decomposition, we find that the ratios NASDAQ/DJIA and S&500/DJIA, normalized to 1971/02/05, approached and then retained the values of 2 and 1, respectively. The temporal variations of the ratios consist of global trends and oscillatory components including a damped oscillation in 8-year cycle and damping factors of 7183 days (NASDAQ/DJIA) and 138471 days (S&P500/DJIA). Anomalies in the ratios, corresponding to significant increases and decreases of indices, only appear in the time scale less than an 8-year cycle. Detrended fluctuation analysis and multiscale entropy analysis of the components with cycles less than a half-year manifest a behavior of self-adjustment in the ratios, and the behavior in S&500/DJIA is more significant than in NASDAQ/DJIA.

  11. Analysis in correlation for the Korean stock market

    NASA Astrophysics Data System (ADS)

    Jung, Woo-Sung; Chae, Seungbyung; Yang, Jae-Suk; Kwon, Okyu; Moon, Hie-Tae

    2005-05-01

    The correlation between stock price changes is useful information. Through the correlation matrix, we construct a portfolio with its minimum spanning tree. We make the minimum spanning tree of the Korean stock market, a representative emerging market, which is different from that of the mature market. It is due to the emerging market's less abundant liquidity than the mature market. And we find the distribution of the correlation coefficient is different for several periods. As the market is developing, many changes from inside and outside the market occurs, and several parameters of the stock market network are changed. The Korean stock market is under an evolution.

  12. Dependence phenomenon analysis of the stock market

    NASA Astrophysics Data System (ADS)

    Cheng, Wuyang; Wang, Jun

    2013-04-01

    A random financial stock price model is developed by the interacting contact process, which is one of the statistical-physics systems. The contact process is a continuous-time Markov process, one interpretation of this process is as a model for the spread of an infection, where the epidemic spreading mimics the interplay of local infections and the recovery of individuals. We investigate and analyze the long-term memory, the nonlinear correlations and the multifractal phenomenon of normalized returns of the price model by statistical analysis methods, which include autocorrelation analysis, the Gaussian copula method and the multifractal analysis method. Moreover, we consider the daily returns of the Shanghai Stock Exchange Composite Index and the Shenzhen Stock Exchange Composite Index, and the comparisons of statistical behaviors of returns between the actual data and the simulation data are presented.

  13. Progress in physical properties of Chinese stock markets

    NASA Astrophysics Data System (ADS)

    Liang, Yuan; Yang, Guang; Huang, Ji-Ping

    2013-08-01

    In the past two decades, statistical physics was brought into the field of finance, applying new methods and concepts to financial time series and developing a new interdiscipline "econophysics". In this review, we introduce several commonly used methods for stock time series in econophysics including distribution functions, correlation functions, detrended fluctuation analysis method, detrended moving average method, and multifractal analysis. Then based on these methods, we review some statistical properties of Chinese stock markets including scaling behavior, long-term correlations, cross-correlations, leverage effects, antileverage effects, and multifractality. Last, based on an agent-based model, we develop a new option pricing model — financial market model that shows a good agreement with the prices using real Shanghai Index data. This review is helpful for people to understand and research statistical physics of financial markets.

  14. Group identification in Indonesian stock market

    NASA Astrophysics Data System (ADS)

    Nurriyadi Suparno, Ervano; Jo, Sung Kyun; Lim, Kyuseong; Purqon, Acep; Kim, Soo Yong

    2016-08-01

    The characteristic of Indonesian stock market is interesting especially because it represents developing countries. We investigate the dynamics and structures by using Random Matrix Theory (RMT). Here, we analyze the cross-correlation of the fluctuations of the daily closing price of stocks from the Indonesian Stock Exchange (IDX) between January 1, 2007, and October 28, 2014. The eigenvalue distribution of the correlation matrix consists of noise which is filtered out using the random matrix as a control. The bulk of the eigenvalue distribution conforms to the random matrix, allowing the separation of random noise from original data which is the deviating eigenvalues. From the deviating eigenvalues and the corresponding eigenvectors, we identify the intrinsic normal modes of the system and interpret their meaning based on qualitative and quantitative approach. The results show that the largest eigenvector represents the market-wide effect which has a predominantly common influence toward all stocks. The other eigenvectors represent highly correlated groups within the system. Furthermore, identification of the largest components of the eigenvectors shows the sector or background of the correlated groups. Interestingly, the result shows that there are mainly two clusters within IDX, natural and non-natural resource companies. We then decompose the correlation matrix to investigate the contribution of the correlated groups to the total correlation, and we find that IDX is still driven mainly by the market-wide effect.

  15. How High Frequency Trading Affects a Market Index

    PubMed Central

    Kenett, Dror Y.; Ben-Jacob, Eshel; Stanley, H. Eugene; gur-Gershgoren, Gitit

    2013-01-01

    The relationship between a market index and its constituent stocks is complicated. While an index is a weighted average of its constituent stocks, when the investigated time scale is one day or longer the index has been found to have a stronger effect on the stocks than vice versa. We explore how this interaction changes in short time scales using high frequency data. Using a correlation-based analysis approach, we find that in short time scales stocks have a stronger influence on the index. These findings have implications for high frequency trading and suggest that the price of an index should be published on shorter time scales, as close as possible to those of the actual transaction time scale. PMID:23817553

  16. Collective Behavior of Stock Prices as a Precursor to Market Crash

    NASA Astrophysics Data System (ADS)

    Maskawa, J.

    We study precursors to the global market crash that occurred onall main stock exchanges throughout the world in October 2008 about three weeks after the bankruptcy of Lehman Brothers Holdings Inc. on 15 September. We examine the collective behavior of stock returns and analyze the market mode, which is a market-wide collective mode, with constituent issues of the FTSE 100 index listed on the London Stock Exchange. Before the market crash, a sharp rise in a measure of the collective behavior was observed. It was shown to be associated with news including the words ``financial crisis". They did not impact stock prices severely alone, but they exacerbated the pessimistic mood that prevailed among stock market participants. Such news increased after the Lehman shock preceding the market crash. The variance increased along with the cumulative amount of news according to a power law.

  17. 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. PMID:26587364

  18. 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.

  19. Using the Stock Market to Teach Physics

    NASA Astrophysics Data System (ADS)

    Faux, David A.; Hearn, Stephen

    2004-11-01

    Students are interested in money. Personal finance is an important issue for most students, especially as they move into university education and take a greater control of their own finances. Many are also interested in stock markets and their ability to allow someone to make, and lose, large sums of money, with their interest fueled by the boom in technology-based stocks of 2000/2001 followed by their subsequent dramatic collapse and the publicizing of so-called "rogue-traders." There is also a much greater ownership of stocks by families following public offerings, stock-based savings products, and the ability to trade stocks online. Consequently, there has been a steady growth of finance and finance-related courses available within degree programs in response to the student demand, with many students motivated by the huge salaries commanded by those with a successful career in the financial sector. We report here details of a joint project between Charterhouse School and the University of Surrey designed to exploit the excitement of finance to teach elements of the high school (age 16-18) curriculum through modeling and simulation.

  20. Decomposing the stock market intraday dynamics

    NASA Astrophysics Data System (ADS)

    Kwapień, J.; Drożdż, S.; Grümmer, F.; Ruf, F.; Speth, J.

    2002-06-01

    The correlation matrix formalism is used to study temporal aspects of the stock market evolution. This formalism allows to decompose the financial dynamics into noise as well as into some coherent repeatable intraday structures. The present study is based on the high-frequency Deutsche Aktienindex (DAX) data over the time period between November 1997 and September 1999, and makes use of both the corresponding returns as well as volatility variations. One principal conclusion is that a bulk of the stock market dynamics is governed by the uncorrelated noise-like processes. There exists, however, a small number of components of coherent short-term repeatable structures in fluctuations that may generate some memory effects seen in the standard autocorrelation function analysis. Laws that govern fluctuations associated with those various components are different, which indicates an extremely complex character of the financial fluctuations.

  1. Structure and dynamics of stock market in times of crisis

    NASA Astrophysics Data System (ADS)

    Zhao, Longfeng; Li, Wei; Cai, Xu

    2016-02-01

    Daily correlations among 322 S&P 500 constituent stocks are investigated by means of correlation-based (CB) network. By using the heterogeneous time scales, we identify global expansion and local clustering market behaviors during crises, which are mainly caused by community splits and inter-sector edge number decreases. The CB networks display distinctive community and sector structures. Graph edit distance is applied to capturing the dynamics of CB networks in which drastic structure reconfigurations can be observed during crisis periods. Edge statistics reveal the power-law nature of edges' duration time distribution. Despite the networks' strong structural changes during crises, we still find some long-duration edges that serve as the backbone of the stock market. Finally the dynamical change of network structure has shown its capability in predicting the implied volatility index (VIX).

  2. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 26 Internal Revenue 11 2010-04-01 2010-04-01 true Mark to market election for marketable stock. 1....1296-1 Mark to market election for marketable stock. (a) Definitions—(1) Eligible RIC. An eligible RIC... stock, the excess, if any, of— (A) The amount of mark to market gain included in gross income of...

  3. Examining the dynamic interactions on volatilities of paired stock markets

    NASA Astrophysics Data System (ADS)

    Lee, Jun Shean; Sek, Siok Kun

    2015-02-01

    We conduct empirical analyses to investigate the interaction between volatilities of paired stock markets. The main objective of this study is to reveal possibility of spillover effects among stock markets which can determine the performances of stock returns and trade volumes of stocks. In particular, we seek to investigate if there exist two-way causal relationships on the volatilities in two stock markets in two groups of countries, i.e. between emerging markets of ASEAN-5 and between emerging and advanced countries. Our study is focused in Malaysia stock market and the paired relationship with its neighbouring countries (ASEAN5) and advanced countries (Japan and U.S.) respectively. The multivariate GARCH(1,1) model is applied in studying the interactions on the volatilities of paired stock markets. The results are compared between neighbouring countries and with that of advanced countries. The results are expected to reveal linkages between volatilities of stock markets and the dynamic relationships across markets. The results provide useful information in studying the performances of stock markets and predicting the stock movements by incorporating the external impacts from foreign stock markets.

  4. 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

  5. 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. PMID:26435898

  6. 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.

  7. The Stock Performance of C. Everett Koop Award Winners Compared With the Standard & Poor's 500 Index

    PubMed Central

    Goetzel, Ron Z.; Fabius, Raymond; Fabius, Dan; Roemer, Enid C.; Thornton, Nicole; Kelly, Rebecca K.; Pelletier, Kenneth R.

    2016-01-01

    Objective: To explore the link between companies investing in the health and well-being programs of their employees and stock market performance. Methods: Stock performance of C. Everett Koop National Health Award winners (n = 26) was measured over time and compared with the average performance of companies comprising the Standard and Poor's (S&P) 500 Index. Results: The Koop Award portfolio outperformed the S&P 500 Index. In the 14-year period tracked (2000–2014), Koop Award winners’ stock values appreciated by 325% compared with the market average appreciation of 105%. Conclusions: This study supports prior and ongoing research demonstrating a higher market valuation—an affirmation of business success by Wall Street investors—of socially responsible companies that invest in the health and well-being of their workers when compared with other publicly traded firms. PMID:26716843

  8. Extreme values in the Chinese and American stock markets based on detrended fluctuation analysis

    NASA Astrophysics Data System (ADS)

    Cao, Guangxi; Zhang, Minjia

    2015-10-01

    This paper focuses on the comparative analysis of extreme values in the Chinese and American stock markets based on the detrended fluctuation analysis (DFA) algorithm using the daily data of Shanghai composite index and Dow Jones Industrial Average. The empirical results indicate that the multifractal detrended fluctuation analysis (MF-DFA) method is more objective than the traditional percentile method. The range of extreme value of Dow Jones Industrial Average is smaller than that of Shanghai composite index, and the extreme value of Dow Jones Industrial Average is more time clustering. The extreme value of the Chinese or American stock markets is concentrated in 2008, which is consistent with the financial crisis in 2008. Moreover, we investigate whether extreme events affect the cross-correlation between the Chinese and American stock markets using multifractal detrended cross-correlation analysis algorithm. The results show that extreme events have nothing to do with the cross-correlation between the Chinese and American stock markets.

  9. 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.

  10. Variable diffusion in stock market fluctuations

    NASA Astrophysics Data System (ADS)

    Hua, Jia-Chen; Chen, Lijian; Falcon, Liberty; McCauley, Joseph L.; Gunaratne, Gemunu H.

    2015-02-01

    We analyze intraday fluctuations in several stock indices to investigate the underlying stochastic processes using techniques appropriate for processes with nonstationary increments. The five most actively traded stocks each contains two time intervals during the day where the variance of increments can be fit by power law scaling in time. The fluctuations in return within these intervals follow asymptotic bi-exponential distributions. The autocorrelation function for increments vanishes rapidly, but decays slowly for absolute and squared increments. Based on these results, we propose an intraday stochastic model with linear variable diffusion coefficient as a lowest order approximation to the real dynamics of financial markets, and to test the effects of time averaging techniques typically used for financial time series analysis. We find that our model replicates major stylized facts associated with empirical financial time series. We also find that ensemble averaging techniques can be used to identify the underlying dynamics correctly, whereas time averages fail in this task. Our work indicates that ensemble average approaches will yield new insight into the study of financial markets' dynamics. Our proposed model also provides new insight into the modeling of financial markets dynamics in microscopic time scales.

  11. Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis

    NASA Astrophysics Data System (ADS)

    Gayo, W. S.; Urrutia, J. D.; Temple, J. M. F.; Sandoval, J. R. D.; Sanglay, J. E. A.

    2015-06-01

    This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers’ Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.

  12. Extracting hidden fluctuation patterns of Hang Seng stock index from network topologies

    NASA Astrophysics Data System (ADS)

    Li, Ping; Wang, Bing-Hong

    2007-05-01

    We present a model of complex network generated from Hang Seng index (HSI) of Hong Kong stock market, which encodes stock market relevant both interconnections and interactions between fluctuation patterns of HSI in the network topologies. In the network, the nodes (edges) represent all kinds of patterns of HSI fluctuation (their interconnections). Based on network topological statistic, we present efficient algorithms, measuring betweenness centrality ( BC) and inverse participation ratio ( IPR) of network adjacency matrix, for detecting topological important nodes. We have at least obtained three uniform nodes of topological importance, and find the three nodes, i.e. 18.7% nodes undertake 71.9% betweenness centrality and closely correlate other nodes. From these topological important nodes, we can extract hidden significant fluctuation patterns of HSI. We also find these patterns are independent the time intervals scales. The results contain important physical implication, i.e. the significant patterns play much more important roles in both information control and transport of stock market, and should be useful for us to more understand fluctuations regularity of stock market index. Moreover, we could conclude that Hong Kong stock market, rather than a random system, is statistically stable, by comparison to random networks.

  13. Time varying market efficiency of the GCC stock markets

    NASA Astrophysics Data System (ADS)

    Charfeddine, Lanouar; Khediri, Karim Ben

    2016-02-01

    This paper investigates the time-varying levels of weak-form market efficiency for the GCC stock markets over the period spanning from May 2005 to September 2013. We use two empirical approaches: (1) the generalized autoregressive conditional heteroscedasticity in mean (GARCH-M) model with state space time varying parameter (Kalman filter), and (2) a rolling technique sample test of the fractional long memory parameter d. As long memory estimation methods, we use the detrended fluctuation analysis (DFA) technique, the modified R/S statistic, the exact local whittle (ELW) and the feasible Exact Local Whittle (FELW) methods. Moreover, we use the Bai and Perron (1998, 2003) multiple structural breaks technique to test and date the time varying behavior of stock market efficiency. Empirical results show that GCC markets have different degrees of time-varying efficiency, and also have experiencing periods of efficiency improvement. Results also show evidence of structural breaks in all GCC markets. Moreover, we observe that the recent financial shocks such as Arab spring and subprime crises have a significant impact on the time path evolution of market efficiency.

  14. Fluctuations of trading volume in a stock market

    NASA Astrophysics Data System (ADS)

    Hong, Byoung Hee; Lee, Kyoung Eun; Hwang, Jun Kyung; Lee, Jae Woo

    2009-03-01

    We consider the probability distribution function of the trading volume and the volume changes in the Korean stock market. The probability distribution function of the trading volume shows double peaks and follows a power law, P(V/)∼( at the tail part of the distribution with α=4.15(4) for the KOSPI (Korea composite Stock Price Index) and α=4.22(2) for the KOSDAQ (Korea Securities Dealers Automated Quotations), where V is the trading volume and is the monthly average value of the trading volume. The second peaks originate from the increasing trends of the average volume. The probability distribution function of the volume changes also follows a power law, P(Vr)∼Vr-β, where Vr=V(t)-V(t-T) and T is a time lag. The exponents β depend on the time lag T. We observe that the exponents β for the KOSDAQ are larger than those for the KOSPI.

  15. Optimal investment horizons for stocks and markets

    NASA Astrophysics Data System (ADS)

    Johansen, A.; Simonsen, I.; Jensen, M. H.

    2006-10-01

    The inverse statistics is the distribution of waiting times needed to achieve a predefined level of return obtained from (detrended) historic asset prices [I. Simonsen, M.H. Jensen, A. Johansen, Eur. Phys. J. 27 (2002) 583; M.H. Jensen, A. Johansen, I. Simonsen, Physica A 234 (2003) 338]. Such a distribution typically goes through a maximum at a time coined the optimal investment horizon, τρ*, which defines the most likely waiting time for obtaining a given return ρ. By considering equal positive and negative levels of return, we reported in [M.H. Jensen, A. Johansen, I. Simonsen, Physica A 234 (2003) 338] on a quantitative gain/loss asymmetry most pronounced for short horizons. In the present paper, the inverse statistics for {2}/{3} of the individual stocks presently in the DJIA is investigated. We show that this gain/loss asymmetry established for the DJIA surprisingly is not present in the time series of the individual stocks nor their average. This observation points towards some kind of collective movement of the stocks of the index (synchronization).

  16. Effect of Trader Composition on Stock Market

    NASA Astrophysics Data System (ADS)

    Wang, Mo-Gei; Wang, Xing-Yuan; Liu, Zhen-Zhen

    2011-05-01

    In this study, we build a double auction market model, which contains two types of agent traders, i.e., the noise traders and fundamentalists, to investigate the effect of the trader composition on the stock market. It is found that, the non-trivial Hurst exponent and the fat-tailed distribution of transaction prices can be observed at any ratio of the noise traders. Analyses on the price variation properties, including the Hurst exponent and the price variation region, show that these properties are stable when the ratio is moderate. However, the non-price variation properties, including the trading volume and the profitability of the two kinds of agents, do not keep stable untrivially in any interval of the ratio of noise traders.

  17. Non-equilibrium stochastic model for stock exchange market

    NASA Astrophysics Data System (ADS)

    Kim, Yup; Kwon, Ikhyun; Yook, Soon-Hyung

    2013-12-01

    We study the effect of the topology of industrial relationship (IR) between the companies in a stock exchange market on the universal features in the market. For this we propose a stochastic model for stock exchange markets based on the behavior of technical traders. From the numerical simulations we measure the return distribution, P(R), and the autocorrelation function of the volatility, C(T), and find that the observed universal features in real financial markets are originated from the heterogeneity of IR network topology. Moreover, the heterogeneous IR topology can also explain Zipf-Pareto’s law for the distribution of market value of equity in the real stock exchange markets.

  18. Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chain

    PubMed Central

    Dai, Yonghui; Han, Dongmei; Dai, Weihui

    2014-01-01

    The stock index reflects the fluctuation of the stock market. For a long time, there have been a lot of researches on the forecast of stock index. However, the traditional method is limited to achieving an ideal precision in the dynamic market due to the influences of many factors such as the economic situation, policy changes, and emergency events. Therefore, the approach based on adaptive modeling and conditional probability transfer causes the new attention of researchers. This paper presents a new forecast method by the combination of improved back-propagation (BP) neural network and Markov chain, as well as its modeling and computing technology. This method includes initial forecasting by improved BP neural network, division of Markov state region, computing of the state transition probability matrix, and the prediction adjustment. Results of the empirical study show that this method can achieve high accuracy in the stock index prediction, and it could provide a good reference for the investment in stock market. PMID:24782659

  19. Using the Stock Market Game to Teach Economics.

    ERIC Educational Resources Information Center

    Lopus, Jane Schaerges

    1985-01-01

    The Stock Market Game is a computerized simulation that involves high school students in trading eligible New York Stock Exchange stocks in an effort to make capital gains. Time required is ten weeks. The game is described; economic concepts that can be taught using the game are listed. (RM)

  20. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 26 Internal Revenue 11 2011-04-01 2011-04-01 false Mark to market election for marketable stock. 1... election with respect to such stock for prior taxable years. For further guidance, see Notice 92-53 (1992-2... a calendar year taxpayer, owns marketable stock in FX, a PFIC that it acquired on January 1,...

  1. 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.

  2. Collective behavior of stock price movements in an emerging market

    NASA Astrophysics Data System (ADS)

    Pan, Raj Kumar; Sinha, Sitabhra

    2007-10-01

    To investigate the universality of the structure of interactions in different markets, we analyze the cross-correlation matrix C of stock price fluctuations in the National Stock Exchange (NSE) of India. We find that this emerging market exhibits strong correlations in the movement of stock prices compared to developed markets, such as the New York Stock Exchange (NYSE). This is shown to be due to the dominant influence of a common market mode on the stock prices. By comparison, interactions between related stocks, e.g., those belonging to the same business sector, are much weaker. This lack of distinct sector identity in emerging markets is explicitly shown by reconstructing the network of mutually interacting stocks. Spectral analysis of C for NSE reveals that, the few largest eigenvalues deviate from the bulk of the spectrum predicted by random matrix theory, but they are far fewer in number compared to, e.g., NYSE. We show this to be due to the relative weakness of intrasector interactions between stocks, compared to the market mode, by modeling stock price dynamics with a two-factor model. Our results suggest that the emergence of an internal structure comprising multiple groups of strongly coupled components is a signature of market development.

  3. Dollar and the stock market: An approach using Haar wavelet

    NASA Astrophysics Data System (ADS)

    Belardi, Aldo Artur; Aguiar, Renato A.

    2012-08-01

    This paper presents a methodology to detect significant changes in the price of U.S. dollar in regarding to the stock exchange using the Haar wavelet as well as statistical analyzes of several parameters. The data used arise of information provided by the stock market, both for the U.S. dollar and for the stock market. The results show that the applied methodology through Haar wavelet, are able to inform in advance the trend of the stock market through a single variable, the U.S. dollar.

  4. Analysis of stock market indices through multidimensional scaling

    NASA Astrophysics Data System (ADS)

    Machado, J. Tenreiro; Duarte, Fernando B.; Duarte, Gonçalo Monteiro

    2011-12-01

    We propose a graphical method to visualize possible time-varying correlations between fifteen stock market values. The method is useful for observing stable or emerging clusters of stock markets with similar behaviour. The graphs, originated from applying multidimensional scaling techniques (MDS), may also guide the construction of multivariate econometric models.

  5. Robot traders can prevent extreme events in complex stock markets

    NASA Astrophysics Data System (ADS)

    Suhadolnik, Nicolas; Galimberti, Jaqueson; Da Silva, Sergio

    2010-11-01

    If stock markets are complex, monetary policy and even financial regulation may be useless to prevent bubbles and crashes. Here, we suggest the use of robot traders as an anti-bubble decoy. To make our case, we put forward a new stochastic cellular automata model that generates an emergent stock price dynamics as a result of the interaction between traders. After introducing socially integrated robot traders, the stock price dynamics can be controlled, so as to make the market more Gaussian.

  6. 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.

  7. 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

  8. 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.

  9. Exploring Market State and Stock Interactions on the Minute Timescale.

    PubMed

    Tan, Lei; Chen, Jun-Jie; Zheng, Bo; Ouyang, Fang-Yan

    2016-01-01

    A stock market is a non-stationary complex system. The stock interactions are important for understanding the state of the market. However, our knowledge on the stock interactions on the minute timescale is limited. Here we apply the random matrix theory and methods in complex networks to study the stock interactions and sector interactions. Further, we construct a new kind of cross-correlation matrix to investigate the correlation between the stock interactions at different minutes within one trading day. Based on 50 million minute-to-minute price data in the Shanghai stock market, we discover that the market states in the morning and afternoon are significantly different. The differences mainly exist in three aspects, i.e. the co-movement of stock prices, interactions of sectors and correlation between the stock interactions at different minutes. In the afternoon, the component stocks of sectors are more robust and the structure of sectors is firmer. Therefore, the market state in the afternoon is more stable. Furthermore, we reveal that the information of the sector interactions can indicate the financial crisis in the market, and the indicator based on the empirical data in the afternoon is more effective. PMID:26900948

  10. Exploring Market State and Stock Interactions on the Minute Timescale

    PubMed Central

    Tan, Lei; Chen, Jun-Jie; Zheng, Bo; Ouyang, Fang-Yan

    2016-01-01

    A stock market is a non-stationary complex system. The stock interactions are important for understanding the state of the market. However, our knowledge on the stock interactions on the minute timescale is limited. Here we apply the random matrix theory and methods in complex networks to study the stock interactions and sector interactions. Further, we construct a new kind of cross-correlation matrix to investigate the correlation between the stock interactions at different minutes within one trading day. Based on 50 million minute-to-minute price data in the Shanghai stock market, we discover that the market states in the morning and afternoon are significantly different. The differences mainly exist in three aspects, i.e. the co-movement of stock prices, interactions of sectors and correlation between the stock interactions at different minutes. In the afternoon, the component stocks of sectors are more robust and the structure of sectors is firmer. Therefore, the market state in the afternoon is more stable. Furthermore, we reveal that the information of the sector interactions can indicate the financial crisis in the market, and the indicator based on the empirical data in the afternoon is more effective. PMID:26900948

  11. Exploring Market State and Stock Interactions on the Minute Timescale.

    PubMed

    Tan, Lei; Chen, Jun-Jie; Zheng, Bo; Ouyang, Fang-Yan

    2016-01-01

    A stock market is a non-stationary complex system. The stock interactions are important for understanding the state of the market. However, our knowledge on the stock interactions on the minute timescale is limited. Here we apply the random matrix theory and methods in complex networks to study the stock interactions and sector interactions. Further, we construct a new kind of cross-correlation matrix to investigate the correlation between the stock interactions at different minutes within one trading day. Based on 50 million minute-to-minute price data in the Shanghai stock market, we discover that the market states in the morning and afternoon are significantly different. The differences mainly exist in three aspects, i.e. the co-movement of stock prices, interactions of sectors and correlation between the stock interactions at different minutes. In the afternoon, the component stocks of sectors are more robust and the structure of sectors is firmer. Therefore, the market state in the afternoon is more stable. Furthermore, we reveal that the information of the sector interactions can indicate the financial crisis in the market, and the indicator based on the empirical data in the afternoon is more effective.

  12. The US stock market leads the federal funds rate and treasury bond yields.

    PubMed

    Guo, Kun; Zhou, Wei-Xing; Cheng, Si-Wei; Sornette, Didier

    2011-01-01

    Using a recently introduced method to quantify the time-varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P 500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started in mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen as key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P 500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis. PMID:21857954

  13. The US Stock Market Leads the Federal Funds Rate and Treasury Bond Yields

    PubMed Central

    Guo, Kun; Zhou, Wei-Xing; Cheng, Si-Wei; Sornette, Didier

    2011-01-01

    Using a recently introduced method to quantify the time-varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P 500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started in mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen as key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P 500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis. PMID:21857954

  14. An information flow among industry sectors in the Korean stock market

    NASA Astrophysics Data System (ADS)

    Oh, Gabjin; Oh, Tamina; Kim, Hoyong; Kwon, Okyu

    2014-12-01

    We investigate the information flow among 22 industry sectors in the Korean stock market by using the symbolic transfer entropy (STE) method. We consider the daily index of 22 industry sectors in the Korean Composite Stock Price Index (KOSPI) from January 3, 2000 to March 30, 2012. We measure the degree of asymmetry in the information flow and the amount of information flow among the industry sectors before, during, and after the subprime crisis in order to analyze how to relate them to the market crisis. We find that the amount of information flow and the number of connectedness during the financial crisis in the Korean stock market are higher than those before and after the market crisis. In addition, we find the role of the insurance sector, which is related to risk management, increases as information source after the crisis.

  15. 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.

  16. Novel indexes based on network structure to indicate financial market

    NASA Astrophysics Data System (ADS)

    Zhong, Tao; Peng, Qinke; Wang, Xiao; Zhang, Jing

    2016-02-01

    There have been various achievements to understand and to analyze the financial market by complex network model. However, current studies analyze the financial network model but seldom present quantified indexes to indicate or forecast the price action of market. In this paper, the stock market is modeled as a dynamic network, in which the vertices refer to listed companies and edges refer to their rank-based correlation based on price series. Characteristics of the network are analyzed and then novel indexes are introduced into market analysis, which are calculated from maximum and fully-connected subnets. The indexes are compared with existing ones and the results confirm that our indexes perform better to indicate the daily trend of market composite index in advance. Via investment simulation, the performance of our indexes is analyzed in detail. The results indicate that the dynamic complex network model could not only serve as a structural description of the financial market, but also work to predict the market and guide investment by indexes.

  17. 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. PMID:27257816

  18. 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.

  19. 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

  20. 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.

  1. Cross-response in correlated financial markets: individual stocks

    NASA Astrophysics Data System (ADS)

    Wang, Shanshan; Schäfer, Rudi; Guhr, Thomas

    2016-04-01

    Previous studies of the stock price response to trades focused on the dynamics of single stocks, i.e. they addressed the self-response. We empirically investigate the price response of one stock to the trades of other stocks in a correlated market, i.e. the cross-responses. How large is the impact of one stock on others and vice versa? - This impact of trades on the price change across stocks appears to be transient instead of permanent as we discuss from the viewpoint of market efficiency. Furthermore, we compare the self-responses on different scales and the self- and cross-responses on the same scale. We also find that the cross-correlation of the trade signs turns out to be a short-memory process.

  2. Topological properties of stock market networks: The case of Brazil

    NASA Astrophysics Data System (ADS)

    Tabak, Benjamin M.; Serra, Thiago R.; Cajueiro, Daniel O.

    2010-08-01

    This paper investigates the topological properties of the Brazilian stock market networks. We build the minimum spanning tree, which is based on the concept of ultrametricity, using the correlation matrix for a variety of stocks of different sectors. Our results suggest that stocks tend to cluster by sector. We employ a dynamic approach using complex network measures and find that the relative importance of different sectors within the network varies. The financial, energy and material sectors are the most important within the network.

  3. 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

  4. 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.

  5. Comparing Tehran STOCK Exchange as AN Emerging Market with a Mature Market by Random Matrix Approach

    NASA Astrophysics Data System (ADS)

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

    We analyze cross-correlation between return fluctuations of stocks of an emerging market by using random matrix theory (RMT). We test the statistics of eigenvalues of cross-correlation (C) between stocks of the Tehran Price Index (TEPIX) as an emerging market and compare these with a mature market (US market). According to the "null hypothesis," a random correlation matrix constructed from mutually uncorrelated time series, the deviation from the Gaussian orthogonal ensemble of RTM is a good criterion. We find that a majority of the eigenvalues of C fall within the bulk (RMT bounds between λ+ and λ-) for the eigenvalues of the random correlation matrices. Further, we find that the distribution of eigenvector components for the eigenvectors corresponding to the largest deviating eigenvalues, display systematic deviations from the RMT prediction. Analyzing the components of the deviating eigenvectors by Inverse Participation Ratio, leads us to know that the largest eigenvalue corresponds to an influence common to the whole market. Our analysis of the other deviating eigenvectors shows distinct industries, whose identities corresponds to the structure of the Iran business environment.

  6. Visualization of a stock market correlation matrix

    NASA Astrophysics Data System (ADS)

    Rea, Alethea; Rea, William

    2014-04-01

    This paper presents a novel application of Neighbor-Net, a clustering algorithm developed for constructing a phylogenetic network in the field of evolutionary biology, to visualizing a correlation matrix. We apply Neighbor-Net as implemented in the SplitsTree software package to 48 stocks listed on the New Zealand Stock Exchange. We show that by visualizing the correlation matrix using a Neighbor-Net splits graph and its associated circular ordering of the stocks that some of the problems associated with understanding the large number of correlations between the individual stocks can be overcome. We compare the visualization of Neighbor-Net with that provided by hierarchical clustering trees and minimum spanning trees. The use of Neighbor-Net networks, or splits graphs, yields greater insight into how closely individual stocks are related to each other in terms of their correlations and suggests new avenues of research into how to construct small diversified stock portfolios.

  7. Frustration driven stock market dynamics: Leverage effect and asymmetry

    NASA Astrophysics Data System (ADS)

    Ahlgren, Peter Toke Heden; Jensen, Mogens H.; Simonsen, Ingve; Donangelo, Raul; Sneppen, Kim

    2007-09-01

    By applying inverse statistics to financial data it has recently been found from empirical studies that indices exhibit a pronounced gain-loss asymmetry [M.H. Jensen, Phys. Rev. Lett. 83 (1999) 76; I. Simonsen, M.H. Jensen, A. Johansen, Eur. Phys. J. B 27 (2002) 583; M.H. Jensen, A. Johansen, I. Simonsen, Physica A 324 (2003) 338]. This gain-loss asymmetry appears to have some similarities with the stylized fact leverage effect and we investigate if they could be of same origin. For this purpose we introduce the Frustration Governed Market model which includes correlations in time between a model index and its individual stocks. It is shown that the model reproduces very well the empirical findings with respect to gain-loss asymmetry and leverage. In special cases, however, the model may produce leverage without a pronounced gain-loss asymmetry.

  8. Learning from the Market: Integrating "The Stock Market Game" (tm) across the Curriculum. EconomicsAmerica.

    ERIC Educational Resources Information Center

    National Council on Economic Education, New York, NY.

    This book is designed to help teachers connect "The Stock Market Game" (tm) and the school curriculum. Three key economic themes developed in the lessons include: (1) stock buyers engage in economizing behavior; (2) market economies encourage the production of wealth; and (3) market activity takes place in the context of a legal environment in…

  9. 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.

  10. Granger causality stock market networks: Temporal proximity and preferential attachment

    NASA Astrophysics Data System (ADS)

    Výrost, Tomáš; Lyócsa, Štefan; Baumöhl, Eduard

    2015-06-01

    The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-samples revealed three significant findings. First, after the recent financial crisis the impact of the US stock market has declined. Second, spatial probit models confirmed the role of the temporal proximity between market closing times for return spillovers, i.e. the time distance between national stock markets matters. Third, a preferential attachment between stock markets exists, i.e. the probability of the presence of spillover effects between any given two markets increases with their degree of connectedness to others.

  11. 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.

  12. Evolution of Shanghai STOCK Market Based on Maximal Spanning Trees

    NASA Astrophysics Data System (ADS)

    Yang, Chunxia; Shen, Ying; Xia, Bingying

    2013-01-01

    In this paper, using a moving window to scan through every stock price time series over a period from 2 January 2001 to 11 March 2011 and mutual information to measure the statistical interdependence between stock prices, we construct a corresponding weighted network for 501 Shanghai stocks in every given window. Next, we extract its maximal spanning tree and understand the structure variation of Shanghai stock market by analyzing the average path length, the influence of the center node and the p-value for every maximal spanning tree. A further analysis of the structure properties of maximal spanning trees over different periods of Shanghai stock market is carried out. All the obtained results indicate that the periods around 8 August 2005, 17 October 2007 and 25 December 2008 are turning points of Shanghai stock market, at turning points, the topology structure of the maximal spanning tree changes obviously: the degree of separation between nodes increases; the structure becomes looser; the influence of the center node gets smaller, and the degree distribution of the maximal spanning tree is no longer a power-law distribution. Lastly, we give an analysis of the variations of the single-step and multi-step survival ratios for all maximal spanning trees and find that two stocks are closely bonded and hard to be broken in a short term, on the contrary, no pair of stocks remains closely bonded for a long time.

  13. A quantum-like approach to the stock market

    NASA Astrophysics Data System (ADS)

    Aerts, Diederik; D'Hooghe, Bart; Sozzo, Sandro

    2012-03-01

    Modern approaches to stock pricing in quantitative finance are typically founded on the Black-Scholes model and the underlying random walk hypothesis. Empirical data indicate that this hypothesis works well in stable situations but, in abrupt transitions such as during an economical crisis, the random walk model fails and alternative descriptions are needed. For this reason, several proposals have been recently forwarded which are based on the formalism of quantum mechanics. In this paper we apply the SCoP formalism, elaborated to provide an operational foundation of quantum mechanics, to the stock market. We argue that a stock market is an intrinsically contextual system where agents' decisions globally influence the market system and stocks prices, determining a nonclassical behavior. More specifically, we maintain that a given stock does not generally have a definite value, e.g., a price, but its value is actualized as a consequence of the contextual interactions in the trading process. This contextual influence is responsible of the non-Kolmogorovian quantumlike behavior of the market at a statistical level. Then, we propose a sphere model within our hidden measurement formalism that describes a buying/selling process of a stock and shows that it is intuitively reasonable to assume that the stock has not a definite price until it is traded. This result is relevant in our opinion since it provides a theoretical support to the use of quantum models in finance.

  14. On the integrated behaviour of non-stationary volatility in stock markets

    NASA Astrophysics Data System (ADS)

    Dionisio, Andreia; Menezes, Rui; Mendes, Diana A.

    2007-08-01

    This paper analyses the behaviour of volatility for several international stock market indexes, namely the SP 500 (USA), the Nikkei (Japan), the PSI 20 (Portugal), the CAC 40 (France), the DAX 30 (Germany), the FTSE 100 (UK), the IBEX 35 (Spain) and the MIB 30 (Italy), in the context of non-stationarity. Our empirical results point to the evidence of the existence of integrated behaviour among several of those stock market indexes of different dimensions. It seems, therefore, that the behaviour of these markets tends to some uniformity, which can be interpreted as the existence of a similar behaviour facing to shocks that may affect the worldwide economy. Whether this is a cause or a consequence of market globalization is an issue that may be stressed in future work.

  15. 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.

  16. Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

    NASA Astrophysics Data System (ADS)

    Yin, Yi; Shang, Pengjian

    2014-06-01

    In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and

  17. Evidence of a worldwide stock market log-periodic anti-bubble since mid-2000

    NASA Astrophysics Data System (ADS)

    Zhou, Wei-Xing; Sornette, Didier

    2003-12-01

    Following our investigation of the USA Standard and Poor index anti-bubble that started in August 2000 (Quant. Finance 2 (2002) 468), we analyze 38 world stock market indices and identify 21 “bearish anti-bubbles” and six “bullish anti-bubbles”. An “anti-bubble” is defined as a self-reinforcing price trajectory with self-similar expanding log-periodic oscillations. Mathematically, a bearish anti-bubble is characterize by a power law decrease of the price (or of the logarithm of the price) as a function of time and by expanding log-periodic oscillations. We propose that bearish anti-bubbles are created by positive price-to-price feedbacks feeding overall pessimism and negative market sentiment further strengthened by inter-personal interactions. Bullish anti-bubbles are here identified for the first time. The most striking discovery is that the majority of European and Western stock market indices as well as other stock indices exhibit practically the same log-periodic power law anti-bubble structure as found for the USA S&P500 index. These anti-bubbles are found to start approximately at the same time, August 2000, in all these markets. This shows a remarkable degree of worldwide synchronization. The descent of the worldwide stock markets since 2000 is thus an international event, suggesting the strengthening of globalization.

  18. 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

  19. Quantifying price fluctuations in the Brazilian stock market

    NASA Astrophysics Data System (ADS)

    Tabak, B. M.; Takami, M. Y.; Cajueiro, D. O.; Petitinga, A.

    2009-01-01

    This paper investigates price fluctuations in the Brazilian stock market. We employ a recently developed methodology to test whether the Brazilian stock price returns present a power law distribution and find that we cannot reject such behavior. Empirical results for sub-partitions of the time series suggests that for most of the time the power law is not rejected, but that in some cases the data set does not conform with a power law distribution.

  20. 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.

  1. Volatility transmission among Latin American stock markets under structural breaks

    NASA Astrophysics Data System (ADS)

    Güloğlu, Bülent; Kaya, Pınar; Aydemir, Resul

    2016-11-01

    The paper investigates the volatility spillovers among five major Latin American (LA) stock markets under the presence of the structural breaks in variance. We employ a multivariate dynamic conditional correlation (DCC GARCH) model allowing for structural breaks in variance. The dynamic correlations show that volatility spillover effects among the markets are not strong. Causality in mean tests indicate one way causality from BOVESPA to all markets, whereas causality in variance tests indicate one way causality only from BOVESPA to IPSA. These findings suggest that while the markets in the sample are interdependent, there is not enough statistical evidence to infer the contagion effects among the markets.

  2. Quantifying the semantics of search behavior before stock market moves

    PubMed Central

    Curme, Chester; Preis, Tobias; Stanley, H. Eugene; Moat, Helen Susannah

    2014-01-01

    Technology is becoming deeply interwoven into the fabric of society. The Internet has become a central source of information for many people when making day-to-day decisions. Here, we present a method to mine the vast data Internet users create when searching for information online, to identify topics of interest before stock market moves. In an analysis of historic data from 2004 until 2012, we draw on records from the search engine Google and online encyclopedia Wikipedia as well as judgments from the service Amazon Mechanical Turk. We find evidence of links between Internet searches relating to politics or business and subsequent stock market moves. In particular, we find that an increase in search volume for these topics tends to precede stock market falls. We suggest that extensions of these analyses could offer insight into large-scale information flow before a range of real-world events. PMID:25071193

  3. Principle Fluctuation Modes of the Global Stock Market

    NASA Astrophysics Data System (ADS)

    Yan, Yan; Liu, Mao-Xin; Zhu, Xiao-Wu; Chen, Xiao-Song

    2012-02-01

    The purpose of this work is to study the principle fluctuation modes of the global stock market, which is regarded as a complex system. It is proposed that the systematic risk can be reflected by the trace calculated from the cross-correlation matrix, and the integrity can be classified into clusters according to the plus-minus signs of the elements of the eigenvectors corresponding to several top largest eigenvalues whose total value accounts for more than 60 percent of the trace. The principle fluctuation modes of 30 stock markets are in the same direction in each year of 2005-2010. According to the classification criteria proposed here, the stock markets of the Americas, Europe and Asia & Oceania are automatically classified into different clusters, while Brazil, Russia and China are separated.

  4. Quantifying the semantics of search behavior before stock market moves.

    PubMed

    Curme, Chester; Preis, Tobias; Stanley, H Eugene; Moat, Helen Susannah

    2014-08-12

    Technology is becoming deeply interwoven into the fabric of society. The Internet has become a central source of information for many people when making day-to-day decisions. Here, we present a method to mine the vast data Internet users create when searching for information online, to identify topics of interest before stock market moves. In an analysis of historic data from 2004 until 2012, we draw on records from the search engine Google and online encyclopedia Wikipedia as well as judgments from the service Amazon Mechanical Turk. We find evidence of links between Internet searches relating to politics or business and subsequent stock market moves. In particular, we find that an increase in search volume for these topics tends to precede stock market falls. We suggest that extensions of these analyses could offer insight into large-scale information flow before a range of real-world events.

  5. Quantifying Wikipedia Usage Patterns Before Stock Market Moves

    NASA Astrophysics Data System (ADS)

    Moat, Helen Susannah; Curme, Chester; Avakian, Adam; Kenett, Dror Y.; Stanley, H. Eugene; Preis, Tobias

    2013-05-01

    Financial crises result from a catastrophic combination of actions. Vast stock market datasets offer us a window into some of the actions that have led to these crises. Here, we investigate whether data generated through Internet usage contain traces of attempts to gather information before trading decisions were taken. We present evidence in line with the intriguing suggestion that data on changes in how often financially related Wikipedia pages were viewed may have contained early signs of stock market moves. Our results suggest that online data may allow us to gain new insight into early information gathering stages of decision making.

  6. 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.

  7. Cross-correlations between West Texas Intermediate crude oil and the stock markets of the BRIC

    NASA Astrophysics Data System (ADS)

    Ma, Feng; Wei, Yu; Huang, Dengshi; Zhao, Lin

    2013-11-01

    In this paper, we investigate the cross-correlation properties between West Texas Intermediate crude oil and the stock markets of the BRIC. We use not only the qualitative analysis of the cross-correlation test, but also take the quantitative analysis of the MF-DXA, confirming the cross-correlation relationship between West Texas Intermediate crude oil and the stock markets of the BRIC (Brazil, Russia, India and China) respectively, which have strongly multifractal features, and the cross-correlations are more strongly multifractal in the short term than in the long term. Furthermore, based on the multifractal spectrum, we also find the multifractality strength between the crude oil WTI and Chinese stock market is stronger than the multifractality strength of other pairs. Based on the Iraq war (Mar 20, 2003) and the Financial crisis in 2008, we divide sample period into four segments to research the degree of the multifractal (ΔH) and the market efficiency (and the risk). Finally, we employ the technique of the rolling window to calculate the time-varying EI (efficiency index) and dependent on the EI, we can easily observe the change of stock markets. Furthermore, we explore the relationship between bivariate cross-correlation exponents (Hxy(q)) and the generalized Hurst exponents.

  8. 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.

  9. 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.

  10. Spillover effects of oil price shocks across stock markets

    NASA Astrophysics Data System (ADS)

    Ng, Zhan Jian; Sek, Siok Kun

    2014-12-01

    Oil price shock can impose detrimental effects to an economy. In this study, we empirically study the spillover effects of oil price shock on determining volatilities of stock markets across the main oil importing and oil producing countries. In particular, we are interested to compare the relative impact of oil price shock on the volatilities of stock markets and how each stock market reacts to oil price shock for oil importing and oil producing countries. We focus the study in four main oil importer and four oil producers respectively using the daily data starting from January 2009 to December 2013. The multivariate GARCH(1,1) model is applied for the purpose of this study. The results of the study suggest that there exist spillover effect between crude oil price and stock returns for all the countries. The short run persistency of spillover effect in oil-exporting countries is lower than oil-importing countries but the long run persistency of spillover effect in oil-exporting countries is higher than oil-importing countries. In general the short run persistency is smaller and the long run persistency is very high. The results hold for volatility of oil price and stock returns and also spillover volatility in all countries.

  11. Stroke: a Hidden Danger of Margin Trading in Stock Markets.

    PubMed

    Lin, Shu-Hui; Wang, Chien-Ho; Liu, Tsai-Ching; Chen, Chin-Shyan

    2015-10-01

    Using 10-year population data from 2000 through 2009 in Taiwan, this is the first paper to analyze the relationship between margin trading in stock markets and stroke hospitalizations. The results show that 3 and 6 days after an increase of margin trading in the Taiwan stock markets are associated with greater stoke hospitalizations. In general, a 1 % increase in total margin trading positions is associated with an increment of 2.5 in the total number of stroke hospitalizations, where the mean number of hospital admissions is 233 cases a day. We further examine the effects of margin trading by gender and age groups and find that the effects of margin trading are significant for males and those who are 45-74 years old only. In summary, buying stocks with money you do not have is quite risky, especially if the prices of those stocks fall past a certain level or if there is a sudden and severe drop in the stock market. There is also a hidden danger to one's health from margin trading. A person should be cautious before conducting margin trading, because while it can be quite profitable, danger always lurks just around the corner.

  12. Index Cohesive Force Analysis Reveals That the US Market Became Prone to Systemic Collapses Since 2002

    PubMed Central

    Kenett, Dror Y.; Shapira, Yoash; Madi, Asaf; Bransburg-Zabary, Sharron; Gur-Gershgoren, Gitit; Ben-Jacob, Eshel

    2011-01-01

    Background The 2007–2009 financial crisis, and its fallout, has strongly emphasized the need to define new ways and measures to study and assess the stock market dynamics. Methodology/Principal Findings The S&P500 dynamics during 4/1999–4/2010 is investigated in terms of the index cohesive force (ICF - the balance between the stock correlations and the partial correlations after subtraction of the index contribution), and the Eigenvalue entropy of the stock correlation matrices. We found a rapid market transition at the end of 2001 from a flexible state of low ICF into a stiff (nonflexible) state of high ICF that is prone to market systemic collapses. The stiff state is also marked by strong effect of the market index on the stock-stock correlations as well as bursts of high stock correlations reminiscence of epileptic brain activity. Conclusions/Significance The market dynamical states, stability and transition between economic states was studies using new quantitative measures. Doing so shed new light on the origin and nature of the current crisis. The new approach is likely to be applicable to other classes of complex systems from gene networks to the human brain. PMID:21556323

  13. 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.

  14. Multiscale multifractal time irreversibility analysis of stock markets

    NASA Astrophysics Data System (ADS)

    Jiang, Chenguang; Shang, Pengjian; Shi, Wenbin

    2016-11-01

    Time irreversibility is one of the most important properties of nonstationary time series. Complex time series often demonstrate even multiscale time irreversibility, such that not only the original but also coarse-grained time series are asymmetric over a wide range of scales. We study the multiscale time irreversibility of time series. In this paper, we develop a method called multiscale multifractal time irreversibility analysis (MMRA), which allows us to extend the description of time irreversibility to include the dependence on the segment size and statistical moments. We test the effectiveness of MMRA in detecting multifractality and time irreversibility of time series generated from delayed Henon map and binomial multifractal model. Then we employ our method to the time irreversibility analysis of stock markets in different regions. We find that the emerging market has higher multifractality degree and time irreversibility compared with developed markets. In this sense, the MMRA method may provide new angles in assessing the evolution stage of stock markets.

  15. High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets

    NASA Astrophysics Data System (ADS)

    Chen, Tai-Liang; Cheng, Ching-Hsue; Teoh, Hia-Jong

    2008-02-01

    Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-series, which factors linear relationships between recent periods of stock prices and fuzzy logical relationships (nonlinear relationships) mined from time-series into forecasting processes. In empirical analysis, the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) and HSI (Heng Seng Index) are employed as experimental datasets, and four recent fuzzy time-series models, Chen’s (1996), Yu’s (2005), Cheng’s (2006) and Chen’s (2007), are used as comparison models. Besides, to compare with conventional statistic method, the method of least squares is utilized to estimate the auto-regressive models of the testing periods within the databases. From analysis results, the performance comparisons indicate that the multi-period adaptation model, proposed in this paper, can effectively improve the forecasting performance of conventional fuzzy time-series models which only factor fuzzy logical relationships in forecasting processes. From the empirical study, the traditional statistic method and the proposed model both reveal that stock price patterns in the Taiwan stock and Hong Kong stock markets are short-term.

  16. Identifying the Bottom Line after a Stock Market Crash

    NASA Astrophysics Data System (ADS)

    Roehner, B. M.

    In this empirical paper we show that in the months following a crash there is a distinct connection between the fall of stock prices and the increase in the range of interest rates for a sample of bonds. This variable, which is often referred to as the interest rate spread variable, can be considered as a statistical measure for the disparity in lenders' opinions about the future; in other words, it provides an operational definition of the uncertainty faced by economic agents. The observation that there is a strong negative correlation between stock prices and the spread variable relies on the examination of eight major crashes in the United States between 1857 and 1987. That relationship which has remained valid for one and a half century in spite of important changes in the organization of financial markets can be of interest in the perspective of Monte Carlo simulations of stock markets.

  17. Fractal Analysis of Prime Indian STOCK Market Indices

    NASA Astrophysics Data System (ADS)

    Samadder, Swetadri; Ghosh, Koushik; Basu, Tapasendra

    2013-03-01

    The purpose of the present work is to study the fractal behaviour of prime Indian stock exchanges, namely Bombay Stock Exchange Sensitivity Index (BSE Sensex) and National Stock Exchange (NSE). To analyze the monofractality of these indices we have used Higuchi method and Katz method separately. By applying Mutifractal Detrended Fluctuation Analysis (MFDFA) technique we have calculated the generalized Hurst exponents, multifractal scaling exponents and generalized multifractal dimensions for the present indices. We have deduced Hölder exponents as well as singularity spectra for BSE and NSE. It has been observed that both the stock exchanges are possessing self-similarity at different small ranges separately and inhomogeneously. By comparing the multifractal behaviour of the BSE and NSE indices, we have found that the second one exhibits a richer multifractal feature than the first one.

  18. Testing for contagion under asymmetric dynamics: Evidence from the stock markets between US and Taiwan

    NASA Astrophysics Data System (ADS)

    Wang, Kuan-Min; Nguyen Thi, Thanh-Binh

    2007-03-01

    This article is an attempt to test, through the use of forward forecasting test on dynamic conditional correlation (DCC), for contagion between Taiwan and US stocks under asymmetry. The process includes three steps. The first step uses the iterated cumulative sums of squares (ICSS) algorithm to detect the structural breaks of market return. The second step creates dummy variables for breaks, estimates EGARCH model of conditional generalized error distribution, and computes dynamic conditional correlation coefficients of DCC multivariate GARCH model. The third step employs one-step and N-step forecast test to check for contagion effect. The evidences prove the asymmetric leverage effect of Taiwan weighted stock index and New York-NYSE Composite Index. Interestingly, we discovered that there are two kinds of contagion, “positive” and “negative”, between markets.

  19. The Stock Market and Economic Principles: A Curriculum Project.

    ERIC Educational Resources Information Center

    Savino, Ronald J.

    This paper outlines how to teach macroeconomic principles through mock stock market investing while helping students develop economic awareness, interest, and comprehension on a more sophisticated level. The basic textbook is "The Economy Today" (B. R. Schiller). After two weeks of teaching basic economic concepts and vocabulary, such as…

  20. Efficiency of Thai stock markets: Detrended fluctuation analysis

    NASA Astrophysics Data System (ADS)

    Sukpitak, Jessada; Hengpunya, Varagorn

    2016-09-01

    The evolution of Hurst exponent of SET index over time, as a measure of market efficiency, is examined by DFA method. It is found that, during the study period, Hurst exponent tends to decrease to the ideal value 0.5, i.e., the market becomes more efficient. This finding readily conforms to the assertion that emerging markets are becoming more efficient. Additionally, the development of Hurst exponent during November 2006 to March 2015 of SET index compared to MAI index is investigated. The result shows that the deviation of the Hurst exponent from 0.5 for the MAI index is larger than that of the SET index. This implies that SET is more efficient than MAI and thus supports the assumption that market capitalization has significant influence on market efficiency.

  1. Predictability of multifractal analysis of Hang Seng stock index in Hong Kong

    NASA Astrophysics Data System (ADS)

    Sun, Xia; Chen, Huiping; Yuan, Yongzhuang; Wu, Ziqin

    2001-12-01

    In this paper, the daily Hang Seng index in Hong Kong stock market is studied by multifractal analysis. The main parameter of multifractal spectra used is Δ f, which can be used to characterize the ratio of number of highest index moments to that of lowest ones. The dependence of today's gain probability ( G%) and the day's index increase probability ( n%) with Δ f of the previous 3 days are studied. It is found that G% and n% can reach 70-80% at the large positive Δ f region and can be very close to 20% at the big negative Δ f region. The predictability decreases with the increasing number of the previous days.

  2. Unraveling chaotic attractors by complex networks and measurements of stock market complexity.

    PubMed

    Cao, Hongduo; Li, Ying

    2014-03-01

    We present a novel method for measuring the complexity of a time series by unraveling a chaotic attractor modeled on complex networks. The complexity index R, which can potentially be exploited for prediction, has a similar meaning to the Kolmogorov complexity (calculated from the Lempel-Ziv complexity), and is an appropriate measure of a series' complexity. The proposed method is used to research the complexity of the world's major capital markets. None of these markets are completely random, and they have different degrees of complexity, both over the entire length of their time series and at a level of detail. However, developing markets differ significantly from mature markets. Specifically, the complexity of mature stock markets is stronger and more stable over time, whereas developing markets exhibit relatively low and unstable complexity over certain time periods, implying a stronger long-term price memory process.

  3. Another type of log-periodic oscillations on Polish stock market

    NASA Astrophysics Data System (ADS)

    Gnaciński, Piotr; Makowiec, Danuta

    2004-12-01

    Log-periodic oscillations have been used to predict price trends and crashes on financial markets. So far two types of log-periodic oscillations have been associated with the real markets. The first type oscillations accompany a rising market and end in a crash. The second type oscillations, called “anti-bubbles” appear after a crash, when the prices decrease. Here, we propose the third type of log-periodic oscillations, where an exogenous crash initiates a log-periodic behavior of the market, and the market is bullish. The critical time is at the beginning of the oscillations. Such behavior has been identified on Polish stock market index WIG between the “Russian crisis” (August 1998) and the “New Economy crash” in April 2000.

  4. Geography and distance effect on financial dynamics in the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Li, Xing; Qiu, Tian; Chen, Guang; Zhong, Li-Xin; Jiang, Xiong-Fei

    2016-09-01

    Geography effect is investigated for the Chinese stock market including the Shanghai and Shenzhen stock markets, based on the daily data of individual stocks. The stocks in the Shanghai city and the Guangdong province are found to greatly contribute to the Shanghai and Shenzhen markets in the geographical sector, respectively. By investigating a geographical correlation on a geographical parameter, the stock location is found to have an impact on the financial dynamics, except for the financial crisis time of the Shenzhen market. Stock distance effect is further studied, with the probability of the short distance observed to be much greater than that of the long distance. The distance is found to only affect the stock correlation of the Shanghai stock market, but has no effect on the Shenzhen stock market.

  5. Prediction of stock market characteristics using neural networks

    NASA Astrophysics Data System (ADS)

    Pandya, Abhijit S.; Kondo, Tadashi; Shah, Trupti U.; Gandhi, Viraf R.

    1999-03-01

    International stocks trading, currency and derivative contracts play an increasingly important role for many investors. Neural network is playing a dominant role in predicting the trends in stock markets and in currency speculation. In most economic applications, the success rate using neural networks is limited to 70 - 80%. By means of the new approach of GMDH (Group Method of Data Handling) neural network predictions can be improved further by 10 - 15%. It was observed in our study, that using GMDH for short, noisy or inaccurate data sample resulted in the best-simplified model. In the GMDH model accuracy of prediction is higher and the structure is simpler than that of the usual full physical model. As an example, prediction of the activity on the stock exchange in New York was considered. On the basis of observations in the period of Jan '95 to July '98, several variables of the stock market (S&P 500, Small Cap, Dow Jones, etc.) were predicted. A model portfolio using various stocks (Amgen, Merck, Office Depot, etc.) was built and its performance was evaluated based on neural network forecasting of the closing prices. Comparison of results was made with various neural network models such as Multilayer Perceptrons with Back Propagation, and the GMDH neural network. Variations of GMDH were studied and analysis of their performance is reported in the paper.

  6. Cointegration analysis and influence rank—A network approach to global stock markets

    NASA Astrophysics Data System (ADS)

    Yang, Chunxia; Chen, Yanhua; Niu, Lei; Li, Qian

    2014-04-01

    In this paper, cointegration relationships among 26 global stock market indices over the periods of sub-prime and European debt crisis and their influence rank are investigated by constructing and analyzing directed and weighted cointegration networks. The obtained results are shown as follows: the crises have changed cointegration relationships among stock market indices, their cointegration relationship increased after the Lehman Brothers collapse, while the degree of cointegration gradually decreased from the sub-prime to European debt crisis. The influence of US, Japan and China market indices are entirely distinguished over different periods. Before European debt crisis US stock market is a ‘global factor’ which leads the developed and emerging markets, while the influence of US stock market decreased evidently during the European debt crisis. Before sub-prime crisis, there is no significant evidence to show that other stock markets co-move with China stock market, while it becomes more integrated with other markets during the sub-prime and European debt crisis. Among developed and emerging stock markets, the developed stock markets lead the world stock markets before European debt crisis, while due to the shock of sub-prime and European debt crisis, their influences decreased and emerging stock markets replaced them to lead global stock markets.

  7. Confidence and the Stock Market: An Agent-Based Approach

    PubMed Central

    Bertella, Mario A.; Pires, Felipe R.; Feng, Ling; Stanley, Harry Eugene

    2014-01-01

    Using a behavioral finance approach we study the impact of behavioral bias. We construct an artificial market consisting of fundamentalists and chartists to model the decision-making process of various agents. The agents differ in their strategies for evaluating stock prices, and exhibit differing memory lengths and confidence levels. When we increase the heterogeneity of the strategies used by the agents, in particular the memory lengths, we observe excess volatility and kurtosis, in agreement with real market fluctuations—indicating that agents in real-world financial markets exhibit widely differing memory lengths. We incorporate the behavioral traits of adaptive confidence and observe a positive correlation between average confidence and return rate, indicating that market sentiment is an important driver in price fluctuations. The introduction of market confidence increases price volatility, reflecting the negative effect of irrationality in market behavior. PMID:24421888

  8. Confidence and the stock market: an agent-based approach.

    PubMed

    Bertella, Mario A; Pires, Felipe R; Feng, Ling; Stanley, Harry Eugene

    2014-01-01

    Using a behavioral finance approach we study the impact of behavioral bias. We construct an artificial market consisting of fundamentalists and chartists to model the decision-making process of various agents. The agents differ in their strategies for evaluating stock prices, and exhibit differing memory lengths and confidence levels. When we increase the heterogeneity of the strategies used by the agents, in particular the memory lengths, we observe excess volatility and kurtosis, in agreement with real market fluctuations--indicating that agents in real-world financial markets exhibit widely differing memory lengths. We incorporate the behavioral traits of adaptive confidence and observe a positive correlation between average confidence and return rate, indicating that market sentiment is an important driver in price fluctuations. The introduction of market confidence increases price volatility, reflecting the negative effect of irrationality in market behavior.

  9. A self-similar hierarchy of the Korean stock market

    NASA Astrophysics Data System (ADS)

    Lim, Gyuchang; Min, Seungsik; Yoo, Kun-Woo

    2013-01-01

    A scaling analysis is performed on market values of stocks listed on Korean stock exchanges such as the KOSPI and the KOSDAQ. Different from previous studies on price fluctuations, market capitalizations are dealt with in this work. First, we show that the sum of the two stock exchanges shows a clear rank-size distribution, i.e., the Zipf's law, just as each separate one does. Second, by abstracting Zipf's law as a γ-sequence, we define a self-similar hierarchy consisting of many levels, with the numbers of firms at each level forming a geometric sequence. We also use two exponential functions to describe the hierarchy and derive a scaling law from them. Lastly, we propose a self-similar hierarchical process and perform an empirical analysis on our data set. Based on our findings, we argue that all money invested in the stock market is distributed in a hierarchical way and that a slight difference exists between the two exchanges.

  10. 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.

  11. Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets

    NASA Astrophysics Data System (ADS)

    Yang, Liansheng; Zhu, Yingming; Wang, Yudong; Wang, Yiqi

    2016-11-01

    Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.

  12. Quantifying the behavior of price dynamics at opening time in stock market

    NASA Astrophysics Data System (ADS)

    Ochiai, Tomoshiro; Takada, Hideyuki; Nacher, Jose C.

    2014-11-01

    The availability of huge volume of financial data has offered the possibility for understanding the markets as a complex system characterized by several stylized facts. Here we first show that the time evolution of the Japan’s Nikkei stock average index (Nikkei 225) futures follows the resistance and breaking-acceleration effects when the complete time series data is analyzed. However, in stock markets there are periods where no regular trades occur between the close of the market on one day and the next day’s open. To examine these time gaps we decompose the time series data into opening time and intermediate time. Our analysis indicates that for the intermediate time, both the resistance and the breaking-acceleration effects are still observed. However, for the opening time there are almost no resistance and breaking-acceleration effects, and volatility is always constantly high. These findings highlight unique dynamic differences between stock markets and forex market and suggest that current risk management strategies may need to be revised to address the absence of these dynamic effects at the opening time.

  13. Analysis of network clustering behavior of the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Chen, Huan; Mai, Yong; Li, Sai-Ping

    2014-11-01

    Random Matrix Theory (RMT) and the decomposition of correlation matrix method are employed to analyze spatial structure of stocks interactions and collective behavior in the Shanghai and Shenzhen stock markets in China. The result shows that there exists prominent sector structures, with subsectors including the Real Estate (RE), Commercial Banks (CB), Pharmaceuticals (PH), Distillers&Vintners (DV) and Steel (ST) industries. Furthermore, the RE and CB subsectors are mostly anti-correlated. We further study the temporal behavior of the dataset and find that while the sector structures are relatively stable from 2007 through 2013, the correlation between the real estate and commercial bank stocks shows large variations. By employing the ensemble empirical mode decomposition (EEMD) method, we show that this anti-correlation behavior is closely related to the monetary and austerity policies of the Chinese government during the period of study.

  14. Collective Behavior of Market Participants during Abrupt Stock Price Changes

    PubMed Central

    Maskawa, Jun-ichi

    2016-01-01

    Under uncertainty, human and animal collectives often respond stochastically to events they encounter. Human or animal individuals behave depending on others’ actions, and sometimes follow choices that are sub-optimal for individuals. Such mimetic behaviors are enhanced during emergencies, creating collective behavior of a group. A stock market that is about to crash, as markets did immediately after the Lehman Brothers bankruptcy, provides illustrative examples of such behaviors. We provide empirical evidence proving the existence of collective behavior among stock market participants in emergent situations. We investigated the resolution of extreme supply-and-demand order imbalances by increased balancing counter orders: buy and sell orders for excess supply and demand respectively, during times of price adjustment, so-called special quotes on the Tokyo Stock Exchange. Counter orders increase positively depending on the quantity of revealed counter orders: the accumulated orders in the book until then. Statistics of the coming counter order are well described using a logistic regression model with the ratio of revealed orders until then to the finally revealed orders as the explanatory variable. Results given here show that the market participants make Bayesian estimations of optimal choices to ascertain whether to order using information about orders of other participants. PMID:27513335

  15. Collective Behavior of Market Participants during Abrupt Stock Price Changes.

    PubMed

    Maskawa, Jun-Ichi

    2016-01-01

    Under uncertainty, human and animal collectives often respond stochastically to events they encounter. Human or animal individuals behave depending on others' actions, and sometimes follow choices that are sub-optimal for individuals. Such mimetic behaviors are enhanced during emergencies, creating collective behavior of a group. A stock market that is about to crash, as markets did immediately after the Lehman Brothers bankruptcy, provides illustrative examples of such behaviors. We provide empirical evidence proving the existence of collective behavior among stock market participants in emergent situations. We investigated the resolution of extreme supply-and-demand order imbalances by increased balancing counter orders: buy and sell orders for excess supply and demand respectively, during times of price adjustment, so-called special quotes on the Tokyo Stock Exchange. Counter orders increase positively depending on the quantity of revealed counter orders: the accumulated orders in the book until then. Statistics of the coming counter order are well described using a logistic regression model with the ratio of revealed orders until then to the finally revealed orders as the explanatory variable. Results given here show that the market participants make Bayesian estimations of optimal choices to ascertain whether to order using information about orders of other participants. PMID:27513335

  16. Collective Behavior of Market Participants during Abrupt Stock Price Changes.

    PubMed

    Maskawa, Jun-Ichi

    2016-01-01

    Under uncertainty, human and animal collectives often respond stochastically to events they encounter. Human or animal individuals behave depending on others' actions, and sometimes follow choices that are sub-optimal for individuals. Such mimetic behaviors are enhanced during emergencies, creating collective behavior of a group. A stock market that is about to crash, as markets did immediately after the Lehman Brothers bankruptcy, provides illustrative examples of such behaviors. We provide empirical evidence proving the existence of collective behavior among stock market participants in emergent situations. We investigated the resolution of extreme supply-and-demand order imbalances by increased balancing counter orders: buy and sell orders for excess supply and demand respectively, during times of price adjustment, so-called special quotes on the Tokyo Stock Exchange. Counter orders increase positively depending on the quantity of revealed counter orders: the accumulated orders in the book until then. Statistics of the coming counter order are well described using a logistic regression model with the ratio of revealed orders until then to the finally revealed orders as the explanatory variable. Results given here show that the market participants make Bayesian estimations of optimal choices to ascertain whether to order using information about orders of other participants.

  17. Information theory applied to econophysics: stock market behaviors

    NASA Astrophysics Data System (ADS)

    Vogel, Eugenio E.; Saravia, Gonzalo

    2014-08-01

    The use of data compressor techniques has allowed to recognize magnetic transitions and their associated critical temperatures [E.E. Vogel, G. Saravia, V. Cortez, Physica A 391, 1591 (2012)]. In the present paper we introduce some new concepts associated to data recognition and extend the use of these techniques to econophysics to explore the variations of stock market indicators showing that information theory can help to recognize different regimes. Modifications and further developments to previously introduced data compressor wlzip are introduced yielding two measurements. Additionally, we introduce an algorithm that allows to tune the number of significant digits over which the data compression is due to act complementing, this with an appropriate method to round off the truncation. The application is done to IPSA, the main indicator of the Chilean Stock Market during the year 2010 due to availability of quality data and also to consider a rare effect: the earthquake of the 27th of February on that year which is as of now the sixth strongest earthquake ever recorded by instruments (8.8 Richter scale) according to United States Geological Survey. Along the year 2010 different regimes are recognized. Calm days show larger compression than agitated days allowing for classification and recognition. Then the focus turns onto selected days showing that it is possible to recognize different regimes with the data of the last hour (60 entries) allowing to determine actions in a safer way. The "day of the week" effect is weakly present but "the hour of the day" effect is clearly present; its causes and implications are discussed. This effect also establishes the influence of Asian, European and American stock markets over the smaller Chilean Stock Market. Then dynamical studies are conducted intended to search a system that can help to realize in real time about sudden variations of the market; it is found that information theory can be really helpful in this respect.

  18. 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.

  19. 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

  20. The study of Thai stock market across the 2008 financial crisis

    NASA Astrophysics Data System (ADS)

    Kanjamapornkul, K.; Pinčák, Richard; Bartoš, Erik

    2016-11-01

    The cohomology theory for financial market can allow us to deform Kolmogorov space of time series data over time period with the explicit definition of eight market states in grand unified theory. The anti-de Sitter space induced from a coupling behavior field among traders in case of a financial market crash acts like gravitational field in financial market spacetime. Under this hybrid mathematical superstructure, we redefine a behavior matrix by using Pauli matrix and modified Wilson loop for time series data. We use it to detect the 2008 financial market crash by using a degree of cohomology group of sphere over tensor field in correlation matrix over all possible dominated stocks underlying Thai SET50 Index Futures. The empirical analysis of financial tensor network was performed with the help of empirical mode decomposition and intrinsic time scale decomposition of correlation matrix and the calculation of closeness centrality of planar graph.

  1. The normalisation of terror: the response of Israel's stock market to long periods of terrorism.

    PubMed

    Peleg, Kobi; Regens, James L; Gunter, James T; Jaffe, Dena H

    2011-01-01

    Man-made disasters such as acts of terrorism may affect a society's resiliency and sensitivity to prolonged physical and psychological stress. The Israeli Tel Aviv stock market TA-100 Index was used as an indicator of reactivity to suicide terror bombings. After accounting for factors such as world market changes and attack severity and intensity, the analysis reveals that although Israel's financial base remained sensitive to each act of terror across the entire period of the Second Intifada (2000-06), sustained psychological resilience was indicated with no apparent overall market shift. In other words, we saw a 'normalisation of terror' following an extended period of continued suicide bombings. The results suggest that investors responded to less transitory global market forces, indicating sustained resilience and long-term market confidence. Future studies directly measuring investor expectations and reactions to man-made disasters, such as terrorism, are warranted.

  2. Inverse-cubic law of index fluctuation distribution in Indian markets

    NASA Astrophysics Data System (ADS)

    Pan, Raj Kumar; Sinha, Sitabhra

    2008-03-01

    One of the principal statistical features characterizing the activity in financial markets is the distribution of fluctuations in market indicators such as the index. While the developed stock markets, e.g., the New York Stock Exchange (NYSE) have been found to show heavy-tailed return distribution with a characteristic power-law exponent, the universality of such behavior has been debated, particularly in regard to emerging markets. Here we investigate the distribution of several indices from the Indian financial market, one of the largest emerging markets in the world. We have used tick-by-tick data from the National Stock Exchange (NSE), as well as, daily closing data from both the NSE and Bombay Stock Exchange (BSE). We find that the cumulative distributions of index returns have long tails consistent with a power law having exponent α ≈ 3, at time scales of both 1 min and 1 day. This "inverse-cubic law" is quantitatively similar to what has been observed in developed markets, thereby providing strong evidence of universality in the behavior of market fluctuations.

  3. Anticipating Stock Market Movements with Google and Wikipedia

    NASA Astrophysics Data System (ADS)

    Moat, Helen Susannah; Curme, Chester; Stanley, H. Eugene; Preis, Tobias

    Many of the trading decisions that have led to financial crises are captured by vast, detailed stock market datasets. Here, we summarize two of our recent studies which investigate whether Internet usage data contain traces of attempts to gather information before such trading decisions were taken. By analyzing changes in how often Internet users searched for financially related information on Google (Preis et al., Sci Rep 3:1684, 2013) and Wikipedia (Moat et al., Sci Rep 3:1801, 2013), patterns are found that may be interpreted as "early warning signs" of stock market moves. Our results suggest that online data may allow us to gain new insight into early information gathering stages of economic decision making.

  4. Characterization of stock market regimes by data compression

    NASA Astrophysics Data System (ADS)

    Vogel, Eugenio E.; Saravia, Gonzalo

    2011-03-01

    It has been shown that data compression can characterize magnetic phases (Physica A 388 (2009) 4075). In the introduction of this presentation we briefly review this result. We then go onto introducing a new data compressor (wlzip) developed by us to optimize recognition of meaningful patterns in the compressing procedure, yielding sharp transition curves at the magnetic critical temperatures. The advantages of the new compressor, such as better definition and tuning capabilities are presented. The rest of the talk consists of applying wlzip to the Chilean stock market along several months during 2010. The accumulated daily data allow to recognizing days with different types of activity. Moreover, the data recorded every minute allow to analyzing the ``present'' status of the stock market by applying wlzip to the data of the last hour or couple of hours. Possible extensions of the application of this technique to other fields are discussed. Partial support from Fondecyt 1100156, ICM and CEDENNA is acknowledged.

  5. A Critical Review of "Learning from the Market: Integrating 'The Stock Market Game' across the Curriculum."

    ERIC Educational Resources Information Center

    Maier, Mark H.

    2002-01-01

    Reviews "Learning from the Market: Integrating 'The Stock Market Game' across the Curriculum" guide for teachers in grades 4 to 12. Believes the guide suffers from errors of fact and omission. Suggests corrections and alternative activities that enable instructors to continue to use the material. (JEH)

  6. Generalized Bogoliubov Polariton Model: An Application to Stock Exchange Market

    NASA Astrophysics Data System (ADS)

    Thuy Anh, Chu; Anh, Truong Thi Ngoc; Lan, Nguyen Tri; Viet, Nguyen Ai

    2016-06-01

    A generalized Bogoliubov method for investigation non-simple and complex systems was developed. We take two branch polariton Hamiltonian model in second quantization representation and replace the energies of quasi-particles by two distribution functions of research objects. Application to stock exchange market was taken as an example, where the changing the form of return distribution functions from Boltzmann-like to Gaussian-like was studied.

  7. On the nature of the stock market: Simulations and experiments

    NASA Astrophysics Data System (ADS)

    Blok, Hendrik J.

    2000-10-01

    In this dissertation two simple models of stock exchange are developed and simulated numerically. The first is characterized by centralized trading with a market maker. Unfortunately, this model is unable to generate realistic market dynamics. The second model discards the requirement of centralized trading. Under variation of the control parameter the model exhibits two phase transitions: both a first- and a second-order (critical). The decentralized model is able to capture many of the interesting properties observed in empirical markets. Significantly, these properties only emerge when the parameters are tuned such that the model spans the critical point. This suggests that real markets may operate at or near a critical point, but is unable to explain why this should be. One of the main points of the thesis is that these empirical phenomena are not present in the stochastic driving force, but emerge endogenously from interactions between agents.

  8. A model for the evaluation of systemic risk in stock markets

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2011-06-01

    Systemic risk refers to the possibility of a collapse of an entire financial system or market, differing from the risk associated with any particular individual or a group pertaining to the system, which may include banks, government, brokers, and creditors. After the 2008 financial crisis, a significant amount of effort has been directed to the study of systemic risk and its consequences around the world. Although it is very difficult to predict when people begin to lose confidence in a financial system, it is possible to model the relationships among the stock markets of different countries and perform a Monte Carlo-type analysis to study the contagion effect. Because some larger and stronger markets influence smaller ones, a model inspired by a catalytic chemical model is proposed. In chemical reactions, reagents with higher concentrations tend to favor their conversion to products. In order to modulate the conversion process, catalyzers may be used. In this work, a mathematical modeling is proposed with bases on the catalytic chemical reaction model. More specifically, the Hang Seng and Dow Jones indices are assumed to dominate Ibovespa (the Brazilian Stock Market index), such that the indices of strong markets are taken as being analogous to the concentrations of the reagents and the indices of smaller markets as concentrations of products. The role of the catalyst is to model the degree of influence of one index on another. The actual data used to fit the model parameter consisted of the Hang Seng index, Dow Jones index, and Ibovespa, since 1993. “What if” analyses were carried out considering some intervention policies.

  9. Cell therapy companies make strong progress from October 2012 to March 2013 amid mixed stock market sentiment.

    PubMed

    Mason, Chris; Mason, Julian; Culme-Seymour, Emily J; Bonfiglio, Gregory A; Reeve, Brock C

    2013-06-01

    During Q4 2012 and Q1 2013, the cell therapy industry made strong progress in translation and commercialization. Continued development of the companies included in a dedicated stock market index suggests emergence of this industry as a distinct healthcare sector.

  10. On the integration of financial markets: How strong is the evidence from five international stock markets?

    NASA Astrophysics Data System (ADS)

    Bentes, Sónia R.

    2015-07-01

    This paper examines the integration of financial markets using data from five international stock markets in the context of globalization. The theoretical basis of this study relies on the price theory and the Law of One Price, which was adjusted to the framework of financial markets. When price levels are nonstationary, cointegration and the error correction model constitute a powerful tool for the empirical examination of market integration. The error correction model provides a fully dynamic framework that allows to separating the long and the short run effects of the integration process. A dataset encompassing the daily stock price series of the PSI 20 (Portugal), IBEX 35 (Spain), FTSE 100 (UK), NIKKEI 225 (Japan) and SP 500 (US) indices from January 4th 1999 to September 19th 2014 is employed. The results highlight that these five stock markets are linked together by just one long-run relationship, although short-run movements are also present, which causes distinct deviations from the long-run equilibrium relationship. Endogeneity prevails in the system as a whole. While market integration in the sense of the Law of One Price holds, pairwise full price transmission has limited evidence. The results therefore show that stock market price movements are highly nonlinear and complex.

  11. Initial value sensitivity of the Chinese stock market and its relationship with the investment psychology

    NASA Astrophysics Data System (ADS)

    Ying, Shangjun; Li, Xiaojun; Zhong, Xiuqin

    2015-04-01

    This paper discusses the initial value sensitivity (IVS) of Chinese stock market, including the single stock market and the Chinese A-share stock market, with respect to real markets and evolving models. The aim is to explore the relationship between IVS of the Chinese A-share stock market and the investment psychology based on the evolving model of genetic cellular automaton (GCA). We find: (1) The Chinese stock market is sensitively dependent on the initial conditions. (2) The GCA model provides a considerable reliability in complexity simulation (e.g. the IVS). (3) The IVS of stock market is positively correlated with the imitation probability when the intensity of the imitation psychology reaches a certain threshold. The paper suggests that the government should seek to keep the imitation psychology under a certain level, otherwise it may induce severe fluctuation to the market.

  12. Stock markets are not what we think they are: the key roles of cross-ownership and corporate treasury stock

    NASA Astrophysics Data System (ADS)

    Roehner, Bertrand M.

    2005-03-01

    We describe, document and statistically test three mechanisms by which corporations can influence or even control stock prices: (i) Parent and holding companies wield control over other publicly traded companies. (ii) Through clever management of treasury stock based on buyback programs and stock issuance, stock price fluctuations can be amplified or curbed. The shock of September 11, 2001 is used to test this effect. (iii) Finally, historical evidence shows that there is a close interdependence between the level of stock prices on the one hand and merger and acquisition activity on the other hand: on average, a 10% increase in the number of mergers brings about a 3% increase in the overall level of stock prices. If one adds up buybacks, initial public offerings and takeover transactions, all of which depend upon strategic decisions taken by corporate management, they represent on average 7.2% of the trade on the New York Stock Exchange over the period 1987-2003 (as much as 12% in specific years such as 1988). This perspective, in which the Boards of Directors of major companies “shepherd” the market, offers a natural interpretation of the so-called “herd behavior” observed in stock markets. The traditional view holds that, by driving profit expectations, corporations have an indirect role in shaping the market. In this paper, we suggest that over the last decades they became more and more the direct moving force of stock markets.

  13. 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

  14. 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

  15. Contemporaneous aggregation and long-memory property of returns and volatility in the Korean stock market

    NASA Astrophysics Data System (ADS)

    Kang, Sang Hoon; Cheong, Chongcheul; Yoon, Seong-Min

    2010-11-01

    The principal objective of this study is to determine whether the long-memory property is real or a spurious result caused by contemporaneous aggregation. In order to assess the presence of long memory in returns and volatility, two different long-memory detection techniques (modified R/S analysis and the GPH test) were applied to the KOSPI 50 index and its 50 constituent individual stock prices. According to the empirical evidence gleaned from the two long-memory tests, we conclude that there exists significant evidence for the long-memory property in volatility in both the market index and in a majority of individual stocks. These findings indicate that the observed evidence of the long-memory feature in volatility of index series is not spurious, and that we can reject the hypothesis that spurious long-memory evidence in the volatility of index series is the consequence of contemporaneous aggregation. However, this conclusion should be considered cautiously, given that a considerable number of the individual stock volatilities in square returns strongly show a short-memory property, as the level of significance in statistical decisions is lowered to the 1% level.

  16. 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.

  17. 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

  18. Clustering of Casablanca stock market based on hurst exponent estimates

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim

    2016-08-01

    This paper deals with the problem of Casablanca Stock Exchange (CSE) topology modeling as a complex network during three different market regimes: general trend characterized by ups and downs, increasing trend, and decreasing trend. In particular, a set of seven different Hurst exponent estimates are used to characterize long-range dependence in each industrial sector generating process. They are employed in conjunction with hierarchical clustering approach to examine the co-movements of the Casablanca Stock Exchange industrial sectors. The purpose is to investigate whether cluster structures are similar across variable, increasing and decreasing regimes. It is observed that the general structure of the CSE topology has been considerably changed over 2009 (variable regime), 2010 (increasing regime), and 2011 (decreasing regime) time periods. The most important findings follow. First, in general a high value of Hurst exponent is associated to a variable regime and a small one to a decreasing regime. In addition, Hurst estimates during increasing regime are higher than those of a decreasing regime. Second, correlations between estimated Hurst exponent vectors of industrial sectors increase when Casablanca stock exchange follows an upward regime, whilst they decrease when the overall market follows a downward regime.

  19. Market impact and trading profile of hidden orders in stock markets

    NASA Astrophysics Data System (ADS)

    Moro, Esteban; Vicente, Javier; Moyano, Luis G.; Gerig, Austin; Farmer, J. Doyne; Vaglica, Gabriella; Lillo, Fabrizio; Mantegna, Rosario N.

    2009-12-01

    We empirically study the market impact of trading orders. We are specifically interested in large trading orders that are executed incrementally, which we call hidden orders. These are statistically reconstructed based on information about market member codes using data from the Spanish Stock Market and the London Stock Exchange. We find that market impact is strongly concave, approximately increasing as the square root of order size. Furthermore, as a given order is executed, the impact grows in time according to a power law; after the order is finished, it reverts to a level of about 0.5-0.7 of its value at its peak. We observe that hidden orders are executed at a rate that more or less matches trading in the overall market, except for small deviations at the beginning and end of the order.

  20. Quantifying the Relationship Between Financial News and the Stock Market

    PubMed Central

    Alanyali, Merve; Moat, Helen Susannah; Preis, Tobias

    2013-01-01

    The complex behavior of financial markets emerges from decisions made by many traders. Here, we exploit a large corpus of daily print issues of the Financial Times from 2nd January 2007 until 31st December 2012 to quantify the relationship between decisions taken in financial markets and developments in financial news. We find a positive correlation between the daily number of mentions of a company in the Financial Times and the daily transaction volume of a company's stock both on the day before the news is released, and on the same day as the news is released. Our results provide quantitative support for the suggestion that movements in financial markets and movements in financial news are intrinsically interlinked. PMID:24356666

  1. How long is the memory of the US stock market?

    NASA Astrophysics Data System (ADS)

    Ferreira, Paulo; Dionísio, Andreia

    2016-06-01

    The Efficient Market Hypothesis (EMH), one of the most important hypothesis in financial economics, argues that return rates have no memory (correlation) which implies that agents cannot make abnormal profits in financial markets, due to the possibility of arbitrage operations. With return rates for the US stock market, we corroborate the fact that with a linear approach, return rates do not show evidence of correlation. However, linear approaches might not be complete or global, since return rates could suffer from nonlinearities. Using detrended cross-correlation analysis and its correlation coefficient, a methodology which analyzes long-range behavior between series, we show that the long-range correlation of return rates only ends in the 149th lag, which corresponds to about seven months. Does this result undermine the EMH?

  2. Quantifying the relationship between financial news and the stock market.

    PubMed

    Alanyali, Merve; Moat, Helen Susannah; Preis, Tobias

    2013-01-01

    The complex behavior of financial markets emerges from decisions made by many traders. Here, we exploit a large corpus of daily print issues of the Financial Times from 2(nd) January 2007 until 31(st) December 2012 to quantify the relationship between decisions taken in financial markets and developments in financial news. We find a positive correlation between the daily number of mentions of a company in the Financial Times and the daily transaction volume of a company's stock both on the day before the news is released, and on the same day as the news is released. Our results provide quantitative support for the suggestion that movements in financial markets and movements in financial news are intrinsically interlinked.

  3. 17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... required by paragraph (a) of this section for the period specified in 17 CFR 240.17a-4(b) of this chapter... 17 Commodity and Securities Exchanges 3 2011-04-01 2011-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities...

  4. 17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... required by paragraph (a) of this section for the period specified in 17 CFR 240.17a-4(b) of this chapter... 17 Commodity and Securities Exchanges 3 2010-04-01 2010-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities...

  5. 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.

  6. Optimality problem of network topology in stocks market analysis

    NASA Astrophysics Data System (ADS)

    Djauhari, Maman Abdurachman; Gan, Siew Lee

    2015-02-01

    Since its introduction fifteen years ago, minimal spanning tree has become an indispensible tool in econophysics. It is to filter the important economic information contained in a complex system of financial markets' commodities. Here we show that, in general, that tool is not optimal in terms of topological properties. Consequently, the economic interpretation of the filtered information might be misleading. To overcome that non-optimality problem, a set of criteria and a selection procedure of an optimal minimal spanning tree will be developed. By using New York Stock Exchange data, the advantages of the proposed method will be illustrated in terms of the power-law of degree distribution.

  7. Stock market speculation: Spontaneous symmetry breaking of economic valuation

    NASA Astrophysics Data System (ADS)

    Sornette, Didier

    2000-09-01

    Firm foundation theory estimates a security's firm fundamental value based on four determinants: expected growth rate, expected dividend payout, the market interest rate and the degree of risk. In contrast, other views of decision-making in the stock market, using alternatives such as human psychology and behavior, bounded rationality, agent-based modeling and evolutionary game theory, expound that speculative and crowd behavior of investors may play a major role in shaping market prices. Here, we propose that the two views refer to two classes of companies connected through a "phase transition". Our theory is based on (1) the identification of the fundamental parity symmetry of prices (p→-p), which results from the relative direction of payment flux compared to commodity flux and (2) the observation that a company's risk-adjusted growth rate discounted by the market interest rate behaves as a control parameter for the observable price. We find a critical value of this control parameter at which a spontaneous symmetry-breaking of prices occurs, leading to a spontaneous valuation in absence of earnings, similarly to the emergence of a spontaneous magnetization in Ising models in absence of a magnetic field. The low growth rate phase is described by the firm foundation theory while the large growth rate phase is the regime of speculation and crowd behavior. In practice, while large "finite-time horizon" effects round off the predicted singularities, our symmetry-breaking speculation theory accounts for the apparent over-pricing and the high volatility of fast growing companies on the stock markets.

  8. Effects of global financial crisis on network structure in a local stock market

    NASA Astrophysics Data System (ADS)

    Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo

    2014-08-01

    This study considers the effects of the 2008 global financial crisis on threshold networks of a local Korean financial market around the time of the crisis. Prices of individual stocks belonging to KOSPI 200 (Korea Composite Stock Price Index 200) are considered for three time periods, namely before, during, and after the crisis. Threshold networks are constructed from fully connected cross-correlation networks, and thresholds of cross-correlation coefficients are assigned to obtain threshold networks. At the high threshold, only one large cluster consisting of firms in the financial sector, heavy industry, and construction is observed during the crisis. However, before and after the crisis, there are several fragmented clusters belonging to various sectors. The power law of the degree distribution in threshold networks is observed within the limited range of thresholds. Threshold networks are fatter during the crisis than before or after the crisis. The clustering coefficient of the threshold network follows the power law in the scaling range.

  9. Pattern of trends in stock markets as revealed by the renormalization method

    NASA Astrophysics Data System (ADS)

    Zhang, H. S.; Shen, X. Y.; Huang, J. P.

    2016-08-01

    Predicting the movement of prices is a challenging topic in financial markets. So far, many investigations have been performed to help understand the dynamics of stock prices. In this work, we utilize the renormalization method to analyze the scaling and pattern of stock price trends. According to the analysis of length and changing velocity of the price trends, we find that there exist asymmetric phenomena of the trends in American stock market. In addition, a stronger Herd behavior is also discovered in the Chinese stock market. Since the Chinese (American) stock market is a representative of emerging (mature) market, the study on comparing the markets between these two countries is of potential value, which can leave us a wiser about both the pattern of the markets and the underlying physical mechanisms.

  10. Information theory in econophysics: stock market and retirement funds

    NASA Astrophysics Data System (ADS)

    Vogel, Eugenio; Saravia, G.; Astete, J.; Díaz, J.; Erribarren, R.; Riadi, F.

    2013-03-01

    Information theory can help to recognize magnetic phase transitions, what can be seen as a way to recognize different regimes. This is achieved by means of zippers specifically designed to compact data in a meaningful way at is the case for compressor wlzip. In the present contribution we first apply wlzip to the Chilean stock market interpreting the compression rates for the files storing the minute variation of the IPSA indicator. Agitated days yield poor compression rates while calm days yield high compressibility. We then correlate this behavior to the value of the five retirement funds related to the Chilean economy. It is found that the covariance between the profitability of the retirement funds and the compressibility of the IPSA values of previous day is high for those funds investing in risky stocks. Surprisingly, there seems to be no great difference among the three riskier funds contrary to what could be expected from the limitations on the portfolio composition established by the laws that regulate this market.

  11. Web Search Queries Can Predict Stock Market Volumes

    PubMed Central

    Bordino, Ilaria; Battiston, Stefano; Caldarelli, Guido; Cristelli, Matthieu; Ukkonen, Antti; Weber, Ingmar

    2012-01-01

    We live in a computerized and networked society where many of our actions leave a digital trace and affect other people’s actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www. PMID:22829871

  12. Web search queries can predict stock market volumes.

    PubMed

    Bordino, Ilaria; Battiston, Stefano; Caldarelli, Guido; Cristelli, Matthieu; Ukkonen, Antti; Weber, Ingmar

    2012-01-01

    We live in a computerized and networked society where many of our actions leave a digital trace and affect other people's actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www.

  13. Interest rate change and Omori dynamics in the Stock Market

    NASA Astrophysics Data System (ADS)

    Petersen, Alexander; Wang, Fengzhong; Havlin, Shlomo; Stanley, H. Eugene

    2009-03-01

    I present the behavior of U.S. markets on the day of U.S. Federal Open Market Commission (FOMC) meetings from the perspective of Statistical Physics. The announcement of key U.S. Federal Reserve rate changes causes a small financial shock, where the dynamics before and after the announcement can be described by an Omori law. We find that markets respond sharply to the news in a complex way reminiscent of physical earthquakes described by the Omori law, which describes the power-law relaxation of aftershocks following a singular perturbation. We find Omori laws in both the volatility of the price (also known as the absolute returns) and the volume traded, using 1-minute resolution financial time series. These results suggest that the perturbative response of the stock market is the same for both financial news and financial crises. The intraday response can be measured by the Omori power-law exponent φ, which has opposite sign before and after the announcement. We estimate the magnitude of news by relating φ to the behavior of the U. S. Treasury Bill before and after FOMC announcements.

  14. Quantum spatial-periodic harmonic model for daily price-limited stock markets

    NASA Astrophysics Data System (ADS)

    Meng, Xiangyi; Zhang, Jian-Wei; Xu, Jingjing; Guo, Hong

    2015-11-01

    We investigate the behaviors of stocks in daily price-limited stock markets by purposing a quantum spatial-periodic harmonic model. The stock price is considered to be oscillating and damping in a quantum spatial-periodic harmonic oscillator potential well. A complicated non-linear relation including inter-band positive correlation and intra-band negative correlation between the volatility and trading volume of a stock is numerically derived with the energy band structure of the model concerned. The effectiveness of price limit is re-examined, with some observed characteristics of price-limited stock markets in China studied by applying our quantum model.

  15. Statistical properties of the stock and credit market: RMT and network topology

    NASA Astrophysics Data System (ADS)

    Lim, Kyuseong; Kim, Min Jae; Kim, Sehyun; Kim, Soo Yong

    We analyzed the dependence structure of the credit and stock market using random matrix theory and network topology. The dynamics of both markets have been spotlighted throughout the subprime crisis. In this study, we compared these two markets in view of the market-wide effect from random matrix theory and eigenvalue analysis. We found that the largest eigenvalue of the credit market as a whole preceded that of the stock market in the beginning of the financial crisis and that of two markets tended to be synchronized after the crisis. The correlation between the companies of both markets became considerably stronger after the crisis as well.

  16. The Proteomics Stock Market Project: A Cross-Disciplinary Collaboration in Biochemistry and Business Education

    ERIC Educational Resources Information Center

    Keller, Heath; Cox, James R.

    2004-01-01

    A collaborative effort between business and chemistry resulted in a class project called the Proteomics Stock Market Project. The project includes biochemical and marketing concepts, technology, writing assignments and group work.

  17. Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data

    NASA Astrophysics Data System (ADS)

    Alfarano, Simone; Lux, Thomas; Wagner, Friedrich

    2006-10-01

    Following Alfarano et al. [Estimation of agent-based models: the case of an asymmetric herding model, Comput. Econ. 26 (2005) 19-49; Excess volatility and herding in an artificial financial market: analytical approach and estimation, in: W. Franz, H. Ramser, M. Stadler (Eds.), Funktionsfähigkeit und Stabilität von Finanzmärkten, Mohr Siebeck, Tübingen, 2005, pp. 241-254], we consider a simple agent-based model of a highly stylized financial market. The model takes Kirman's ant process [A. Kirman, Epidemics of opinion and speculative bubbles in financial markets, in: M.P. Taylor (Ed.), Money and Financial Markets, Blackwell, Cambridge, 1991, pp. 354-368; A. Kirman, Ants, rationality, and recruitment, Q. J. Econ. 108 (1993) 137-156] of mimetic contagion as its starting point, but allows for asymmetry in the attractiveness of both groups. Embedding the contagion process into a standard asset-pricing framework, and identifying the abstract groups of the herding model as chartists and fundamentalist traders, a market with periodic bubbles and bursts is obtained. Taking stock of the availability of a closed-form solution for the stationary distribution of returns for this model, we can estimate its parameters via maximum likelihood. Expanding our earlier work, this paper presents pertinent estimates for the Australian dollar/US dollar exchange rate and the Australian stock market index. As it turns out, our model indicates dominance of fundamentalist behavior in both the stock and foreign exchange market.

  18. 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.

  19. 77 FR 66658 - Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-06

    ... COMMISSION Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate... Financial Industry Regulatory Authority (``FINRA'') October 31, 2012. Pursuant to Section 19(b)(1) of the... October 22, 2012, The NASDAQ Stock Market LLC (``NASDAQ'' or ``Exchange''), filed with the Securities...

  20. Measuring persistence in stock market volatility using the FIGARCH approach

    NASA Astrophysics Data System (ADS)

    Bentes, Sónia R.

    2014-08-01

    This paper examines the long memory property in the conditional variance of the G7’s major stock market indices, using the FIGARCH model. The GARCH and IGARCH frameworks are also estimated for comparative purposes. To this end, a dataset encompassing the daily returns of the S&P/TSX 60, CAC 40, DAX 30, MIB 30, NIKKEI 225, FTSE 100 and S&P 500 indices from January 4th 1999 to January 21st 2009 is employed. Our results show evidence of long memory in the conditional variance, which is more pronounced for DAX 30, MIB 30 and CAC 40. However, NIKKEI 225 is found to be the less persistent. This may be explained by the fact that smaller markets, like DAX 30, are less liquid, less efficient, and more prone to experiencing correlated fluctuations and, therefore, more susceptible to being influenced by aggressive investors. On the other hand, bigger markets tend to exhibit lower correlations, thus favoring lower persistence levels. Finally, we use the log likelihood, Schwarz and Akaike Information Criteria to discriminate between models and found that FIGARCH is the most suitable model to capture the persistence.

  1. A Glauber Monte Carlo Approach to Stock Market Dynamics

    NASA Astrophysics Data System (ADS)

    Castiglione, Filippo; Stauffer, Dietrich; Pandey, Ras

    2001-03-01

    A computer simulation model is used to study the evolution of stock price and the distribution of price fluctuation. Effects of trading momentum and price resistance are considered by a Glauber Monte Carlo approach. The price resistance is described by an elastic energy Ee = e \\cdot x \\cdot |x| while the momentum bias Ep = - b \\cdot y, where, x = (p(t) - p(0))/x_m, y = (p(t+1) - p(t))/ym with the stock price at time t, p(t), and xm and ym are the maximum absolute values up to the current time step. e and b are elastic and momentum bias coefficients. Trades are executed via the herding percolation model with the number (n_s) of trading groups depend on the size of the group, i.e., ns = N/s^τ where N is the size of the market and τ = 2.5. Probability to buy (a/2) and sell (a/2) or remain inactive (1-a) depends on the activity a with the execution probability to buy Wb = e^-E/ [1 + e^-E] and sell with 1-W_b. The distribution of price fluctuation (P(y)) shows a long time tail with a power-law, P(y) ~ y^-μ, μ ~= 4 at e = 1.0, b = 5. The volatility auto-correlation function (c(τ)) shows a reasonable behavior (positive) over several iterations.

  2. Liquidity spillover in international stock markets through distinct time scales.

    PubMed

    Righi, Marcelo Brutti; Vieira, Kelmara Mendes

    2014-01-01

    This paper identifies liquidity spillovers through different time scales based on a wavelet multiscaling method. We decompose daily data from U.S., British, Brazilian and Hong Kong stock markets indices in order to calculate the scale correlation between their illiquidities. The sample is divided in order to consider non-crisis, sub-prime crisis and Eurozone crisis. We find that there are changes in correlations of distinct scales and different periods. Association in finest scales is smaller than in coarse scales. There is a rise on associations in periods of crisis. In frequencies, there is predominance for significant distinctions involving the coarsest scale, while for crises periods there is predominance for distinctions on the finest scale.

  3. Evidence of multifractality from emerging European stock markets.

    PubMed

    Caraiani, Petre

    2012-01-01

    We test for the presence of multifractality in the daily returns of the three most important stock market indices from Central and Eastern Europe, Czech PX, Hungarian BUX and Polish WIG using the Empirical Mode Decomposition based Multifractal Detrended Fluctuation Analysis. We found that the global Hurst coefficient varies with the q coefficient and that there is multifractality evidenced through the multifractal spectrum. The exercise is replicated for the sample around the high volatility period corresponding to the last global financial crisis. Although no direct link has been found between the crisis and the multifractal spectrum, the crisis was found to influence the overall shape as quantified through the norm of the multifractal spectrum.

  4. Liquidity Spillover in International Stock Markets through Distinct Time Scales

    PubMed Central

    Righi, Marcelo Brutti; Vieira, Kelmara Mendes

    2014-01-01

    This paper identifies liquidity spillovers through different time scales based on a wavelet multiscaling method. We decompose daily data from U.S., British, Brazilian and Hong Kong stock markets indices in order to calculate the scale correlation between their illiquidities. The sample is divided in order to consider non-crisis, sub-prime crisis and Eurozone crisis. We find that there are changes in correlations of distinct scales and different periods. Association in finest scales is smaller than in coarse scales. There is a rise on associations in periods of crisis. In frequencies, there is predominance for significant distinctions involving the coarsest scale, while for crises periods there is predominance for distinctions on the finest scale. PMID:24465918

  5. Statistical properties and pre-hit dynamics of price limit hits in the Chinese stock markets.

    PubMed

    Wan, Yu-Lei; Xie, Wen-Jie; Gu, Gao-Feng; Jiang, Zhi-Qiang; Chen, Wei; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

    2015-01-01

    Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders' short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect), indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners.

  6. Statistical Properties and Pre-Hit Dynamics of Price Limit Hits in the Chinese Stock Markets

    PubMed Central

    Wan, Yu-Lei; Xie, Wen-Jie; Gu, Gao-Feng; Jiang, Zhi-Qiang; Chen, Wei; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

    2015-01-01

    Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders’ short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect), indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners. PMID:25874716

  7. Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price

    NASA Astrophysics Data System (ADS)

    Zhuang, Xiaoyang; Wei, Yu; Ma, Feng

    2015-07-01

    In this paper, the multifractality and efficiency degrees of ten important Chinese sectoral indices are evaluated using the methods of MF-DFA and generalized Hurst exponents. The study also scrutinizes the dynamics of the efficiency of Chinese sectoral stock market by the rolling window approach. The overall empirical findings revealed that all the sectoral indices of Chinese stock market exist different degrees of multifractality. The results of different efficiency measures have agreed on that the 300 Materials index is the least efficient index. However, they have a slight diffidence on the most efficient one. The 300 Information Technology, 300 Telecommunication Services and 300 Health Care indices are comparatively efficient. We also investigate the cross-correlations between the ten sectoral indices and WTI crude oil price based on Multifractal Detrended Cross-correlation Analysis. At last, some relevant discussions and implications of the empirical results are presented.

  8. Can percolation theory be applied to the stock market?

    NASA Astrophysics Data System (ADS)

    Stauffer, Dietrich

    1998-11-01

    The fluctuations of the stock market - the price changes per unit time - seem to deviate from Gaussians for short time steps. Power laws, exponentials, and multifractal descriptions have been offered to explain this short-time behavior. Microscopic models dealing with the decisions of single traders on the market have tried to reproduce this behavior. Possibly the simplest of these models is the herding approach of Cont and Bouchaud. Here a total of Nt traders cluster together randomly as in percolation theory. Each cluster randomly decides by buy or sell an amount proportional to its size, or not to trade. Monte Carlo simulations in two to seven dimensions at the percolation threshold depend on the number N of clusters trading within one time step. For N 1, the changes follow a power law; for 1 N Nt they are bell-shaped with power-law tails; for N Nt they crossover to a Gaussian. The correlations in the absolute value of the change decay slowly with time. Thus percolation not only describes the origin of life or the boiling of your breakfast egg, but also explains why we are not rich.

  9. 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.

  10. Testing the stability of the 2000 US stock market “antibubble”

    NASA Astrophysics Data System (ADS)

    Zhou, Wei-Xing; Sornette, Didier

    2005-03-01

    Since August 2000, the stock market in the USA as well as most other western markets have depreciated almost in synchrony according to complex patterns of drops and local rebounds. In (Quantitative Finance 2 (2002) 468), we have proposed to describe this phenomenon using the concept of a log-periodic power law antibubble, characterizing behavioral herding between investors leading to a competition between positive and negative feedbacks in the pricing process. A monthly prediction for the future evolution of the US S&P 500 index has been issued, monitored and updated in ( http://www.ess.ucla.edu/faculty/sornette/prediction/index.asp#prediction), which is still running as the article goes to press. Here, we test the possible existence of a regime switching in the US S&P 500 antibubble. First, we find some evidence that the antibubble has exhibited a transition in log-periodicity described by a so-called second-order log-periodicity. Second, we develop a battery of tests to detect a possible end of the antibubble of the first order which suggest that the antibubble was alive in August 2003 but has ended in the USA, when expressed in the local US dollar currency. Our tests provide quantitative measures to diagnose the end of an antibubble. Such diagnostic is not instantaneous and requires from three to six months within the new regime before assessing its existence with confidence. From the perspective of foreign investors in their currencies (S&P 500 denominated in British pound or in euro) or when expressed in gold so as to correct for an arguably artificial US$ valuation associated with the Federal Reserve interest rate and monetary policy, we find that the S&P 500 antibubble is still alive and running its course. Similar analyses performed on the major European stock markets (CAC 40 of France, DAX of Germany, and FTSE 100 of United Kingdom) show that the antibubble is also present and continuing there.

  11. On the nature of the stock market: Simulations and experiments

    NASA Astrophysics Data System (ADS)

    Blok, Hendrik J.

    Over the last few years there has been a surge of activity within the physics community in the emerging field of Econophysics-the study of economic systems from a physicist's perspective. Physicists tend to take a different view than economists and other social scientists, being interested in such topics as phase transitions and fluctuations. In this dissertation two simple models of stock exchange are developed and simulated numerically. The first is characterized by centralized trading with a market maker. Fluctuations are driven by a stochastic component in the agents' forecasts. As the scale of the fluctuations is varied a critical phase transition is discovered. Unfortunately, this model is unable to generate realistic market dynamics. The second model discards the requirement of centralized trading. In this case the stochastic driving force is Gaussian-distributed ``news events'' which are public knowledge. Under variation of the control parameter the model exhibits two phase transitions: both a first- and a second-order (critical). The decentralized model is able to capture many of the interesting properties observed in empirical markets such as fat tails in the distribution of returns, a brief memory in the return series, and long-range correlations in volatility. Significantly, these properties only emerge when the parameters are tuned such that the model spans the critical point. This suggests that real markets may operate at or near a critical point, but is unable to explain why this should be. This remains an interesting open question worth further investigation. One of the main points of the thesis is that these empirical phenomena are not present in the stochastic driving force, but emerge endogenously from interactions between agents. Further, they emerge despite the simplicity of the modeled agents; suggesting complex market dynamics do not arise from the complexity of individual investors but simply from interactions between (even simple) investors

  12. Stock Market Indices and Investment Funds. An Empirical Approach in the Spanish and European Context

    NASA Astrophysics Data System (ADS)

    Ferruz, Luis; Marco, Isabel; Rivas, Francisco Javier

    This paper analyses changes in the levels of volatility of the Ibex 35 index over the past decade, as a representative index and benchmark for the Spanish equities market and the performance of the leading European stock market indices, Eurotop 100 and Euro Stoxx 50. We also consider the increasing importance and acceptance of mutual funds as the ideal instrument for the financial diversification of investment portfolios. The paper links mutual funds and benchmarks to focus on the analysis of a sample of equity investment funds, comparing their performance in terms of both returns and historical homocedastic volatility over various time periods (250, 100 and 20 days) with that of the most representative indices in the Spanish and European markets using the same parameters. These indices serve as a benchmark against which to assess the extent to which investment in funds is in fact rational in financial terms. We illustrate our approach using a sample of domestically and internationally diversified mutual funds, as well as three benchmarks, the Ibex 35, Eurotop 100 and Euro Stoxx 50 indices. Minimum quadratic linear models are applied to series of daily returns and to volatilities within the homocedastic framework and their correlation.

  13. Effects of Technical Traders in a Synthetic Stock Market

    NASA Astrophysics Data System (ADS)

    Bernaschi, M.; Castiglione, F.

    In Ref. 1, a new model for the description of the financial markets dynamics has been proposed. Traders move on a two dimensional lattice and interact by means of mechanisms of mutual influence. In the present paper, we present results from large-scale simulations of the same model enhanced by the introduction of rational traders modeled as moving-averages followers. The dynamics now accounts for log-normal distribution of volatility which is consistent with some observation of real financial indexes7 at least for the central part of the distribution.

  14. Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions

    PubMed Central

    Banik, Shipra; Khodadad Khan, A. F. M.; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange. PMID:24701205

  15. Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

    PubMed

    Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

  16. 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

  17. 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

  18. 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

  19. A study of correlations in the stock market

    NASA Astrophysics Data System (ADS)

    Sharma, Chandradew; Banerjee, Kinjal

    2015-08-01

    We study the various sectors of the Bombay Stock Exchange (BSE) for a period of 8 years from April 2006 to March 2014. Using the data of daily returns of a period of eight years we make a direct model free analysis of the pattern of the sectorial indices movement and the correlations among them. Our analysis shows significant auto correlation among the individual sectors and also strong cross-correlation among sectors. We also find that auto correlations in some of the sectors persist in time. This is a very significant result and has not been reported so far in Indian context. These findings will be very useful in model building for prediction of price movement of equities, derivatives and portfolio management. We show that the Random Walk Hypothesis is not applicable in modeling the Indian market and mean-variance-skewness-kurtosis based portfolio optimization might be required. We also find that almost all sectors are highly correlated during large fluctuation periods and have only moderate correlation during normal periods.

  20. Cross-correlation analysis of stock markets using EMD and EEMD

    NASA Astrophysics Data System (ADS)

    Xu, Mengjia; Shang, Pengjian; Lin, Aijing

    2016-01-01

    Empirical mode decomposition (EMD) is a data-driven signal analysis method for nonlinear and nonstationary data. Since it is intuitive, direct, posterior and adaptive, EMD is widely applied to various fields of study. In this paper, EMD and ensemble empirical mode decomposition (EEMD), a modified method of EMD, are applied to financial time series. Through analyzing the intrinsic mode functions (IMFs) of EMD and EEMD, we find EEMD method performs better on the orthogonality of IMFs than EMD. With clustering the ordered frequencies of IMFs, the IMFs obtained from EEMD method are grouped into high-, medium-, and low-frequency components, representing the short-, medium-, and long-term volatilities of the index sequences, respectively. With the cross-correlation analysis of DCCA cross-correlation coefficient, our findings allow us to gain further and detailed insight into the cross-correlations of stock markets.

  1. Application of the Beck model to stock markets: Value-at-Risk and portfolio risk assessment

    NASA Astrophysics Data System (ADS)

    Kozaki, M.; Sato, A.-H.

    2008-02-01

    We apply the Beck model, developed for turbulent systems that exhibit scaling properties, to stock markets. Our study reveals that the Beck model elucidates the properties of stock market returns and is applicable to practical use such as the Value-at-Risk estimation and the portfolio analysis. We perform empirical analysis with daily/intraday data of the S&P500 index return and find that the volatility fluctuation of real markets is well-consistent with the assumptions of the Beck model: The volatility fluctuates at a much larger time scale than the return itself and the inverse of variance, or “inverse temperature”, β obeys Γ-distribution. As predicted by the Beck model, the distribution of returns is well-fitted by q-Gaussian distribution of Tsallis statistics. The evaluation method of Value-at-Risk (VaR), one of the most significant indicators in risk management, is studied for q-Gaussian distribution. Our proposed method enables the VaR evaluation in consideration of tail risk, which is underestimated by the variance-covariance method. A framework of portfolio risk assessment under the existence of tail risk is considered. We propose a multi-asset model with a single volatility fluctuation shared by all assets, named the single β model, and empirically examine the agreement between the model and an imaginary portfolio with Dow Jones indices. It turns out that the single β model gives good approximation to portfolios composed of the assets with non-Gaussian and correlated returns.

  2. A new indicator of imminent occurrence of drawdown in the stock market

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2009-09-01

    The crashes in financial markets have caught the attention of many researchers since 1929 and several mathematical models have been proposed to try to forecast the occurrence of these events. The main idea in this work is to use a wavelet transform to detect imminent abrupt changes in a financial time series, which may be eventually related to the possibility of a crash. Case studies are conducted using wavelet approaches with data covering pre-crash and post-crash 1929, as well as more recent Hang Seng and IBOVESPA data. The financial crisis of 2008 also is analyzed using this method. These time series provide useful insights into the behavior of wavelet coefficients under the possibility of short term crashes in stock market. However, it is not a trivial task to infer an imminent drawdown by simply examining the pattern of the wavelet transform coefficients. Hence, an index (a real number between 0 and 1) is proposed to aggregate the information provided by the wavelet coefficients. The new index presented good capability of monitoring crashes and drawdown with small error margins, at least in the studied cases.

  3. Modeling Long-term Behavior of Stock Market Prices Using Differential Equations

    NASA Astrophysics Data System (ADS)

    Yang, Xiaoxiang; Zhao, Conan; Mazilu, Irina

    2015-03-01

    Due to incomplete information available in the market and uncertainties associated with the price determination process, the stock prices fluctuate randomly during a short period of time. In the long run, however, certain economic factors, such as the interest rate, the inflation rate, and the company's revenue growth rate, will cause a gradual shift in the stock price. Thus, in this paper, a differential equation model has been constructed in order to study the effects of these factors on the stock prices. The model obtained accurately describes the general trends in the AAPL and XOM stock price changes over the last ten years.

  4. The minimal length uncertainty and the quantum model for the stock market

    NASA Astrophysics Data System (ADS)

    Pedram, Pouria

    2012-03-01

    We generalize the recently proposed quantum model for the stock market by Zhang and Huang to make it consistent with the discrete nature of the stock price. In this formalism, the price of the stock and its trend satisfy the generalized uncertainty relation and the corresponding generalized Hamiltonian contains an additional term proportional to the fourth power of the trend. We study a driven infinite quantum well where information as the external field periodically fluctuates and show that the presence of the minimal trading value of stocks results in a positive shift in the characteristic frequencies of the quantum system. The connection between the information frequency and the transition probabilities is discussed finally.

  5. 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.

  6. Entropy: A new measure of stock market volatility?

    NASA Astrophysics Data System (ADS)

    Bentes, Sonia R.; Menezes, Rui

    2012-11-01

    When uncertainty dominates understanding stock market volatility is vital. There are a number of reasons for that. On one hand, substantial changes in volatility of financial market returns are capable of having significant negative effects on risk averse investors. In addition, such changes can also impact on consumption patterns, corporate capital investment decisions and macroeconomic variables. Arguably, volatility is one of the most important concepts in the whole finance theory. In the traditional approach this phenomenon has been addressed based on the concept of standard-deviation (or variance) from which all the famous ARCH type models - Autoregressive Conditional Heteroskedasticity Models- depart. In this context, volatility is often used to describe dispersion from an expected value, price or model. The variability of traded prices from their sample mean is only an example. Although as a measure of uncertainty and risk standard-deviation is very popular since it is simple and easy to calculate it has long been recognized that it is not fully satisfactory. The main reason for that lies in the fact that it is severely affected by extreme values. This may suggest that this is not a closed issue. Bearing on the above we might conclude that many other questions might arise while addressing this subject. One of outstanding importance, from which more sophisticated analysis can be carried out, is how to evaluate volatility, after all? If the standard-deviation has some drawbacks shall we still rely on it? Shall we look for an alternative measure? In searching for this shall we consider the insight of other domains of knowledge? In this paper we specifically address if the concept of entropy, originally developed in physics by Clausius in the XIX century, which can constitute an effective alternative. Basically, what we try to understand is, which are the potentialities of entropy compared to the standard deviation. But why entropy? The answer lies on the fact

  7. Identifying the multiscale impacts of crude oil price shocks on the stock market in China at the sector level

    NASA Astrophysics Data System (ADS)

    Huang, Shupei; An, Haizhong; Gao, Xiangyun; Huang, Xuan

    2015-09-01

    The aim of this research is to investigate the multiscale dynamic linkages between crude oil price and the stock market in China at the sector level. First, the Haar à trous wavelet transform is implemented to extract multiscale information from the original time series. Furthermore, we incorporate the vector autoregression model to estimate the dynamic relationship pairing the Brent oil price and each sector stock index at each scale. There is a strong evidence showing that there are bidirectional Granger causality relationships between most of the sector stock indices and the crude oil price in the short, medium and long terms, except for those in the health, utility and consumption sectors. In fact, the impacts of the crude oil price shocks vary for different sectors over different time horizons. More precisely, the energy, information, material and telecommunication sector stock indices respond to crude oil price shocks negatively in the short run and positively in the medium and long runs, terms whereas the finance sector responds positively over all three time horizons. Moreover, the Brent oil price shocks have a stronger influence on the stock indices of sectors other than the health, optional and utility sectors in the medium and long terms than in the short term. The results obtained suggest implication of this paper as that the investment and policymaking decisions made during different time horizons should be based on the information gathered from each corresponding time scale.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. Antibubble and prediction of China's stock market and real-estate

    NASA Astrophysics Data System (ADS)

    Zhou, Wei-Xing; Sornette, Didier

    2004-06-01

    We show that the Chinese stock markets are quite different and decoupled from Western markets (which include Tokyo). We document a well-developed log-periodic power-law antibubble in China's stock market, which started in August 2001. We argue that the current stock market antibubble is sustained by a contemporary active unsustainable real-estate bubble in China. The characteristic parameters of the antibubble have exhibited remarkable stability over one year (October 2002-October 2003). Many tests, including predictability over different horizons and time periods, confirm the high significance of the antibubble detection. Based on an analysis including data up to 2003/10/28, we have predicted that the Chinese stock market will stop its negative trend around the end of 2003 and start going up, appreciating by at least 25% in the following 6 months. We present a partial assessment of this prediction at the time of revision of this manuscript (early January 2004). Notwithstanding the immature nature of the Chinese equity market and the strong influence of government policy, we have found maybe even stronger imprints of herding than in other mature markets. This is maybe due indeed to the immaturity of the Chinese market which seems to attract short-term investors more interested in fast gains than in long-term investments, thus promoting speculative herding.

  13. Are Price Limits Effective? An Examination of an Artificial Stock Market.

    PubMed

    Zhang, Xiaotao; Ping, Jing; Zhu, Tao; Li, Yuelei; Xiong, Xiong

    2016-01-01

    We investigated the inter-day effects of price limits policies that are employed in agent-based simulations. To isolate the impact of price limits from the impact of other factors, we built an artificial stock market with higher frequency price limits hitting. The trading mechanisms in this market are the same as the trading mechanisms in China's stock market. Then, we designed a series of simulations with and without price limits policy. The results of these simulations demonstrate that both upper and lower price limits can cause a volatility spillover effect and a trading interference effect. The process of price discovery will be delayed if upper price limits are imposed on a stock market; however, this phenomenon does not occur when lower price limits are imposed. PMID:27513330

  14. 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.

  15. Are Price Limits Effective? An Examination of an Artificial Stock Market

    PubMed Central

    Zhu, Tao; Li, Yuelei; Xiong, Xiong

    2016-01-01

    We investigated the inter-day effects of price limits policies that are employed in agent-based simulations. To isolate the impact of price limits from the impact of other factors, we built an artificial stock market with higher frequency price limits hitting. The trading mechanisms in this market are the same as the trading mechanisms in China’s stock market. Then, we designed a series of simulations with and without price limits policy. The results of these simulations demonstrate that both upper and lower price limits can cause a volatility spillover effect and a trading interference effect. The process of price discovery will be delayed if upper price limits are imposed on a stock market; however, this phenomenon does not occur when lower price limits are imposed. PMID:27513330

  16. Are Price Limits Effective? An Examination of an Artificial Stock Market.

    PubMed

    Zhang, Xiaotao; Ping, Jing; Zhu, Tao; Li, Yuelei; Xiong, Xiong

    2016-01-01

    We investigated the inter-day effects of price limits policies that are employed in agent-based simulations. To isolate the impact of price limits from the impact of other factors, we built an artificial stock market with higher frequency price limits hitting. The trading mechanisms in this market are the same as the trading mechanisms in China's stock market. Then, we designed a series of simulations with and without price limits policy. The results of these simulations demonstrate that both upper and lower price limits can cause a volatility spillover effect and a trading interference effect. The process of price discovery will be delayed if upper price limits are imposed on a stock market; however, this phenomenon does not occur when lower price limits are imposed.

  17. 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.

  18. Trend extraction using empirical mode decomposition and statistical empirical mode decomposition: Case study: Kuala Lumpur stock market

    NASA Astrophysics Data System (ADS)

    Jaber, Abobaker M.

    2014-12-01

    Two nonparametric methods for prediction and modeling of financial time series signals are proposed. The proposed techniques are designed to handle non-stationary and non-linearity behave and to extract meaningful signals for reliable prediction. Due to Fourier Transform (FT), the methods select significant decomposed signals that will be employed for signal prediction. The proposed techniques developed by coupling Holt-winter method with Empirical Mode Decomposition (EMD) and it is Extending the scope of empirical mode decomposition by smoothing (SEMD). To show performance of proposed techniques, we analyze daily closed price of Kuala Lumpur stock market index.

  19. Empirical regularities of order placement in the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gu, Gao-Feng; Chen, Wei; Zhou, Wei-Xing

    2008-05-01

    Using ultra-high-frequency data extracted from the order flows of 23 stocks traded on the Shenzhen Stock Exchange, we study the empirical regularities of order placement in the opening call auction, cool period and continuous auction. The distributions of relative logarithmic prices against reference prices in the three time periods are qualitatively the same with quantitative discrepancies. The order placement behavior is asymmetric between buyers and sellers and between the inside-the-book orders and outside-the-book orders. In addition, the conditional distributions of relative prices in the continuous auction are independent of the bid-ask spread and volatility. These findings are crucial to build an empirical behavioral microscopic model based on order flows for Chinese stocks.

  20. Life insurance investment and stock market participation in Europe.

    PubMed

    Cavapozzi, Danilo; Trevisan, Elisabetta; Weber, Guglielmo

    2013-03-01

    In most European countries life insurance has played a key role in household portfolios, to the extent that it has often been the first asset ever purchased. In this paper we use life history data from a host of European countries to investigate the role of life insurance investment in shaping individuals' attitudes towards participation in stocks and mutual funds. We show that individuals who purchased a life insurance policy are more likely to invest in stocks and mutual funds later. On the one hand, these findings support the notion that life insurance policies play an educational role in financial investment. On the other hand, they are also consistent with behavioural models where economic agents are first concerned with avoiding unacceptable adverse scenarios by purchasing low risk investments, such as life insurance policies, and then invest in riskier assets, such as stocks and mutual funds, to obtain higher economic returns.

  1. Trading strategy based on dynamic mode decomposition: Tested in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Cui, Ling-xiao; Long, Wen

    2016-11-01

    Dynamic mode decomposition (DMD) is an effective method to capture the intrinsic dynamical modes of complex system. In this work, we adopt DMD method to discover the evolutionary patterns in stock market and apply it to Chinese A-share stock market. We design two strategies based on DMD algorithm. The strategy which considers only timing problem can make reliable profits in a choppy market with no prominent trend while fails to beat the benchmark moving-average strategy in bull market. After considering the spatial information from spatial-temporal coherent structure of DMD modes, we improved the trading strategy remarkably. Then the DMD strategies profitability is quantitatively evaluated by performing SPA test to correct the data-snooping effect. The results further prove that DMD algorithm can model the market patterns well in sideways market.

  2. Non-linear characteristics and long-range correlations in Asian stock markets

    NASA Astrophysics Data System (ADS)

    Jiang, J.; Ma, K.; Cai, X.

    2007-05-01

    We test several non-linear characteristics of Asian stock markets, which indicates the failure of efficient market hypothesis and shows the essence of fractal of the financial markets. In addition, by using the method of detrended fluctuation analysis (DFA) to investigate the long range correlation of the volatility in the stock markets, we find that the crossover phenomena exist in the results of DFA. Further, in the region of small volatility, the scaling behavior is more complicated; in the region of large volatility, the scaling exponent is close to 0.5, which suggests the market is more efficient. All these results may indicate the possibility of characteristic multifractal scaling behaviors of the financial markets.

  3. Intraday volatility spillovers between spot and futures indices: Evidence from the Korean stock market

    NASA Astrophysics Data System (ADS)

    Kang, Sang Hoon; Cheong, Chongcheul; Yoon, Seong-Min

    2013-04-01

    This study provides empirical evidence of the relationship between spot and futures markets in Korea. In particular, the study focuses on the volatility spillover relationship between spot and futures markets by using three high-frequency (10 min, 30 min, and 1 h time-scales) intraday data sets of KOSPI 200 spot and futures contracts. The results indicate a strong bi-directional causal relationship between futures and spot markets, suggesting that return volatility in the spot market can influence that in the futures market and vice versa. Thus, the results indicate that new information is reflected in futures and spot markets simultaneously. This bi-directional causal relationship provides market participants with important guidance on understanding the intraday information transmission between the two markets. Thus, on a given trading day, there may be sudden and sharp increases or decreases in return volatility in the Korean stock market as a result of positive feedback and synchronization of spot and futures markets.

  4. Dependence structure of the Korean stock market in high frequency data

    NASA Astrophysics Data System (ADS)

    Kim, Min Jae; Kwak, Young Bin; Kim, Soo Yong

    2011-03-01

    This paper analyzes the evolution of the dependence structure for various time window intervals, known as Epps effect, using the Trade and Quote data of 663 actively traded stocks in Korean stock market. It is found that the random matrix theory analysis could not represent the dependence structure of the stock market in the microstructure regime. The Cook-Johnson copula is introduced as a parsimonious alternative method to handle this problem, and the existence of the Epps effect is confirmed for the 663 stocks using high frequency data. It was also found that large capitalization companies tend to have a stronger dependence structure, except for the largest capitalization group, since the phenomenon of price level resistance leads to the weak dependence structure in the largest capitalization group. In addition, grouping the industry as a sub-portfolio is an appropriate approach for hour interval traders, whereas this approach is not a strategy recommended for high frequency traders.

  5. Can we predict crashes? The case of the Brazilian stock market

    NASA Astrophysics Data System (ADS)

    Cajueiro, Daniel O.; Tabak, Benjamin M.; Werneck, Filipe K.

    2009-04-01

    In this study we analyze Brazilian stock prices to detect the development of bubbles and crashes in individual stocks using a log-periodic equation. We implement a genetic algorithm to calibrate the parameters of the model and we test the methodology for the most liquid stocks traded on the Brazilian Stock Market (Bovespa). In order to evaluate whether this approach is useful we employ nonparametric statistics and test whether returns after the predicted crash are negative and lower than returns before the crash. Empirical results are consistent with the prediction hypothesis, e.g., the method applied can be used to forecast the end of asset bubbles or large corrections in stock prices.

  6. Modeling EU electricity market competition using the residual supply index

    SciTech Connect

    Swinand, Gregory; Scully, Derek; Ffoulkes, Stuart; Kessler, Brian

    2010-11-15

    An econometric approach to related hourly Residual Supply Index to price-cost margins in the major EU electricity generation markets suggests that market structure, as measured by the RSI, is a significant explanatory factor for markups, even when scarcity and other explanatory variables are included. (author)

  7. Author Affiliation Index: A New Approach to Marketing Journal Ranking

    ERIC Educational Resources Information Center

    Pan, Yue; Chen, Carl R.

    2011-01-01

    Previous research has adopted various methods to assess the relative quality of academic marketing journals. This study, as a replication and extension of Chen and Huang (2007), introduces the Author Affiliation Index (AAI) as an alternative approach to assessing marketing journal quality. The AAI is defined as the ratio of articles authored by…

  8. A Theory for Market Impact: How Order Flow Affects Stock Price

    NASA Astrophysics Data System (ADS)

    Gerig, Austin

    2008-04-01

    It is known that the impact of transactions on stock price (market impact) is a concave function of the size of the order, but there exists little quantitative theory that suggests why this is so. I develop a quantitative theory for the market impact of hidden orders (orders that reflect the true intention of buying and selling) that matches the empirically measured result and that reproduces some of the non-trivial and universal properties of stock returns (returns are percent changes in stock price). The theory is based on a simple premise, that the stock market can be modeled in a mechanical way - as a device that translates order flow into an uncorrelated price stream. Given that order flow is highly autocorrelated, this premise requires that market impact (1) depends on past order flow and (2) is asymmetric for buying and selling. I derive the specific form for the dependence in (1) by assuming that current liquidity responds to information about all currently active hidden orders (liquidity is a measure of the price response to a transaction of a given size). This produces an equation that suggests market impact should scale logarithmically with total order size. Using data from the London Stock Exchange I empirically measure market impact and show that the result matches the theory. Also using empirical data, I qualitatively specify the asymmetry of (2). Putting all results together, I form a model for market impact that reproduces three universal properties of stock returns - that returns are uncorrelated, that returns are distributed with a power law tail, and that the magnitude of returns is highly autocorrelated (also known as clustered volatility).

  9. Investor Behavior and Flow-through Capability in the US Stock Market.

    PubMed

    Cano, Carlos; Jareño, Francisco; Tolentino, Marta

    2016-01-01

    This paper analyzes investor behavior depending on the flow-through capability (FTC) in the US stock market, because investors seek protection from inflation rate changes, and the FTC (a firm's ability to transmit inflation shocks to the prices of its products and services) is a key factor in investment decisions. Our estimates of the FTC of firms listed on the US stock exchange at the sector level are significantly different among industries, and we demonstrate a direct relationship between changes in stock prices (at the sector level) and FTC. These results would be relevant because they have important implications on investor behavior. PMID:27242585

  10. Investor Behavior and Flow-through Capability in the US Stock Market

    PubMed Central

    Cano, Carlos; Jareño, Francisco; Tolentino, Marta

    2016-01-01

    This paper analyzes investor behavior depending on the flow-through capability (FTC) in the US stock market, because investors seek protection from inflation rate changes, and the FTC (a firm's ability to transmit inflation shocks to the prices of its products and services) is a key factor in investment decisions. Our estimates of the FTC of firms listed on the US stock exchange at the sector level are significantly different among industries, and we demonstrate a direct relationship between changes in stock prices (at the sector level) and FTC. These results would be relevant because they have important implications on investor behavior. PMID:27242585

  11. Investor Behavior and Flow-through Capability in the US Stock Market.

    PubMed

    Cano, Carlos; Jareño, Francisco; Tolentino, Marta

    2016-01-01

    This paper analyzes investor behavior depending on the flow-through capability (FTC) in the US stock market, because investors seek protection from inflation rate changes, and the FTC (a firm's ability to transmit inflation shocks to the prices of its products and services) is a key factor in investment decisions. Our estimates of the FTC of firms listed on the US stock exchange at the sector level are significantly different among industries, and we demonstrate a direct relationship between changes in stock prices (at the sector level) and FTC. These results would be relevant because they have important implications on investor behavior.

  12. Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

    NASA Astrophysics Data System (ADS)

    Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

    2013-09-01

    In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.

  13. Stochastic frontier model approach for measuring stock market efficiency with different distributions.

    PubMed

    Hasan, Md Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md Azizul

    2012-01-01

    The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation. PMID:22629352

  14. Stochastic Frontier Model Approach for Measuring Stock Market Efficiency with Different Distributions

    PubMed Central

    Hasan, Md. Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md. Azizul

    2012-01-01

    The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time- varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation. PMID:22629352

  15. Forecasting VaR and ES of stock index portfolio: A Vine copula method

    NASA Astrophysics Data System (ADS)

    Zhang, Bangzheng; Wei, Yu; Yu, Jiang; Lai, Xiaodong; Peng, Zhenfeng

    2014-12-01

    Risk measurement has both theoretical and practical significance in risk management. Using daily sample of 10 international stock indices, firstly this paper models the internal structures among different stock markets with C-Vine, D-Vine and R-Vine copula models. Secondly, the Value-at-Risk (VaR) and Expected Shortfall (ES) of the international stock markets portfolio are forecasted using Monte Carlo method based on the estimated dependence of different Vine copulas. Finally, the accuracy of VaR and ES measurements obtained from different statistical models are evaluated by UC, IND, CC and Posterior analysis. The empirical results show that the VaR forecasts at the quantile levels of 0.9, 0.95, 0.975 and 0.99 with three kinds of Vine copula models are sufficiently accurate. Several traditional methods, such as historical simulation, mean-variance and DCC-GARCH models, fail to pass the CC backtesting. The Vine copula methods can accurately forecast the ES of the portfolio on the base of VaR measurement, and D-Vine copula model is superior to other Vine copulas.

  16. Modified generalized sample entropy and surrogate data analysis for stock markets

    NASA Astrophysics Data System (ADS)

    Xu, Mengjia; Shang, Pengjian; Huang, Jingjing

    2016-06-01

    In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as stock market. The method based on Hausdorff distance presents a different way of time series patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic and real-world data for providing the comparative study. Results show that the modified method is more sensitive to the change of dynamics and has richer information. In addition, exponential functions can be used to successfully fit the curves obtained from the modified method and quantify the changes of complexity for stock market data.

  17. Dependence structure of the commodity and stock markets, and relevant multi-spread strategy

    NASA Astrophysics Data System (ADS)

    Kim, Min Jae; Kim, Sehyun; Jo, Yong Hwan; Kim, Soo Yong

    2011-10-01

    Understanding the dependence structure between the commodity and stock markets is a crucial issue in constructing a portfolio. It can also help us to discover new opportunities to implement spread trading using multiple assets classified in the two different markets. This study analyzed the dependence structure of the commodity and stock markets using the random matrix theory technique and network analysis. Our results show that the stock and commodity markets must be handled as completely separated asset classes except for the oil and gold markets, so the performance enhancement of the mean-variance portfolio is significant as expected. In light of the fact that WTI 1 month futures and four oil-related stocks are strongly correlated, they were selected as basic ingredients to complement the multi-spread convergence trading strategy using a machine learning technique called the AdaBoost algorithm. The performance of this strategy for non-myopic investors, who can endure short-term loss, can be enhanced significantly on a risk measurement basis.

  18. Non-Equilibrium Patterns in the Space of the Stock Market Prices

    NASA Astrophysics Data System (ADS)

    Gligor, M.; Ignat, M.

    2002-11-01

    Using a phenomenological approach, we analyse the formation and the propagation of the patterns (or ‘dissipative structures’) in the stock market, the spatial coordinate being the bid-offer spread y, as a function of which the spectrum φ of deals is modelled. The stock market will be considered a distributed active medium that is a set of active elements (the brokers) interacting with others through deals (typically a diffusion process). The physical model used is the reaction-diffusion model. The reactive part of the reaction-diffusion equation is developed from a hot-spot mechanism, with a characteristic jump when φ passes the critical value φc. Solving the stationary equation according to the Dirichlet boundary conditions, we find the ‘hot deals’ regions, meaning regions of speculative transactions which can be considered ‘dissipation’ as they do not contribute to the gross national product. The time propagation of these patterns in the one-dimensional space considered could explain the evolution of markets towards speculative bubbles. These are frequently met in the frame of emerging stock markets. Financial data, which illustrate the physical model refer to Romania's stock market, Bucharest S.E.

  19. 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.

  20. Can Big Data Machines Analyze Stock Market Sentiment?

    PubMed

    Dhar, Vasant

    2014-12-01

    Do the massive amounts of social and professionally curated data on the Internet contain useful sentiment about the market that "big data machines" can extract systematically? If so, what are the important challenges in creating economic value from these diffuse sources? In this commentary, I delve into these questions and frame the challenges involved using recent market developments as an illustrative backdrop. PMID:27442753

  1. Can Big Data Machines Analyze Stock Market Sentiment?

    PubMed

    Dhar, Vasant

    2014-12-01

    Do the massive amounts of social and professionally curated data on the Internet contain useful sentiment about the market that "big data machines" can extract systematically? If so, what are the important challenges in creating economic value from these diffuse sources? In this commentary, I delve into these questions and frame the challenges involved using recent market developments as an illustrative backdrop.

  2. 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.

  3. 76 FR 64411 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-18

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... hereby given that on September 30, 2011, The NASDAQ Stock Market LLC (``NASDAQ'') filed with the... volatility may use the order type to avoid selling only a small portion of the order at the price...

  4. 75 FR 6748 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-02-10

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule... January 29, 2010, The NASDAQ Stock Market LLC (``NASDAQ'' or ``Exchange'') filed with the Securities and... use of non-standard cabinet sizes or special cabinet cooling equipment, or the re-selling of...

  5. 78 FR 3940 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-17

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify an Optional Historical Research and Administrative Report Fee... January 10, 2013, The NASDAQ Stock Market LLC (``NASDAQ'') filed with the Securities and...

  6. 77 FR 74538 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-14

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... Financial Industry Regulatory Authority (``FINRA'') December 10, 2012. Pursuant to Section 19(b)(1) of the... on November 26, 2012, The NASDAQ Stock Market LLC (the ``Exchange'') filed with the Securities...

  7. 75 FR 5822 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-02-04

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change, as Modified by Amendment No. 1 Thereto, To Amend Its Financial... hereby given that on January ] 21, 2010, The NASDAQ Stock Market LLC (the ``Exchange'' or...

  8. Empirical properties of inter-cancellation durations in the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gu, Gao-Feng; Xiong, Xiong; Zhang, Wei; Zhang, Yong-Jie; Zhou, Wei-Xing

    2014-03-01

    Order cancellation process plays a crucial role in the dynamics of price formation in order-driven stock markets and is important in the construction and validation of computational finance models. Based on the order flow data of 23 liquid stocks traded on the Shenzhen Stock Exchange in 2003, we investigate the empirical statistical properties of inter-cancellation durations in units of events defined as the waiting times between two consecutive cancellations. The inter-cancellation durations for both buy and sell orders of all the stocks favor a q-exponential distribution when the maximum likelihood estimation method is adopted; In contrast, both cancelled buy orders of 9 stocks and cancelled sell orders of 4 stocks prefer Weibull distribution when the nonlinear least-square estimation is used. Applying detrended fluctuation analysis (DFA), centered detrending moving average (CDMA) and multifractal detrended fluctuation analysis (MF-DFA) methods, we unveil that the inter-cancellation duration time series process long memory and multifractal nature for both buy and sell cancellations of all the stocks. Our findings show that order cancellation processes exhibit long-range correlated bursty behaviors and are thus not Poissonian.

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

    SciTech Connect

    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 the 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    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 the 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.

  11. Applications of physics to economics and finance: Money, income, wealth, and the stock market

    NASA Astrophysics Data System (ADS)

    Dragulescu, Adrian Antoniu

    Several problems arising in Economics and Finance are analyzed using concepts and quantitative methods from Physics. The dissertation is organized as follows: In the first chapter it is argued that in a closed economic system, money is conserved. Thus, by analogy with energy, the equilibrium probability distribution of money must follow the exponential Boltzmann-Gibbs law characterized by an effective temperature equal to the average amount of money per economic agent. The emergence of Boltzmann-Gibbs distribution is demonstrated through computer simulations of economic models. A thermal machine which extracts a monetary profit can be constructed between two economic systems with different temperatures. The role of debt and models with broken time-reversal symmetry for which the Boltzmann-Gibbs law does not hold, are discussed. In the second chapter, using data from several sources, it is found that the distribution of income is described for the great majority of population by an exponential distribution, whereas the high-end tail follows a power law. From the individual income distribution, the probability distribution of income for families with two earners is derived and it is shown that it also agrees well with the data. Data on wealth is presented and it is found that the distribution of wealth has a structure similar to the distribution of income. The Lorenz curve and Gini coefficient were calculated and are shown to be in good agreement with both income and wealth data sets. In the third chapter, the stock-market fluctuations at different time scales are investigated. A model where stock-price dynamics is governed by a geometrical (multiplicative) Brownian motion with stochastic variance is proposed. The corresponding Fokker-Planck equation can be solved exactly. Integrating out the variance, an analytic formula for the time-dependent probability distribution of stock price changes (returns) is found. The formula is in excellent agreement with the Dow

  12. Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone

    NASA Astrophysics Data System (ADS)

    Anagnostidis, P.; Varsakelis, C.; Emmanouilides, C. J.

    2016-04-01

    In this paper, the impact of the 2008 financial crisis on the weak-form efficiency of twelve Eurozone stock markets is investigated empirically. Efficiency is tested via the Generalized Hurst Exponent method, while dynamic Hurst exponents are estimated by means of the rolling window technique. To account for biases associated with the finite sample size and the leptokurtosis of the financial data, the statistical significance of the Hurst exponent estimates is assessed through a series of Monte-Carlo simulations drawn from the class of α-stable distributions. According to our results, the 2008 crisis has adversely affected stock price efficiency in most of the Eurozone capital markets, leading to the emergence of significant mean-reverting patterns in stock price movements.

  13. Statistical properties of daily ensemble variables in the Chinese stock markets

    NASA Astrophysics Data System (ADS)

    Gu, Gao-Feng; Zhou, Wei-Xing

    2007-09-01

    We study dynamical behavior of the Chinese stock markets by investigating the statistical properties of daily ensemble return and variety defined, respectively, as the mean and the standard deviation of the ensemble daily price return of a portfolio of stocks traded in China's stock markets on a given day. The distribution of the daily ensemble return has an exponential form in the center and power-law tails, while the variety distribution is lognormal in the bulk followed by a power-law tail for large variety. Based on detrended fluctuation analysis, R/S analysis and modified R/S analysis, we find evidence of long memory in the ensemble return and strong evidence of long memory in the evolution of variety.

  14. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... mechanism of a free and open, fair and orderly, market, and to protect investors; and the laws of the... shares, such as a newspaper of general circulation or a trade publication; (iv) No less frequently...

  15. Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market

    NASA Astrophysics Data System (ADS)

    Jiang, Jiaqi; Gu, Rongbao

    2016-04-01

    This paper generalizes the method of traditional singular value decomposition entropy by incorporating orders q of Rényi entropy. We analyze the predictive power of the entropy based on trajectory matrix using Shanghai Composite Index and Dow Jones Index data in both static test and dynamic test. In the static test on SCI, results of global granger causality tests all turn out to be significant regardless of orders selected. But this entropy fails to show much predictability in American stock market. In the dynamic test, we find that the predictive power can be significantly improved in SCI by our generalized method but not in DJI. This suggests that noises and errors affect SCI more frequently than DJI. In the end, results obtained using different length of sliding window also corroborate this finding.

  16. Empirical regularities of opening call auction in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gu, Gao-Feng; Ren, Fei; Ni, Xiao-Hui; Chen, Wei; Zhou, Wei-Xing

    2010-01-01

    We study the statistical regularities of an opening call auction using the ultra-high-frequency data of 22 liquid stocks traded on the Shenzhen Stock Exchange in 2003. The distribution of the relative price, defined as the relative difference between the order price in the opening call auction and the closing price on the last trading day, is asymmetric and that the distribution displays a sharp peak at the zero relative price and a relatively wide peak at the negative relative price. The detrended fluctuation analysis (DFA) method is adopted to investigate the long-term memory of relative order prices. We further study the statistical regularities of order sizes in the opening call auction, and observe a phenomenon of number preference, known as order size clustering. The probability density function (PDF) of order sizes could be well fitted by a q-Gamma function, and the long-term memory also exists in order sizes. In addition, both the average volume and the average number of orders decrease exponentially with the price level away from the best bid or ask price level in the limit-order book (LOB) established immediately after the opening call auction, and a price clustering phenomenon is observed.

  17. The Stock Market Crashes of 1929 and 1987: Linking History and Personal Finance Education

    ERIC Educational Resources Information Center

    Lopus, Jane S.

    2005-01-01

    This article discusses two twentieth-century stock market crashes: the crash of 1929 and the crash of 1987. When this material is presented to students, they see important parallels between the two historical events. But despite remarkable similarities in the severity and many other aspects of the two crashes, the crash of 1929 was followed by the…

  18. A morphological perceptron with gradient-based learning for Brazilian stock market forecasting.

    PubMed

    Araújo, Ricardo de A

    2012-04-01

    Several linear and non-linear techniques have been proposed to solve the stock market forecasting problem. However, a limitation arises from all these techniques and is known as the random walk dilemma (RWD). In this scenario, forecasts generated by arbitrary models have a characteristic one step ahead delay with respect to the time series values, so that, there is a time phase distortion in stock market phenomena reconstruction. In this paper, we propose a suitable model inspired by concepts in mathematical morphology (MM) and lattice theory (LT). This model is generically called the increasing morphological perceptron (IMP). Also, we present a gradient steepest descent method to design the proposed IMP based on ideas from the back-propagation (BP) algorithm and using a systematic approach to overcome the problem of non-differentiability of morphological operations. Into the learning process we have included a procedure to overcome the RWD, which is an automatic correction step that is geared toward eliminating time phase distortions that occur in stock market phenomena. Furthermore, an experimental analysis is conducted with the IMP using four complex non-linear problems of time series forecasting from the Brazilian stock market. Additionally, two natural phenomena time series are used to assess forecasting performance of the proposed IMP with other non financial time series. At the end, the obtained results are discussed and compared to results found using models recently proposed in the literature.

  19. 76 FR 29014 - Self-Regulatory Organizations; NASDAQ Stock Market, LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-19

    ... COMMISSION Self-Regulatory Organizations; NASDAQ Stock Market, LLC; Notice of Filing and Immediate... from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization... the principal office of the Exchange, and at the Commission's Public Reference Room. II....

  20. 77 FR 3024 - Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-20

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change Relating to Options Fees January 13, 2012. Pursuant to Section 19(b)(1) of the Securities Exchange Act of 1934...

  1. 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.

  2. A morphological perceptron with gradient-based learning for Brazilian stock market forecasting.

    PubMed

    Araújo, Ricardo de A

    2012-04-01

    Several linear and non-linear techniques have been proposed to solve the stock market forecasting problem. However, a limitation arises from all these techniques and is known as the random walk dilemma (RWD). In this scenario, forecasts generated by arbitrary models have a characteristic one step ahead delay with respect to the time series values, so that, there is a time phase distortion in stock market phenomena reconstruction. In this paper, we propose a suitable model inspired by concepts in mathematical morphology (MM) and lattice theory (LT). This model is generically called the increasing morphological perceptron (IMP). Also, we present a gradient steepest descent method to design the proposed IMP based on ideas from the back-propagation (BP) algorithm and using a systematic approach to overcome the problem of non-differentiability of morphological operations. Into the learning process we have included a procedure to overcome the RWD, which is an automatic correction step that is geared toward eliminating time phase distortions that occur in stock market phenomena. Furthermore, an experimental analysis is conducted with the IMP using four complex non-linear problems of time series forecasting from the Brazilian stock market. Additionally, two natural phenomena time series are used to assess forecasting performance of the proposed IMP with other non financial time series. At the end, the obtained results are discussed and compared to results found using models recently proposed in the literature. PMID:22391234

  3. Intuition and Professional Competence: Intuitive Versus Rational Forecasting of the Stock Market

    ERIC Educational Resources Information Center

    Harteis, Christian; Gruber, Hans

    2008-01-01

    This article argues that intuition is a crucial component of professional competence, and provides empirical evidence to support this claim. It was found that in most cases intuitive predictions of stock market development are better than rationally justified ones and that experts predict more precisely than novices on a descriptive data level.…

  4. 77 FR 52373 - Self-Regulatory Organizations; NASDAQ Stock Market, LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-29

    ...), 73 FR 69685 (November 19, 2008) (SR-BSE-2008-48). See also BX Rule 1013(a)(5). The process by which... Securities Exchange Act Release No. 58927 (November 10, 2008), 73 FR 69685 (November 19, 2008) (SR-BSE-2008... COMMISSION Self-Regulatory Organizations; NASDAQ Stock Market, LLC; Notice of Filing and...

  5. Gold price effect on stock market: A Markov switching vector error correction approach

    NASA Astrophysics Data System (ADS)

    Wai, Phoong Seuk; Ismail, Mohd Tahir; Kun, Sek Siok

    2014-06-01

    Gold is a popular precious metal where the demand is driven not only for practical use but also as a popular investments commodity. While stock market represents a country growth, thus gold price effect on stock market behavior as interest in the study. Markov Switching Vector Error Correction Models are applied to analysis the relationship between gold price and stock market changes since real financial data always exhibit regime switching, jumps or missing data through time. Besides, there are numerous specifications of Markov Switching Vector Error Correction Models and this paper will compare the intercept adjusted Markov Switching Vector Error Correction Model and intercept adjusted heteroskedasticity Markov Switching Vector Error Correction Model to determine the best model representation in capturing the transition of the time series. Results have shown that gold price has a positive relationship with Malaysia, Thailand and Indonesia stock market and a two regime intercept adjusted heteroskedasticity Markov Switching Vector Error Correction Model is able to provide the more significance and reliable result compare to intercept adjusted Markov Switching Vector Error Correction Models.

  6. A Noncomputerized Version of the Williams and Walker Stock Market Experiment in a Finance Course.

    ERIC Educational Resources Information Center

    Bell, Christopher R.

    1993-01-01

    Asserts that the computerized stock market simulation described by Williams and Walker is complex and a better approach to teaching financial economics. Describes a noncomputerized version of the same teaching activity used to teach asset valuation to undergraduate financial economics students. (CFR)

  7. 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.

  8. 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.

  9. A Stock-Market Game Using Mining Stocks for Economic-Geology Students.

    ERIC Educational Resources Information Center

    Mossman, David John

    1988-01-01

    Described is a game especially for senior economic geology students. The game challenges them to test their skills under present market conditions in an area of high consumer risk. Discussed are preparation and management of a portfolio, conducting research on various mining companies, and final accounting for results achieved in light of…

  10. Hidden cross-correlation patterns in stock markets based on permutation cross-sample entropy and PCA

    NASA Astrophysics Data System (ADS)

    Lin, Aijing; Shang, Pengjian; Zhong, Bo

    2014-12-01

    In this article, we investigate the hidden cross-correlation structures in Chinese stock markets and US stock markets by performing PCSE combined with PCA approach. It is suggested that PCSE can provide a more faithful and more interpretable description of the dynamic mechanism between time series than cross-correlation matrix. We show that this new technique can be adapted to observe stock markets especially during financial crisis. In order to identify and compare the interactions and structures of stock markets during financial crisis, as well as in normal periods, all the samples are divided into four sub-periods. The results imply that the cross-correlations between Chinese group are stronger than the US group in the most sub-periods. In particular, it is likely that the US stock markets are more integrated with each other during global financial crisis than during Asian financial crisis. However, our results illustrate that Chinese stock markets are not immune from the global financial crisis, although less integrated with other markets if they are compared with US stock markets.

  11. The position profiles of order cancellations in an emerging stock market

    NASA Astrophysics Data System (ADS)

    Gu, Gao-Feng; Xiong, Xiong; Ren, Fei; Zhou, Wei-Xing; Zhang, Wei

    2013-04-01

    Order submission and cancellation are two constituent actions of stock trading behaviors in order-driven markets. Order submission dynamics has been extensively studied for different markets, while order cancellation dynamics is less understood. There are two positions associated with a cancellation, that is, the price level in the limit-order book (LOB) and the position in the queue at each price level. We study the profiles of these two order cancellation positions through rebuilding the limit-order book using the order flow data of 23 liquid stocks traded on the Shenzhen Stock Exchange in the year 2003. We find that the profiles of relative price levels where cancellations occur obey a log-normal distribution. After normalizing the relative price level by removing the factor of order numbers stored at the price level, we find that the profiles exhibit a power-law scaling behavior on the right tails for both buy and sell orders. When focusing on the order cancellation positions in the queue at each price level, we find that the profiles increase rapidly in the front of the queue, and then fluctuate around a constant value till the end of the queue. These profiles are similar for different stocks. In addition, the profiles of cancellation positions can be fitted by an exponent function for both buy and sell orders. These two kinds of cancellation profiles seem universal for different stocks investigated and exhibit minor asymmetry between buy and sell orders. Our empirical findings shed new light on the order cancellation dynamics and pose constraints on the construction of order-driven stock market models.

  12. One-factor model for the cross-correlation matrix in the Vietnamese stock market

    NASA Astrophysics Data System (ADS)

    Nguyen, Quang

    2013-07-01

    Random matrix theory (RMT) has been applied to the analysis of the cross-correlation matrix of a financial time series. The most important findings of previous studies using this method are that the eigenvalue spectrum largely follows that of random matrices but the largest eigenvalue is at least one order of magnitude higher than the maximum eigenvalue predicted by RMT. In this work, we investigate the cross-correlation matrix in the Vietnamese stock market using RMT and find similar results to those of studies realized in developed markets (US, Europe, Japan) [9-18] as well as in other emerging markets[20,21,19,22]. Importantly, we found that the largest eigenvalue could be approximated by the product of the average cross-correlation coefficient and the number of stocks studied. We demonstrate this dependence using a simple one-factor model. The model could be extended to describe other characteristics of the realistic data.

  13. 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.

  14. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... passive foreign investment company (PFIC), including any PFIC stock owned directly or indirectly by an... the Form 8621, “Return by a Shareholder of a Passive Foreign Investment Company or Qualified Electing... eligible RIC is a regulated investment company that offers for sale, or has outstanding, any stock of...

  15. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... passive foreign investment company (PFIC), including any PFIC stock owned directly or indirectly by an... the Form 8621, “Return by a Shareholder of a Passive Foreign Investment Company or Qualified Electing... eligible RIC is a regulated investment company that offers for sale, or has outstanding, any stock of...

  16. On distribution of number of trades in different time windows in the stock market

    NASA Astrophysics Data System (ADS)

    Dremin, I. M.; Leonidov, A. V.

    2005-08-01

    Properties of distributions of the number of trades in different intraday time intervals for five stocks traded in MICEX are studied. The dependence of the mean number of trades on the capital turnover is analyzed. Correlation analysis using factorial and Hq moments demonstrates the multifractal nature of these distributions as well as some peculiar changes in the correlation pattern. Guided by the analogy with the analysis of particle multiplicity distributions in multiparticle production at high energies, an evolution equation relating changes in capital turnover and a number of trades is proposed. We argue that such equation can describe the observed features of the distribution of the number of trades in the stock market.

  17. Long Memory in STOCK Market Volatility: the International Evidence

    NASA Astrophysics Data System (ADS)

    Yang, Chunxia; Hu, Sen; Xia, Bingying; Wang, Rui

    2012-08-01

    It is still a hot topic to catch the auto-dependence behavior of volatility. Here, based on the measurement of average volatility, under different observation window size, we investigated the dependence of successive volatility of several main stock indices and their simulated GARCH(1, 1) model, there were obvious linear auto-dependence in the logarithm of volatility under a small observation window size and nonlinear auto-dependence under a big observation. After calculating the correlation and mutual information of the logarithm of volatility for Dow Jones Industrial Average during different periods, we find that some influential events can change the correlation structure and the volatilities of different periods have distinct influence on that of the remote future. Besides, GARCH model could produce similar behavior of dependence as real data and long memory property. But our analyses show that the auto-dependence of volatility in GARCH is different from that in real data, and the long memory is undervalued by GARCH.

  18. Mood and the market: can press reports of investors' mood predict stock prices?

    PubMed

    Cohen-Charash, Yochi; Scherbaum, Charles A; Kammeyer-Mueller, John D; Staw, Barry M

    2013-01-01

    We examined whether press reports on the collective mood of investors can predict changes in stock prices. We collected data on the use of emotion words in newspaper reports on traders' affect, coded these emotion words according to their location on an affective circumplex in terms of pleasantness and activation level, and created indices of collective mood for each trading day. Then, by using time series analyses, we examined whether these mood indices, depicting investors' emotion on a given trading day, could predict the next day's opening price of the stock market. The strongest findings showed that activated pleasant mood predicted increases in NASDAQ prices, while activated unpleasant mood predicted decreases in NASDAQ prices. We conclude that both valence and activation levels of collective mood are important in predicting trend continuation in stock prices.

  19. Mood and the Market: Can Press Reports of Investors' Mood Predict Stock Prices?

    PubMed Central

    Scherbaum, Charles A.; Kammeyer-Mueller, John D.

    2013-01-01

    We examined whether press reports on the collective mood of investors can predict changes in stock prices. We collected data on the use of emotion words in newspaper reports on traders' affect, coded these emotion words according to their location on an affective circumplex in terms of pleasantness and activation level, and created indices of collective mood for each trading day. Then, by using time series analyses, we examined whether these mood indices, depicting investors' emotion on a given trading day, could predict the next day's opening price of the stock market. The strongest findings showed that activated pleasant mood predicted increases in NASDAQ prices, while activated unpleasant mood predicted decreases in NASDAQ prices. We conclude that both valence and activation levels of collective mood are important in predicting trend continuation in stock prices. PMID:24015202

  20. 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).

  1. A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

    PubMed

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

  2. A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

    PubMed

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

  3. A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

    PubMed Central

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

  4. ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

    PubMed Central

    Shao, Xigao; Wu, Kun; Liao, Bifeng

    2012-01-01

    Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓp-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ1-norm multiple support vector regression model. PMID:23365561

  5. The price impact asymmetry of institutional trading in the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Ren, Fei; Zhong, Li-Xin

    2012-04-01

    The asymmetric price impact between the institutional purchases and sales of 32 liquid stocks in the Chinese stock market in 2003 is carefully studied. We analyze the price impact in both drawup and drawdown trends with consecutive positive and negative daily price changes, and test the dependence of the price impact asymmetry on the market condition. For most of the stocks, institutional sales have a larger price impact than institutional purchases, and a larger impact of institutional purchases exists only in a few stocks with primarily increasing tendencies. We further study the mean return of trades surrounding institutional transactions, and find that the asymmetric behavior also exists before and after institutional transactions. A new variable is proposed to investigate the order book structure, and it can partially explain the price impact of institutional transactions. A linear regression for the price impact of institutional transactions further confirms our finding that institutional sales primarily have a larger price impact than institutional purchases in the bearish year 2003.

  6. Statistical physics in foreign exchange currency and stock markets

    NASA Astrophysics Data System (ADS)

    Ausloos, M.

    2000-09-01

    Problems in economy and finance have attracted the interest of statistical physicists all over the world. Fundamental problems pertain to the existence or not of long-, medium- or/and short-range power-law correlations in various economic systems, to the presence of financial cycles and on economic considerations, including economic policy. A method like the detrended fluctuation analysis is recalled emphasizing its value in sorting out correlation ranges, thereby leading to predictability at short horizon. The ( m, k)-Zipf method is presented for sorting out short-range correlations in the sign and amplitude of the fluctuations. A well-known financial analysis technique, the so-called moving average, is shown to raise questions to physicists about fractional Brownian motion properties. Among spectacular results, the possibility of crash predictions has been demonstrated through the log-periodicity of financial index oscillations.

  7. Multifractality of stock markets based on cumulative distribution function and multiscale multifractal analysis

    NASA Astrophysics Data System (ADS)

    Lin, Aijing; Shang, Pengjian

    2016-04-01

    Considering the diverse application of multifractal techniques in natural scientific disciplines, this work underscores the versatility of multiscale multifractal detrended fluctuation analysis (MMA) method to investigate artificial and real-world data sets. The modified MMA method based on cumulative distribution function is proposed with the objective of quantifying the scaling exponent and multifractality of nonstationary time series. It is demonstrated that our approach can provide a more stable and faithful description of multifractal properties in comprehensive range rather than fixing the window length and slide length. Our analyzes based on CDF-MMA method reveal significant differences in the multifractal characteristics in the temporal dynamics between US and Chinese stock markets, suggesting that these two stock markets might be regulated by very different mechanism. The CDF-MMA method is important for evidencing the stable and fine structure of multiscale and multifractal scaling behaviors and can be useful to deepen and broaden our understanding of scaling exponents and multifractal characteristics.

  8. 76 FR 77032 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-09

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... Market LLC (``NASDAQ'' or the ``Exchange'') filed with the Securities and Exchange Commission...) the shares of liquidity provided in all securities through one of its Market Participant...

  9. MainXchange in the Classroom: The New Internet Stock Market Game. Teacher's Guide and Student Activities.

    ERIC Educational Resources Information Center

    1998

    This teaching guide/student activities booklet, for grades 6-9 and 7-11, outlines an Internet-based stock exchange simulation that allows students to learn about the stock market in a fun format. The simulation (the "MainXchange") described in the booklet offers students the opportunity to engage in "real-life" investing, while exploring and…

  10. 76 FR 52724 - Self-Regulatory Organizations; the NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-23

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; the NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Extend the Pilot Period of the Trading Pause for NMS Stocks August...

  11. 76 FR 34781 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-14

    ... (April 29, 2011), 76 FR 25730 (May 5, 2011) (SR-NASDAQ-2011-056). The Commission notes that SR-NASDAQ... Event'' means: a reverse stock split, re-incorporation or a change in the Company's place of... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed...

  12. 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.

  13. Hybrid intelligent methodology to design translation invariant morphological operators for Brazilian stock market prediction.

    PubMed

    Araújo, Ricardo de A

    2010-12-01

    This paper presents a hybrid intelligent methodology to design increasing translation invariant morphological operators applied to Brazilian stock market prediction (overcoming the random walk dilemma). The proposed Translation Invariant Morphological Robust Automatic phase-Adjustment (TIMRAA) method consists of a hybrid intelligent model composed of a Modular Morphological Neural Network (MMNN) with a Quantum-Inspired Evolutionary Algorithm (QIEA), which searches for the best time lags to reconstruct the phase space of the time series generator phenomenon and determines the initial (sub-optimal) parameters of the MMNN. Each individual of the QIEA population is further trained by the Back Propagation (BP) algorithm to improve the MMNN parameters supplied by the QIEA. Also, for each prediction model generated, it uses a behavioral statistical test and a phase fix procedure to adjust time phase distortions observed in stock market time series. Furthermore, an experimental analysis is conducted with the proposed method through four Brazilian stock market time series, and the achieved results are discussed and compared to results found with random walk models and the previously introduced Time-delay Added Evolutionary Forecasting (TAEF) and Morphological-Rank-Linear Time-lag Added Evolutionary Forecasting (MRLTAEF) methods.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Random matrix theory and cross-correlations in global financial indices and local stock market indices

    NASA Astrophysics Data System (ADS)

    Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo

    2013-02-01

    We analyzed cross-correlations between price fluctuations of global financial indices (20 daily stock indices over the world) and local indices (daily indices of 200 companies in the Korean stock market) by using random matrix theory (RMT). We compared eigenvalues and components of the largest and the second largest eigenvectors of the cross-correlation matrix before, during, and after the global financial the crisis in the year 2008. We find that the majority of its eigenvalues fall within the RMT bounds [ λ -, λ +], where λ - and λ + are the lower and the upper bounds of the eigenvalues of random correlation matrices. The components of the eigenvectors for the largest positive eigenvalues indicate the identical financial market mode dominating the global and local indices. On the other hand, the components of the eigenvector corresponding to the second largest eigenvalue are positive and negative values alternatively. The components before the crisis change sign during the crisis, and those during the crisis change sign after the crisis. The largest inverse participation ratio (IPR) corresponding to the smallest eigenvector is higher after the crisis than during any other periods in the global and local indices. During the global financial the crisis, the correlations among the global indices and among the local stock indices are perturbed significantly. However, the correlations between indices quickly recover the trends before the crisis.

  19. Store Impulse Marketing Strategies and Body Mass Index

    PubMed Central

    Collins, Rebecca; Hunter, Gerald; Ghosh-Dastidar, Bonnie; Dubowitz, Tamara

    2015-01-01

    Objectives. We quantified the use of placement and price reduction marketing strategies in different food retail outlets to identify associations between these strategies and the risk of overweight and obesity among customers. Methods. In 2011 we collected dietary and health information from 1372 residents in “food deserts” in Pittsburgh, PA. We audited neighborhood restaurants and food stores (n = 40) including 16 distant food venues at which residents reported shopping. We assessed end-aisle displays, special floor displays, cash register displays, and price reductions for sugar-sweetened beverages (SSBs); foods high in saturated oils, fats, and added sugars; and nutritious foods such as fruits, vegetables, and products with at least 51% whole grains. Results. Supermarkets and superstores had the largest numbers of displays and price reductions for low-nutrient foods. Exposure to displays of SSBs and foods high in saturated oils, fats, and added sugars and price reduction of SSBs was associated with increased body mass index. Conclusions. In-store marketing strategies of low-nutrient foods appear to be risk factors for a higher body mass index among regular shoppers. Future research is needed to confirm the causal role of marketing strategies in obesity. PMID:25521881

  20. Do stock prices drive people crazy?

    PubMed

    Lin, Chung-Liang; Chen, Chin-Shyan; Liu, Tsai-Ching

    2015-03-01

    This is the first research to examine a potential relation between stock market volatility and mental disorders. Using data on daily incidences of mental disorders in Taiwan over 4000 days from 1998 through 2009 to assess the time-series relation between stock price movements and mental disorders, we observe that stock price fluctuation clearly affects the hospitalization of mental disorders. We find that during a 12-year follow-up period, a low stock price index, a daily fall in the stock price index and consecutive daily falls in the stock price index are all associated with greater of mental disorders hospitalizations. A 1000-point fall in the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) increases the number of daily mental disorders hospitalizations by 4.71%. A 1% fall in the TAIEX in one single day increases daily hospitalizations for mental disorders by 0.36%. When the stock price index falls one consecutive day, it causes a daily increase of approximately 0.32% hospitalizations due to mental disorders on that day. Stock price index is found to be significant for both gender and all age groups. In addition, daily change is significant for both gender and middle-age groups, whereas accumulated change is significant for males and people aged 45-64. Stockholdings can help people accumulate wealth, but they can also increase mental disorders hospitalizations. In other words, stock price fluctuations do drive people crazy.

  1. 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.

  2. Recession Depression: Mental Health Effects of the 2008 Stock Market Crash*

    PubMed Central

    McInerney, Melissa; Mellor, Jennifer M.; Nicholas, Lauren Hersch

    2013-01-01

    Do sudden, large wealth losses affect mental health? We use exogenous variation in the interview dates of the 2008 Health and Retirement Study to assess the impact of large wealth losses on mental health among older U.S. adults. We compare cross-wave changes in wealth and mental health for respondents interviewed before and after the October 2008 stock market crash. We find that the crash reduced wealth and increased feelings of depression and use of antidepressant drugs, and that these effects were largest among respondents with high levels of stock holdings prior to the crash. These results suggest that sudden wealth losses cause immediate declines in subjective measures of mental health. However, we find no evidence that wealth losses lead to increases in clinically-validated measures of depressive symptoms or indicators of depression. PMID:24113241

  3. 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.

  4. 76 FR 12784 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-08

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify Fees for Members Using the NASDAQ Market Center March 2, 2011. Pursuant to Section 19(b)(1) of...

  5. 76 FR 57778 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-09-16

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify Fees for Members Using the NASDAQ Options Market September 12, 2011. Pursuant to Section 19(b)(1) of...

  6. The Impact of The Stock Market Game on Financial Literacy and Mathematics Achievement: Results from a National Randomized Controlled Trial

    ERIC Educational Resources Information Center

    Hinojosa, Trisha; Miller, Shazia; Swanlund, Andrew; Hallberg, Kelly; Brown, Megan; O'Brien, Brenna

    2010-01-01

    The Stock Market Game[TM] is an educational program supported by the Securities Industry and Financial Markets Association (SIFMA) Foundation for Investor Education. The program is designed to teach students the importance of saving and investing by building their financial literacy skills. The primary focus of the study was to measure the impact…

  7. 77 FR 57618 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-18

    ... The NASDAQ Stock Market LLC proposes to modify Chapter XV, entitled ``Options Pricing,'' at Section 2 governing pricing for NASDAQ members using the NASDAQ Options Market (``NOM''), NASDAQ's facility for..., the Proposed Rule Change 1. Purpose NASDAQ proposes to modify Chapter XV, entitled ``Options...

  8. 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.

  9. Fractional Brownian Motion with Stochastic Variance:. Modeling Absolute Returns in STOCK Markets

    NASA Astrophysics Data System (ADS)

    Roman, H. E.; Porto, M.

    We discuss a model for simulating a long-time memory in time series characterized in addition by a stochastic variance. The model is based on a combination of fractional Brownian motion (FBM) concepts, for dealing with the long-time memory, with an autoregressive scheme with conditional heteroskedasticity (ARCH), responsible for the stochastic variance of the series, and is denoted as FBMARCH. Unlike well-known fractionally integrated autoregressive models, FBMARCH admits finite second moments. The resulting probability distribution functions have power-law tails with exponents similar to ARCH models. This idea is applied to the description of long-time autocorrelations of absolute returns ubiquitously observed in stock markets.

  10. Black Monday on stock markets throughout the world - a new phenomenon of collective panic disorder? A psychiatric approach.

    PubMed

    Sperling, Wolfgang; Bleich, Stefan; Reulbach, Udo

    2008-12-01

    Drastic losses on the stock markets within short periods have been the subject of numerous investigations in view of the fact that they are often irrational. Stock exchanges around the world suffered dramatic losses on Monday 21 January 2008, and again recently on Monday 17 March 2008. Regardless of cultural affiliation, public reporting of the global collapse in stock prices on Monday was striking in its almost unified mood of panic, anxiety and general fear of further partially arbitrary trading losses. These partly irrational mechanisms of an international financial crisis seem to fulfil several criteria of typical panic disorders according to classification systems like ICD-10 or DSM-IV. The new phenomenon affects international stock markets in the sense of a global panic disorder (GPD).

  11. 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.

  12. Self-Organized Criticality and Stock Market Dynamics: an Empirical Study

    SciTech Connect

    M. Bartolozzi; D. B. Leinweber; A. W. Thomas

    2004-05-01

    The Stock Market is a complex self-interacting system, characterized by an intermittent behavior. Periods of high activity alternate with periods of relative calm. In the present work we investigate empirically about the possibility that the market is in a self-organized critical state (SOC). A wavelet transform method is used in order to separate high activity periods, related to the avalanches of sandpile models, from quiescent. A statistical analysis of the filtered data show a power law behavior in the avalanche size, duration and laminar times. The memory process, implied by the power law distribution, of the laminar times is not consistent with classical conservative models for self-organized criticality. We argue that a ''near-SOC'' state or a time dependence in the driver, which may be chaotic, can explain this behavior.

  13. A partisan effect in the efficiency of the US stock market

    NASA Astrophysics Data System (ADS)

    Alvarez-Ramirez, J.; Rodriguez, E.; Espinosa-Paredes, G.

    2012-10-01

    This work examines the presence of a partisan effect in the US markets over different presidential periods. The analysis is based on the computation of the fractal scaling dynamics of the Dow Jones Industrial Average by means of the detrended fluctuation analysis. The results indicated the presence of several cycles with dominant periods ranging from a 4 to 12 years/cycle. It is argued that these periods are within the range for business cycles reported in the recent literature. On the other hand, it is found that over Democratic terms the stock market tends to deviate from de random walk behavior, which suggests important differences in the economic policies implemented by each political party.

  14. The dependence of Islamic and conventional stocks: A copula approach

    NASA Astrophysics Data System (ADS)

    Razak, Ruzanna Ab; Ismail, Noriszura

    2015-09-01

    Recent studies have found that Islamic stocks are dependent on conventional stocks and they appear to be more risky. In Asia, particularly in Islamic countries, research on dependence involving Islamic and non-Islamic stock markets is limited. The objective of this study is to investigate the dependence between financial times stock exchange Hijrah Shariah index and conventional stocks (EMAS and KLCI indices). Using the copula approach and a time series model for each marginal distribution function, the copula parameters were estimated. The Elliptical copula was selected to present the dependence structure of each pairing of the Islamic stock and conventional stock. Specifically, the Islamic versus conventional stocks (Shariah-EMAS and Shariah-KLCI) had lower dependence compared to conventional versus conventional stocks (EMAS-KLCI). These findings suggest that the occurrence of shocks in a conventional stock will not have strong impact on the Islamic stock.

  15. Criticality and market efficiency in a simple realistic model of the stock market

    NASA Astrophysics Data System (ADS)

    Challet, Damien; Marsili, Matteo

    2003-09-01

    We discuss a simple model based on the minority game which reproduces the main stylized facts of anomalous fluctuations in finance. We present the analytic solution of the model in the thermodynamic limit. Stylized facts arise only close to a line of critical points with nontrivial properties, marking the transition to an unpredictable market. We show that the emergence of critical fluctuations close to the phase transition is governed by the interplay between the signal to noise ratio and the system size. These results provide a clear and consistent picture of financial markets, where stylized facts and verge of unpredictability are intimately related aspects of the same critical systems.

  16. Financial technical indicator based on chaotic bagging predictors for adaptive stock selection in Japanese and American markets

    NASA Astrophysics Data System (ADS)

    Suzuki, Tomoya; Ohkura, Yuushi

    2016-01-01

    In order to examine the predictability and profitability of financial markets, we introduce three ideas to improve the traditional technical analysis to detect investment timings more quickly. Firstly, a nonlinear prediction model is considered as an effective way to enhance this detection power by learning complex behavioral patterns hidden in financial markets. Secondly, the bagging algorithm can be applied to quantify the confidence in predictions and compose new technical indicators. Thirdly, we also introduce how to select more profitable stocks to improve investment performance by the two-step selection: the first step selects more predictable stocks during the learning period, and then the second step adaptively and dynamically selects the most confident stock showing the most significant technical signal in each investment. Finally, some investment simulations based on real financial data show that these ideas are successful in overcoming complex financial markets.

  17. 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.

  18. The risks and returns of stock investment in a financial market

    NASA Astrophysics Data System (ADS)

    Li, Jiang-Cheng; Mei, Dong-Cheng

    2013-03-01

    The risks and returns of stock investment are discussed via numerically simulating the mean escape time and the probability density function of stock price returns in the modified Heston model with time delay. Through analyzing the effects of delay time and initial position on the risks and returns of stock investment, the results indicate that: (i) There is an optimal delay time matching minimal risks of stock investment, maximal average stock price returns and strongest stability of stock price returns for strong elasticity of demand of stocks (EDS), but the opposite results for weak EDS; (ii) The increment of initial position recedes the risks of stock investment, strengthens the average stock price returns and enhances stability of stock price returns. Finally, the probability density function of stock price returns and the probability density function of volatility and the correlation function of stock price returns are compared with other literatures. In addition, good agreements are found between them.

  19. 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.

  20. Evolution of worldwide stock markets, correlation structure, and correlation-based graphs.

    PubMed

    Song, Dong-Ming; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2011-08-01

    We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period January 1996 to July 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term time scale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the nondiagonal elements of the correlation matrix, correlation-based graphs, and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of the correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks in order to detect the fast dynamics of successive changes of correlation-based graphs in a quantitative way.

  1. Evolution of worldwide stock markets, correlation structure, and correlation-based graphs

    NASA Astrophysics Data System (ADS)

    Song, Dong-Ming; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

    2011-08-01

    We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period January 1996 to July 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term time scale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the nondiagonal elements of the correlation matrix, correlation-based graphs, and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of the correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks in order to detect the fast dynamics of successive changes of correlation-based graphs in a quantitative way.

  2. The Proteomics Stock Market Project. A Cross-Disciplinary Collaboration in Biochemistry and Business Education

    NASA Astrophysics Data System (ADS)

    Keller, Heath; Cox, James R.

    2004-04-01

    Students taking courses in different disciplines can work together to add unique elements to their educational experience. A model for this type of pedagogical approach has been established in the Proteomics Stock Market Project, a collaborative effort between instructors and students in the Department of Chemistry and Department of Management, Marketing, and Business Administration at Murray State University. Stage I involved biochemistry students investigating the topic of proteomics and choosing companies for potential investment based only on scientific investigation. Marketing and management students completed Stage II and provided an investment analysis on the companies selected in Stage I. In Stage III, the biochemistry students focused on a particular company and investigated a protein-based therapeutic product. Blackboard software was utilized in each stage of the project to facilitate the exchange of information and electronic documents. This project was designed to give biochemistry students an appreciation for the emerging field of proteomics and the marketing and management students a flavor for real-world applications of business principles. During the project, students were exposed to ideas and concepts not typically covered in their courses. With this involvement, the students had the opportunity to gain a broader perspective of course content compared to a more traditional curriculum.

  3. Evolution of worldwide stock markets, correlation structure, and correlation-based graphs.

    PubMed

    Song, Dong-Ming; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2011-08-01

    We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period January 1996 to July 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term time scale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the nondiagonal elements of the correlation matrix, correlation-based graphs, and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of the correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks in order to detect the fast dynamics of successive changes of correlation-based graphs in a quantitative way. PMID:21929065

  4. An agent-based model of stock markets incorporating momentum investors

    NASA Astrophysics Data System (ADS)

    Wei, J. R.; Huang, J. P.; Hui, P. M.

    2013-06-01

    It has been widely accepted that there exist investors who adopt momentum strategies in real stock markets. Understanding the momentum behavior is of both academic and practical importance. For this purpose, we propose and study a simple agent-based model of trading incorporating momentum investors and random investors. The random investors trade randomly all the time. The momentum investors could be idle, buying or selling, and they decide on their action by implementing an action threshold that assesses the most recent price movement. The model is able to reproduce some of the stylized facts observed in real markets, including the fat-tails in returns, weak long-term correlation and scaling behavior in the kurtosis of returns. An analytic treatment of the model relates the model parameters to several quantities that can be extracted from real data sets. To illustrate how the model can be applied, we show that real market data can be used to constrain the model parameters, which in turn provide information on the behavior of momentum investors in different markets.

  5. Weather effects on the returns and volatility of the Shanghai stock market

    NASA Astrophysics Data System (ADS)

    Kang, Sang Hoon; Jiang, Zhuhua; Lee, Yeonjeong; Yoon, Seong-Min

    2010-01-01

    This study investigates the weather effects on returns as well as volatility in the Shanghai stock market. In order to analyze the influence of the opening of B-share market to domestic investors, it is assumed that domestic investors are more sensitive to the Shanghai local weather than foreign investors. In doing so, extreme weather condition dummies are generated by using the 21-day and 31-day moving average and its standard deviation. Empirical analysis provides two key results regarding weather effects. First, the weather effect exists in the A-share returns, but does not exist in the B-share returns over the whole period. In addition, the post-opening period shows the strong weather effect on B-share returns only, indicating that the market openness to domestic investors results in the weather effect. Second, the weather effect has a strong influence on the volatility of both A- and B-share returns. Similar to the case of returns, the weather effect on volatility is explained by the openness of B-share market.

  6. The use of the Hurst exponent to investigate the global maximum of the Warsaw Stock Exchange WIG20 index

    NASA Astrophysics Data System (ADS)

    Domino, Krzysztof

    2012-01-01

    The WIG20 index-the index of the 20 biggest companies traded on the Warsaw Stock Exchange-reached the global maximum on 29th October 2007. I have used the local DFA (Detrended Functional Analysis) to obtain the Hurst exponent (diffusion exponent) and investigate the signature of anti-correlation of share price evolution around the maximum. The analysis was applied to the share price evolution for variable DFA parameters. For many values of parameters, the evidence of anti-correlation near the WIG20 maximum was pointed out.

  7. US stock market efficiency over weekly, monthly, quarterly and yearly time scales

    NASA Astrophysics Data System (ADS)

    Rodriguez, E.; Aguilar-Cornejo, M.; Femat, R.; Alvarez-Ramirez, J.

    2014-11-01

    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. Recent developments in evolutionary economic theory (Lo, 2004) have tailored the concept of adaptive market hypothesis (AMH) by proposing that market efficiency is not an all-or-none concept, but rather market efficiency is a characteristic that varies continuously over time and across markets. Within the AMH framework, this work considers the Dow Jones Index Average (DJIA) for studying the deviations from the random walk behavior over time. It is found that the market efficiency also varies over different time scales, from weeks to years. The well-known detrended fluctuation analysis was used for the characterization of the serial correlations of the return sequences. The results from the empirical showed that interday and intraday returns are more serially correlated than overnight returns. Also, some insights in the presence of business cycles (e.g., Juglar and Kuznets) are provided in terms of time variations of the scaling exponent.

  8. Statistical properties of cross-correlation in the Korean stock market

    NASA Astrophysics Data System (ADS)

    Oh, G.; Eom, C.; Wang, F.; Jung, W.-S.; Stanley, H. E.; Kim, S.

    2011-01-01

    We investigate the statistical properties of the cross-correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the cross-correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original cross-correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The β_{473} coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function E(σ) with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E( σ) σ^{-γ}, with the exponent γ 2.92 and those for Asian currency crisis decreases significantly.

  9. Economy with the time delay of information flow—The stock market case

    NASA Astrophysics Data System (ADS)

    Miśkiewicz, Janusz

    2012-02-01

    Any decision process requires information about the past and present state of the system, but in an economy acquiring data and processing it is an expensive and time-consuming task. Therefore, the state of the system is often measured over some legal interval, analysed after the end of well defined time periods and the results announced much later before any strategic decision is envisaged. The various time delay roles have to be crucially examined. Here, a model of stock market coupled with an economy is investigated to emphasise the role of the time delay span on the information flow. It is shown that the larger the time delay the more important the collective behaviour of agents since one observes time oscillations in the absolute log-return autocorrelations.

  10. 77 FR 35732 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-14

    ... (``NOM''), NASDAQ's facility for executing and routing standardized equity and index options... Nasdaq 100 Index traded under the symbol MNX (``MNX'') as follows: Non-NOM market NOM market Customer...\\ for transactions in NDX: \\3\\ An order that adds liquidity is one that is entered into NOM and rests...

  11. 76 FR 34783 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-14

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Amend Rule 7034 Regarding Certain Co-Location Installation Fees June 8, 2011. Pursuant to Section 19(b)(1)...

  12. 78 FR 3945 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-17

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change Relating to Fees for Certain Co-Location Services January 11, 2013. Pursuant to Section 19(b)(1) of the...

  13. 77 FR 46535 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-03

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...-4. I. Self-Regulatory Organization's Statement of the Terms of Substance of the Proposed Rule Change...) No change. * * * * * II. Self-Regulatory Organization's Statement of the Purpose of, and...

  14. 75 FR 64379 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-19

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... 240.19b-4. I. Self-Regulatory Organization's Statement of the Terms of Substance of the Proposed Rule... month shall be waived. (b) No change. (c) No change. (d) No change. * * * * * II....

  15. 76 FR 9391 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-17

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... change from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory...-professional user per month shall be waived. (b) No change. (c) No change. (d) No change. * * * * * II....

  16. 75 FR 63238 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-14

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify the Requirements To Qualify for Credits as a Designated Liquidity Provider Under Rule 7018(i) October...

  17. 75 FR 36460 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-25

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the Terms of the... Organization's Statement of the Purpose of, and Statutory Basis for, the Proposed Rule Change In its...

  18. 75 FR 41258 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-15

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule.... \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the... forth in subsection (b)(2)-(4) above. (4) No change. * * * * * II. Self-Regulatory...

  19. 78 FR 50465 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-19

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate.... \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the... the principal office of the Exchange, and at the Commission's Public Reference Room. II....

  20. 76 FR 53521 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-26

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the Terms of Substance... Exchange, and at the Commission's Public Reference Room. II. Self-Regulatory Organization's Statement...

  1. 76 FR 51453 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-18

    ... Markets Plan; Securities Exchange Act Release No. 60405 (July 30, 2009), 74 FR 39362 (August 6, 2009); NOM.... For instance, Google is a stock with a high share price ($602.38 closing price on December 27th). Google options therefore may require special settings due to the risk involved in actively...

  2. 77 FR 21607 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-10

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify NASDAQ's Transaction Execution Fee and Credit Schedule April 5, 2012. Pursuant to Section 19(b)(1)...

  3. 76 FR 64403 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-18

    ... From the Federal Register Online via the Government Publishing Office ] SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change Relating to Customer Rebates To Add Liquidity September 22,...

  4. 77 FR 64167 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-18

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the Terms of Substance of the...-Regulatory Organization's Statement of the Purpose of, and Statutory Basis for, the Proposed Rule Change...

  5. 76 FR 13007 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-09

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... proposed rule change from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19-b4. I. Self... at http://www.sec.gov , and at the Commission's Public Reference Room. II....

  6. 77 FR 77141 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-31

    ..., and Finland and Baltic countries of Latvia and Estonia, operates First North and the Main Market. For... world during the height of the financial crisis in September and October 2008, First North stocks with..., 2012), 77 FR 22042 (April 12, 2012)(SR-NASDAQ-2012- 043)(notice of filing); and 68378 (December 6,...

  7. 75 FR 13629 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Approval of Proposed...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-22

    ... Stock Market LLC; Order Granting Approval of Proposed Rule Change To Modify the Press Release...,\\2\\ a proposed rule change to modify certain of Nasdaq's rules pertaining to its press release... Exchange Act Release No. 61461 (February 1, 2010), 75 FR 6241 (``Notice''). II. Description of...

  8. 76 FR 52727 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-23

    ... Organization's Statement on Burden on Competition NASDAQ does not believe that the proposed rule change will... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of a Proposed Rule Change Regarding Clerical Changes to Its Rules August 17, 2011. Pursuant...

  9. 77 FR 42073 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-17

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate.... \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the...), 73 FR 18587 (April 4, 2008) (SR-NASDAQ-2008-026 (notice of filing and immediate...

  10. 78 FR 40223 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-03

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's... Notice. II. Self-Regulatory Organization's Statement of the Purpose of, and Statutory Basis for,...

  11. 77 FR 61810 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-11

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate.... 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the Terms of Substance... change. * * * * * II. Self-Regulatory Organization's Statement of the Purpose of, and Statutory Basis...

  12. 78 FR 74206 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-10

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change Relating to Acceptable Trade Range December 4, 2013. Pursuant to Section 19(b)(1) of the Securities Exchange...

  13. 77 FR 62293 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-12

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change Relating to Inbound Routing From an Affiliated Exchange October 5, 2012... change as described in Items I and II below, which Items have been prepared by the Exchange....

  14. 78 FR 57905 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-20

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Correct a Typographical Error and an Incorrect Cross Reference in Rule 5635(e)(4) September 16, 2013....

  15. 76 FR 49809 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-11

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... change from interested persons. \\1\\ 15 U.S.C. 78s(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory... principal office, and at the Commission's Public Reference Room. II. Self-Regulatory...

  16. 75 FR 57091 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-17

    ... Substance of the Proposed Rule Change NASDAQ proposes to modify pricing for NASDAQ members using the NASDAQ... purposes of the Act. If the Commission takes such action, the Commission shall institute proceedings to... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and......

  17. 78 FR 25774 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-05-02

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule Change, as Modified by Amendment No. 2 Thereto, Relating to the Listing and Trading of the Shares of the First Trust Senior Loan Fund of First...

  18. Order flow dynamics around extreme price changes on an emerging stock market

    NASA Astrophysics Data System (ADS)

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

    2010-07-01

    We study the dynamics of order flows around large intraday price changes using ultra-high-frequency data from the Shenzhen Stock Exchange. We find a significant reversal of price for both intraday price decreases and increases with a permanent price impact. The volatility, the volume of different types of orders, the bid-ask spread and the volume imbalance increase before the extreme events and decay slowly as a power law, which forms a well-established peak. The volume of buy market orders increases faster and the corresponding peak appears earlier than for sell market orders around positive events, while the volume peak of sell market orders leads buy market orders in the magnitude and time around negative events. When orders are divided into four groups according to their aggressiveness, we find that the behaviors of order volume and order number are similar, except for buy limit orders and canceled orders that the peak of order number postpones 2 min later after the peak of order volume, implying that investors placing large orders are more informed and play a central role in large price fluctuations. We also study the relative rates of different types of orders and find differences in the dynamics of relative rates between buy orders and sell orders and between individual investors and institutional investors. There is evidence that institutions behave very differently from individuals and that they have more aggressive strategies. Combining these findings, we conclude that institutional investors are better informed and play a more influential role in driving large price fluctuations.

  19. 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.

  20. 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.

  1. The coupling analysis between stock market indices based on permutation measures

    NASA Astrophysics Data System (ADS)

    Shi, Wenbin; Shang, Pengjian; Xia, Jianan; Yeh, Chien-Hung

    2016-04-01

    Many information-theoretic methods have been proposed for analyzing the coupling dependence between time series. And it is significant to quantify the correlation relationship between financial sequences since the financial market is a complex evolved dynamic system. Recently, we developed a new permutation-based entropy, called cross-permutation entropy (CPE), to detect the coupling structures between two synchronous time series. In this paper, we extend the CPE method to weighted cross-permutation entropy (WCPE), to address some of CPE's limitations, mainly its inability to differentiate between distinct patterns of a certain motif and the sensitivity of patterns close to the noise floor. It shows more stable and reliable results than CPE does when applied it to spiky data and AR(1) processes. Besides, we adapt the CPE method to infer the complexity of short-length time series by freely changing the time delay, and test it with Gaussian random series and random walks. The modified method shows the advantages in reducing deviations of entropy estimation compared with the conventional one. Finally, the weighted cross-permutation entropy of eight important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.

  2. Crisis-like behavior in China's stock market and its interpretation.

    PubMed

    Fan, Fangli; Gao, Jianbo; Liang, Shuhong

    2015-01-01

    In order for China to play a bigger, more positive role in the world, it is important for China to have a healthy capital market. This perception motivates us to examine the health of China's capital market, especially the severity of the overall loss of the listed companies in China and the effects of accounting irregularities on the losses. We show the overall loss of the listed companies was very severe, in particular, crisis-like behavior emerged in the fourth quarter of 2002, 2004, 2005, and 2008. We further observe that loss in the fourth quarter was much greater than the average loss of the first three quarters in the same year. The most straightforward interpretation of this loss pattern is that companies underreported losses in the first three quarters, to boost their stock values in most time of the year. However, in the fourth quarter, accounting balance of the whole year dictated that the reported loss in the fourth quarter had to be much greater than the actual loss. Fortunately, such irregularity has been greatly reduced, thanks to the accounting reforms in China in 2007. PMID:25658454

  3. Crisis-Like Behavior in China's Stock Market and Its Interpretation

    PubMed Central

    Fan, Fangli; Gao, Jianbo; Liang, Shuhong

    2015-01-01

    In order for China to play a bigger, more positive role in the world, it is important for China to have a healthy capital market. This perception motivates us to examine the health of China's capital market, especially the severity of the overall loss of the listed companies in China and the effects of accounting irregularities on the losses. We show the overall loss of the listed companies was very severe, in particular, crisis-like behavior emerged in the fourth quarter of 2002, 2004, 2005, and 2008. We further observe that loss in the fourth quarter was much greater than the average loss of the first three quarters in the same year. The most straightforward interpretation of this loss pattern is that companies underreported losses in the first three quarters, to boost their stock values in most time of the year. However, in the fourth quarter, accounting balance of the whole year dictated that the reported loss in the fourth quarter had to be much greater than the actual loss. Fortunately, such irregularity has been greatly reduced, thanks to the accounting reforms in China in 2007. PMID:25658454

  4. Crisis-like behavior in China's stock market and its interpretation.

    PubMed

    Fan, Fangli; Gao, Jianbo; Liang, Shuhong

    2015-01-01

    In order for China to play a bigger, more positive role in the world, it is important for China to have a healthy capital market. This perception motivates us to examine the health of China's capital market, especially the severity of the overall loss of the listed companies in China and the effects of accounting irregularities on the losses. We show the overall loss of the listed companies was very severe, in particular, crisis-like behavior emerged in the fourth quarter of 2002, 2004, 2005, and 2008. We further observe that loss in the fourth quarter was much greater than the average loss of the first three quarters in the same year. The most straightforward interpretation of this loss pattern is that companies underreported losses in the first three quarters, to boost their stock values in most time of the year. However, in the fourth quarter, accounting balance of the whole year dictated that the reported loss in the fourth quarter had to be much greater than the actual loss. Fortunately, such irregularity has been greatly reduced, thanks to the accounting reforms in China in 2007.

  5. Self-similar log-periodic structures in western stock markets from 2000

    SciTech Connect

    M. Bartolozzi; S. Drozdz; D. B. Leinweber; J. Speth; A. W. Thomas

    2005-09-01

    The presence of log-periodic structures before and after stock market crashes is considered to be an imprint of an intrinsic discrete scale invariance (DSI) in this complex system. The fractal framework of the theory leaves open the possibility of observing self-similar log-periodic structures at different time scales. In the present work, we analyze the daily closures of four of the most important indices worldwide since 2000: the DAX for Germany and the NASDAQ-100, the S&P 500 and the Dow Jones for the United States. The qualitative behavior of these different markets is similar during the temporal frame studied. Evidence is found for decelerating log-periodic oscillations of duration about two years and starting in September 2000. Moreover, a nested sub-structure starting in May 2002 is revealed, bringing more evidence to support the hypothesis of self-similar, log-periodic behavior. Ongoing log-periodic oscillations are also revealed. A Lomb analysis over the aforementioned periods indicates a preferential scaling factor lambda~2. Higher order harmonics are also present. The spectral pattern of the data has been found to be similar to that of a Weierstrass-type function, used as a prototype of a log-periodic fractal function.

  6. Self-Similar Log-Periodic Structures in Western STOCK Markets from 2000

    NASA Astrophysics Data System (ADS)

    Bartolozzi, M.; Drożdż, S.; Leinweber, D. B.; Speth, J.; Thomas, A. W.

    The presence of log-periodic structures before and after stock market crashes is considered to be an imprint of an intrinsic discrete scale invariance (DSI) in this complex system. The fractal framework of the theory leaves open the possibility of observing self-similar log-periodic structures at different time scales. In the present work, we analyze the daily closures of four of the most important indices worldwide since 2000: the DAX for Germany and the NASDAQ-100, the S&P 500 and the Dow Jones for the United States. The qualitative behavior of these different markets is similar during the temporal frame studied. Evidence is found for decelerating log-periodic oscillations of duration about two years and starting in September 2000. Moreover, a nested sub-structure starting in May 2002 is revealed, bringing more evidence to support the hypothesis of self-similar, log-periodic behavior. Ongoing log-periodic oscillations are also revealed. A Lomb analysis over the aforementioned periods indicates a preferential scaling factor λ~2. Higher order harmonics are also present. The spectral pattern of the data has been found to be similar to that of a Weierstrass-type function, used as a prototype of a log-periodic fractal function.

  7. 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.

  8. Stock Exchange

    ERIC Educational Resources Information Center

    Silverman, Jerry Stuart

    1974-01-01

    Using play money, students buy and sell six types of stock certificates at prices determined periodically by tossing three dice; all students participate as investors, brokers, or banker. In addition to gaining practice on computational skills in a motivational game, students study the real stock market concurrently. (SD)

  9. Scaling and Volatility of Breakouts and Breakdowns in Stock Price Dynamics

    PubMed Central

    Liu, Lu; Wei, Jianrong; Huang, Jiping

    2013-01-01

    Background Because the movement of stock prices is not only ubiquitous in financial markets but also crucial for investors, extensive studies have been done to understand the law behind it. In particular, since the financial crisis in 2008, researchers have a more interest in investigating large market volatilities in order to grasp changing market trends. Methodology/Principal Findings In this work, we analyze the breakouts and breakdowns of both the Standard & Poor’s 500 Index in the US stock market and the Shanghai Composite Index in the Chinese stock market. The breakout usually represents an ongoing upward trend in technical analysis while the breakdown represents an ongoing downward trend. Based on the renormalization method, we introduce two parameters to quantize breakouts and breakdowns, respectively. We discover scaling behavior, characterized by power-law distributions for both the breakouts and breakdowns in the two financial markets with different power-law exponents, which reflect different market volatilities. In detail, the market volatility for breakdowns is usually larger than that for breakouts. Moreover, as an emerging market, the Chinese stock market has larger market volatilities for both the breakouts and breakdowns than the US stock market (a mature market). Further, the short-term volatilities show similar features for both the US stock market and the Chinese stock market. However, the medium-term volatilities in the US stock market are almost symmetrical for the breakouts and breakdowns, whereas those in the Chinese stock market appear to be asymmetrical for the breakouts and breakdowns. Conclusions/Signicance The methodology presented here provides a way to understand scaling and hence volatilities of breakouts and breakdowns in stock price dynamics. Our findings not only reveal the features of market volatilities but also make a comparison between mature and emerging financial markets. PMID:24376577

  10. Does Reviewing Lead to Better Learning and Decision Making? Answers from a Randomized Stock Market Experiment

    PubMed Central

    Wessa, Patrick; Holliday, Ian E.

    2012-01-01

    Background The literature is not univocal about the effects of Peer Review (PR) within the context of constructivist learning. Due to the predominant focus on using PR as an assessment tool, rather than a constructivist learning activity, and because most studies implicitly assume that the benefits of PR are limited to the reviewee, little is known about the effects upon students who are required to review their peers. Much of the theoretical debate in the literature is focused on explaining how and why constructivist learning is beneficial. At the same time these discussions are marked by an underlying presupposition of a causal relationship between reviewing and deep learning. Objectives The purpose of the study is to investigate whether the writing of PR feedback causes students to benefit in terms of: perceived utility about statistics, actual use of statistics, better understanding of statistical concepts and associated methods, changed attitudes towards market risks, and outcomes of decisions that were made. Methods We conducted a randomized experiment, assigning students randomly to receive PR or non–PR treatments and used two cohorts with a different time span. The paper discusses the experimental design and all the software components that we used to support the learning process: Reproducible Computing technology which allows students to reproduce or re–use statistical results from peers, Collaborative PR, and an AI–enhanced Stock Market Engine. Results The results establish that the writing of PR feedback messages causes students to experience benefits in terms of Behavior, Non–Rote Learning, and Attitudes, provided the sequence of PR activities are maintained for a period that is sufficiently long. PMID:22666385

  11. Multifractal detrended cross-correlation analysis of the oil-dependent economies: Evidence from the West Texas intermediate crude oil and the GCC stock markets

    NASA Astrophysics Data System (ADS)

    Ma, Feng; Zhang, Qian; Peng, Chen; Wei, Yu

    2014-09-01

    In this paper, we firstly investigate the cross-correlations between the crude oil market and the six GCC stock markets. Based on the analysis of the significant statistic Qcc(m) and the cross-correlation coefficient, we find that the cross-correlations between the crude oil market and the six GCC stock markets are all significant. Employing the method of the MF-DFA and MF-DXA, we further find that the auto-correlations of the crude oil market and the six GCC stock markets and cross-correlations between them are all the multifractality. Moreover, using the multifractal spectrum, we can also verify the multifractal characteristics between the crude oil market and the six GCC stock markets. Furthermore, we use the penalized contrast function to detect the structural break points of the WTI-Oil return series and its conditional volatility, and then discuss the cross-correlations between the crude oil and the six GCC stock markets in the different phases according to these break points. At last, we employ the technique of the rolling window to investigate the dynamic of the scaling exponent Hxy(q). In addition, we explore the relationship between the cross-correlation exponents Hxy(q) and the average scaling exponents [Hxx(q)+Hyy(q)]/2].

  12. Stock market network’s topological stability: Evidence from planar maximally filtered graph and minimal spanning tree

    NASA Astrophysics Data System (ADS)

    Yan, Xin-Guo; Xie, Chi; Wang, Gang-Jin

    2015-08-01

    We study the topological stability of stock market network by investigating the topological robustness, namely the ability of the network to resist structural or topological changes. The stock market network is extracted by minimal spanning tree (MST) and planar maximally filtered graph (PMFG). We find that the specific delisting thresholds of the listed companies exist in both MST and PMFG networks. In comparison with MST, PMFG provides more information and is better for the aim of exploring stock market network’s robustness. The PMFG before the US sub-prime crisis (i.e., from June 2005 to May 2007) has a stronger robustness against the intentional topological damage than the other two sub-periods (i.e., from June 2007 to May 2009 and from June 2009 to May 2011). We also find that the nonfractal property exists in MSTs of S&P 500, i.e., the highly connected nodes link with each other directly, which indicates that the MSTs are vulnerable to the removal of such important nodes. Moreover, the financial institutions and high technology companies are important in maintaining the stability of S&P 500 network.

  13. Research on the evolution of stock correlation based on maximal spanning trees

    NASA Astrophysics Data System (ADS)

    Yang, Chunxia; Zhu, Xueshuai; Li, Qian; Chen, Yanhua; Deng, Qiangqiang

    2014-12-01

    In this study, we choose the daily closing price of 268 constituent stocks of the S&P 500 index, 221 stocks of London Stock Exchange, 148 constituent stocks of the Shanghai Composite index and 152 constituent stocks of the Hang Seng index as the research objects and select the sample of all the stock markets from 2 January, 2003, to 16 September, 2013. For each stock market, first, using a moving window to scan through every stock return series and mutual information to measure the statistical interdependence between stock returns, we construct a corresponding weighted network in every given window. Then we study the evolution of stock correlation by analyzing the average mutual information, mutual information distribution and topology structure’s variation of the maximal spanning tree extracting from every weighted network. All the obtained results indicate that for all the stock markets, both the average mutual information and the standard deviation of mutual information distribution first gradually increase and they reach a peak during the full-outbreak periods, and finally, they decrease again. In addition, the topology structure of the maximal spanning tree also changes from compact star-like to loose chain-like first and then turns to compact star-like once more. All the facts tell us that the crisis does change the stock correlation and the stock correlation is from weak to strong first, and then becomes weak again.

  14. Simulation of a Hirschman-Herfindahl index without complete market share information.

    PubMed

    Nauenberg, Eric; Alkhamisi, Mahdi; Andrijuk, Yuri

    2004-01-01

    This paper utilizes maximum likelihood methods to simulate a Hirschman-Herfindahl index (HHI) for markets in which complete market share information is unavailable or delayed. Many jurisdictions either may be unable to administratively collect data or experience delays in collection that make data regarding turbulent markets of limited use. With the development of this method, regulatory authorities monitoring health-care competition or health-care firms can now use market surveys--in which reliable recall is often limited to the largest three or four firms--to produce an on-the-spot measure of market concentration.

  15. Topology of the South African stock market network across the 2008 financial crisis

    NASA Astrophysics Data System (ADS)

    Majapa, Mohamed; Gossel, Sean Joss

    2016-03-01

    This study uses the cross-correlations in the daily closing prices of the South African Top 100 companies listed on the JSE All share index (ALSI) from June 2003 to June 2013 to compute minimum spanning tree maps. In addition to the full sample, the analysis also uses three sub-periods to investigate the topological evolution before, during, and after the 2008 financial crisis. The findings show that although there is substantial clustering and homogeneity on the JSE, the most connected nodes are in the financial and resources sectors. The sub-sample results further reveal that the JSE network tree shrank in the run-up to, and during the financial crisis, and slowly expanded afterwards. In addition, the different clusters in the network are connected by various nodes that are significantly affected by diversification and credit market dynamics.

  16. Using recurrence plot analysis to distinguish between endogenous and exogenous stock market crashes

    NASA Astrophysics Data System (ADS)

    Guhathakurta, Kousik; Bhattacharya, Basabi; Chowdhury, A. Roy

    2010-05-01

    Recurrence Plots are graphical tools based on Phase Space Reconstruction. Recurrence Quantification Analysis (RQA) is a statistical quantification of RPs. RP and RQA are good at working with non-stationarity and noisy data, in detecting changes in data behavior, in particular in detecting breaks, like a phase transition and in informing about other dynamic properties of a time series. Endogenous Stock Market Crashes have been modeled as phase changes in recent times. Motivated by this, we have used RP and RQA techniques for detecting critical regimes preceding an endogenous crash seen as a phase transition and hence give an estimation of the initial bubble time. We have used a new method for computing RQA measures with confidence intervals. We have also used the techniques on a known exogenous crash to see if the RP reveals a different story or not. The analysis is made on Nifty, Hong Kong AOI and Dow Jones Industrial Average, taken over a time span of about 3 years for the endogenous crashes. Then the RPs of all time series have been observed, compared and discussed. All the time series have been first transformed into the classical momentum divided by the maximum Xmax of the time series over the time window which is considered in the specific analysis. RPs have been plotted for each time series, and RQA variables have been computed on different epochs. Our studies reveal that, in the case of an endogenous crash, we have been able to identify the bubble, while in the case of exogenous crashes the plots do not show any such pattern, thus helping us in identifying such crashes.

  17. Australian Thesaurus of Education Descriptors. A Word-Stock for Indexing and Retrieving Australian Educational Literature.

    ERIC Educational Resources Information Center

    Lavender, G. B.; Findlay, Margaret A.

    This core thesaurus of terms suitable for indexing Australian educational literature was developed by the Australian Council for Educational Research by means of a systematic and thorough revision of the "Thesaurus of ERIC Descriptors." Based on the actual terminology of education in Australia, this thesaurus includes: key words and phrases used…

  18. 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.

  19. Universal behaviour in the stock market: Time dynamics of the electronic orderbook

    NASA Astrophysics Data System (ADS)

    Kızılersü, Ayşe; Kreer, Markus; Thomas, Anthony W.; Feindt, Michael

    2016-07-01

    A consequence of the digital revolution is that share trading at the stock exchange takes place via electronic order books which are accessed by traders and investors via the internet. Our empirical findings of the London Stock Exchange demonstrate that once ultra-high frequency manipulation on time scales less than around ten milliseconds is excluded, all relevant changes in the order book happen with time differences that are randomly distributed and well described by a left-truncated Weibull distribution with universal shape parameter (independent of time and same for all stocks). The universal shape parameter corresponds to maximum entropy of the distribution.

  20. Correlation network analysis for multi-dimensional data in stocks market

    NASA Astrophysics Data System (ADS)

    Kazemilari, Mansooreh; Djauhari, Maman Abdurachman

    2015-07-01

    This paper shows how the concept of vector correlation can appropriately measure the similarity among multivariate time series in stocks network. The motivation of this paper is (i) to apply the RV coefficient to define the network among stocks where each of them is represented by a multivariate time series; (ii) to analyze that network in terms of topological structure of the stocks of all minimum spanning trees, and (iii) to compare the network topology between univariate correlation based on r and multivariate correlation network based on RV coefficient.

  1. Endogenous and exogenous dynamics in the fluctuations of capital fluxes. An empirical analysis of the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Jiang, Z.-Q.; Guo, L.; Zhou, W.-X.

    2007-06-01

    A phenomenological investigation of the endogenous and exogenous dynamics in the fluctuations of capital fluxes is carried out on the Chinese stock market using mean-variance analysis, fluctuation analysis, and their generalizations to higher orders. Non-universal dynamics have been found not only in the scaling exponent α, which is different from the universal values 1/2 and 1, but also in the distributions of the ratio η= σexo / σendo of individual stocks. Both the scaling exponent α of fluctuations and the Hurst exponent Hi increase in logarithmic form with the time scale Δt and the mean traded value per minute , respectively. We find that the scaling exponent αendo of the endogenous fluctuations is independent of the time scale. Multiscaling and multifractal features are observed in the data as well. However, the inhomogeneous impact model is not verified.

  2. A Hands-on Activity for Teaching the Poisson Distribution Using the Stock Market

    ERIC Educational Resources Information Center

    Dunlap, Mickey; Studstill, Sharyn

    2014-01-01

    The number of increases a particular stock makes over a fixed period follows a Poisson distribution. This article discusses using this easily-found data as an opportunity to let students become involved in the data collection and analysis process.

  3. To lag or not to lag? How to compare indices of stock markets that operate on different times

    NASA Astrophysics Data System (ADS)

    Sandoval, Leonidas

    2014-06-01

    Financial markets worldwide do not have the same working hours. As a consequence, the study of correlation or causality between financial market indices becomes dependent on whether we should use all indices on the same day or lagged indices in computations of correlation matrices. The answer this article proposes is that we should consider both, by representing original and lagged indices in the same network. We then obtain a better understanding of how indices that operate on different hours relate to each other. We use a diverse range of 79 stock market indices from around the world and study their correlation structure, the eigenvalues and eigenvectors of their correlations under different time periods and volatility, as well as the differences between the working hours of the stock exchanges in order to analyze the possible time zone effects and suggest ways to remove them. We also analyze the enlarged correlation matrix obtained from original and lagged indices and examine a network structure derived from it, thus showing connections between lagged and original indices that could not be well represented before.

  4. Stock Market Returns and Clinical Trial Results of Investigational Compounds: An Event Study Analysis of Large Biopharmaceutical Companies

    PubMed Central

    Hwang, Thomas J.

    2013-01-01

    Background For biopharmaceutical companies, investments in research and development are risky, and the results from clinical trials are key inflection points in the process. Few studies have explored how and to what extent the public equity market values clinical trial results. Methods Our study dataset matched announcements of clinical trial results for investigational compounds from January 2011 to May 2013 with daily stock market returns of large United States-listed pharmaceutical and biotechnology companies. Event study methodology was used to examine the relationship between clinical research events and changes in stock returns. Results We identified public announcements for clinical trials of 24 investigational compounds, including 16 (67%) positive and 8 (33%) negative events. The majority of announcements were for Phase 3 clinical trials (N = 13, 54%), and for oncologic (N = 7, 29%) and neurologic (N = 6, 24%) indications. The median cumulative abnormal returns on the day of the announcement were 0.8% (95% confidence interval [CI]: –2.3, 13.4%; P = 0.02) for positive events and –2.0% (95% CI: –9.1, 0.7%; P = 0.04) for negative events, with statistically significant differences from zero. In the day immediately following the announcement, firms with positive events were associated with stock price corrections, with median cumulative abnormal returns falling to 0.4% (95% CI: –3.8, 12.3%; P = 0.33). For firms with negative announcements, the median cumulative abnormal returns were –1.7% (95% CI: –9.5, 1.0%; P = 0.03), and remained significantly negative over the two day event window. The magnitude of abnormal returns did not differ statistically by indication, by trial phase, or between biotechnology and pharmaceutical firms. Conclusions The release of clinical trial results is an economically significant event and has meaningful effects on market value for large biopharmaceutical companies. Stock return

  5. Trends and Indicators: Pension Money in the Stock Market; Median Salaries of Chief Executives and Academic Officers, 1992-93; Faculty Pay and the Cost of Living.

    ERIC Educational Resources Information Center

    Chronicle of Higher Education, 1993

    1993-01-01

    Data presented include a graph comparing College Retirement Equities Fund progress with a major stock price index, 1990-93; a table of median salaries of chief academic and executive officers at public, private, and church-related colleges, by enrollment; and a comparison of faculty salaries and the Consumer Price Index, 1986-87 to 1991-92. (MSE)

  6. The effect of tick size on trading volume share in three competing stock markets

    NASA Astrophysics Data System (ADS)

    Nagumo, Shota; Shimada, Takashi; Ito, Nobuyasu

    2016-09-01

    The relationship between tick sizes and trading volume share in two and three competing markets is studied theoretically. By introducing a simple model which is equipped with multiple markets and non-strategic traders, we analytically calculate the share. It is shown that share is shifted from a market with a larger tick size to a market with a smaller tick size, and the size of share-shift is determined by difference between tick sizes not by ratio between tick sizes in both cases of two markets and three markets.

  7. Analysis of linkage effects among industry sectors in China's stock market before and after the financial crisis

    NASA Astrophysics Data System (ADS)

    Yang, Rui; Li, Xiangyang; Zhang, Tong

    2014-10-01

    This paper uses two physics-derived techniques, the minimum spanning tree and the hierarchical tree, to investigate the networks formed by CITIC (China International Trust and Investment Corporation) industry indices in three periods from 2006 to 2013. The study demonstrates that obvious industry clustering effects exist in the networks, and Durable Consumer Goods, Industrial Products, Information Technology, Frequently Consumption and Financial Industry are the core nodes in the networks. We also use the rolling window technique to investigate the dynamic evolution of the networks' stability, by calculating the mean correlations and mean distances, as well as the variance of correlations and the distances of these indices. China's stock market is still immature and subject to administrative interventions. Therefore, through this analysis, regulators can focus on monitoring the core nodes to ensure the overall stability of the entire market, while investors can enhance their portfolio allocations or investment decision-making.

  8. 77 FR 23788 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-20

    ... BATS Penny as well as BATS non-Penny Routing Fees to its members based on the type of options orders..., Firm, Market Maker and Professional orders in equity and index options to the BATS Exchange, Inc. (``BATS''). The Exchange's Routing Fees are located at Chapter XV, Section 2, entitled ``NASDAQ...

  9. 78 FR 24282 - Self-Regulatory Organizations; the NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-24

    ... Proposed Rule Change NASDAQ proposes to amend Chapter XV, entitled ``Options Pricing,'' at Section 2 governing pricing for NASDAQ members using the NASDAQ Options Market (``NOM''), NASDAQ's facility for executing and routing standardized equity and index options. Specifically, NOM proposes to amend its...

  10. 78 FR 19791 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-02

    ... Proposed Rule Change NASDAQ proposes to amend Chapter XV, entitled ``Options Pricing,'' at Section 2 governing pricing for NASDAQ members using the NASDAQ Options Market (``NOM''), NASDAQ's facility for executing and routing standardized equity and index options. Specifically, NOM proposes to amend its...

  11. 78 FR 11257 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-15

    ..., entitled ``Options Pricing,'' which governs pricing for NASDAQ members using the NASDAQ Options Market (``NOM''), NASDAQ's facility for executing and routing standardized equity and index options. The... Effectiveness of Proposed Rule Change Relating to a Pricing Clarification February 11, 2013. Pursuant to...

  12. Using dynamic mode decomposition to extract cyclic behavior in the stock market

    NASA Astrophysics Data System (ADS)

    Hua, Jia-Chen; Roy, Sukesh; McCauley, Joseph L.; Gunaratne, Gemunu H.

    2016-04-01

    The presence of cyclic expansions and contractions in the economy has been known for over a century. The work reported here searches for similar cyclic behavior in stock valuations. The variations are subtle and can only be extracted through analysis of price variations of a large number of stocks. Koopman mode analysis is a natural approach to establish such collective oscillatory behavior. The difficulty is that even non-cyclic and stochastic constituents of a finite data set may be interpreted as a sum of periodic motions. However, deconvolution of these irregular dynamical facets may be expected to be non-robust, i.e., to depend on specific data set. We propose an approach to differentiate robust and non-robust features in a time series; it is based on identifying robust features with reproducible Koopman modes, i.e., those that persist between distinct sub-groupings of the data. Our analysis of stock data discovered four reproducible modes, one of which has period close to the number of trading days/year. To the best of our knowledge these cycles were not reported previously. It is particularly interesting that the cyclic behaviors persisted through the great recession even though phase relationships between stocks within the modes evolved in the intervening period.

  13. NewsMarket 2.0: Analysis of News for Stock Price Forecasting

    NASA Astrophysics Data System (ADS)

    Barazzetti, Alessandro; Mastronardi, Rosangela

    Most of the existing financial research tools use a stock's historical price and technical indicators to predict future price trends without taking into account the impact of web news. The recent explosion of demand for information on financial investment management is driving the search for alternative methods of quantitative data analysis.

  14. Evidence of fueling of the 2000 new economy bubble by foreign capital inflow: implications for the future of the US economy and its stock market

    NASA Astrophysics Data System (ADS)

    Sornette, Didier; Zhou, Wei-Xing

    2004-02-01

    Previous analyses of a large ensemble of stock markets have demonstrated that a log-periodic power law (LPPL) behavior of the prices constitutes a qualifying signature of speculative bubbles that often land with a crash. We detect such a LPPL signature in the foreign capital inflow during the bubble on the US markets culminating in March 2000. We detect a weak synchronization and lag with the NASDAQ LPPL pattern. We propose to rationalize these observations by the existence of positive feedback loops between market-appreciation/increased-spending/increased-deficit-of-balance-of-payment/larger-foreign-surplus/increased-foreign-capital-inflows and so on. Our analysis suggests that foreign capital inflow has been following rather than causing the bubble. We then combine a macroeconomic analysis of feedback processes occurring between the economy and the stock market with a technical analysis of more than 200 years of the DJIA to investigate possible scenarios for the future, three years after the end of the bubble and deep into a bearish regime. We conclude that the low interest rates and depreciating dollar are the indispensable ingredients for a lower sustainable burden of the global US debt structure and for allowing the slow rebuilding of an internationally competitive economy. This will probably be accompanied by a weak stock market on the medium term as the growing Federal deficit is consuming a large part of the foreign surplus dollars and the stock market is remaining a very risky and unattractive investment. Notwithstanding strong surge of liquidity in recent months orchestrated by the Federal Reserve, this macroeconomic analysis which incorporates an element of collective behavior is in line with our recent analyses of the bearish market that started in 2000 in terms of a LPPL “anti-bubble”. We project this LPPL anti-bubble to continue at least for another year. On the short term, increased availability of liquidity (M1) and self-fulfilling bullish

  15. Being on the Field When the Game Is Still Under Way. The Financial Press and Stock Markets in Times of Crisis

    PubMed Central

    Casarin, Roberto; Squazzoni, Flaminio

    2013-01-01

    This paper looks at the relationship between negative news and stock markets in times of global crisis, such as the 2008/2009 period. We analysed one year of front page banner headlines of three financial newspapers, the Wall Street Journal, Financial Times, and Il Sole24ore to examine the influence of bad news both on stock market volatility and dynamic correlation. Our results show that the press and markets influenced each other in generating market volatility and in particular, that the Wall Street Journal had a crucial effect both on the volatility and correlation between the US and foreign markets. We also found significant differences between newspapers in their interpretation of the crisis, with the Financial Times being significantly pessimistic even in phases of low market volatility. Our results confirm the reflexive nature of stock markets. When the situation is uncertain and unpredictable, market behaviour may even reflect qualitative, big picture, and subjective information such as streamers in a newspaper, whose economic and informative value is questionable. PMID:23861791

  16. Being on the field when the game is still under way. The financial press and stock markets in times of crisis.

    PubMed

    Casarin, Roberto; Squazzoni, Flaminio

    2013-01-01

    This paper looks at the relationship between negative news and stock markets in times of global crisis, such as the 2008/2009 period. We analysed one year of front page banner headlines of three financial newspapers, the Wall Street Journal, Financial Times, and Il Sole24ore to examine the influence of bad news both on stock market volatility and dynamic correlation. Our results show that the press and markets influenced each other in generating market volatility and in particular, that the Wall Street Journal had a crucial effect both on the volatility and correlation between the US and foreign markets. We also found significant differences between newspapers in their interpretation of the crisis, with the Financial Times being significantly pessimistic even in phases of low market volatility. Our results confirm the reflexive nature of stock markets. When the situation is uncertain and unpredictable, market behaviour may even reflect qualitative, big picture, and subjective information such as streamers in a newspaper, whose economic and informative value is questionable.

  17. Being on the field when the game is still under way. The financial press and stock markets in times of crisis.

    PubMed

    Casarin, Roberto; Squazzoni, Flaminio

    2013-01-01

    This paper looks at the relationship between negative news and stock markets in times of global crisis, such as the 2008/2009 period. We analysed one year of front page banner headlines of three financial newspapers, the Wall Street Journal, Financial Times, and Il Sole24ore to examine the influence of bad news both on stock market volatility and dynamic correlation. Our results show that the press and markets influenced each other in generating market volatility and in particular, that the Wall Street Journal had a crucial effect both on the volatility and correlation between the US and foreign markets. We also found significant differences between newspapers in their interpretation of the crisis, with the Financial Times being significantly pessimistic even in phases of low market volatility. Our results confirm the reflexive nature of stock markets. When the situation is uncertain and unpredictable, market behaviour may even reflect qualitative, big picture, and subjective information such as streamers in a newspaper, whose economic and informative value is questionable. PMID:23861791

  18. A Master Equation Approach to Modeling Short-term Behaviors of the Stock Market

    NASA Astrophysics Data System (ADS)

    Zhao, Conan; Yang, Xiaoxiang; Mazilu, Irina

    2015-03-01

    Short term fluctuations in stock prices are highly random, due to the multitude of external factors acting on the price determination process. While long-term economic factors such as inflation and revenue growth rate affect short-term price fluctuation, it is difficult to obtain the complete set of information and uncertainties associated with a given period of time. Instead, we propose a simpler short-term model based on only prior price averages and extrema. In this paper, we take a master equation under the random walk hypothesis and fit parameters based on AAPL stock price data over the past ten years. We report results for small system sizes and for the short term average price. These results may lead to a general closed-form solution to this particular master equation.

  19. Impact of information cost and switching of trading strategies in an artificial stock market

    NASA Astrophysics Data System (ADS)

    Liu, Yi-Fang; Zhang, Wei; Xu, Chao; Vitting Andersen, Jørgen; Xu, Hai-Chuan

    2014-08-01

    This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.

  20. 75 FR 64384 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Instituting Proceedings To...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-19

    ..., 2010), 75 FR 41258. \\4\\ See Letter from Joe Ratterman, Chairman and Chief Executive Officer, BATS... Exchange Act Release No. 62740 (August 18, 2010), 75 FR 52049 (August 24, 2010). II. Description of the..., particularly in times of market stress, and exacerbate market volatility.\\8\\ \\7\\ See BATS Letter at 2;...

  1. System Latency in Linked Spot and Futures Markets

    NASA Astrophysics Data System (ADS)

    Wagener, Martin; Riordan, Ryan

    We examine the lead-lag effect between DAX index and DAX index futures under asymmetric latency in the exchange infrastructure. Using 1-min high frequency observations in 2006-2007, it is found that the market integration between stock index and stock index futures has significantly grown compared to prior research. While the degree of price discovery in the futures market decreased both markets react mostly contemporaneously towards new information. An event story of latency reduction on Xetra reveals that exchange latency is one important factor explaining this development. We find evidence that smaller asymmetric round-trip-times between Xetra and Eurex lead to a higher degree of market integration.

  2. 76 FR 6168 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; NASDAQ OMX PHLX LLC; NASDAQ OMX BX...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-03

    ..., 2009), 74 FR 22191 (May 12, 2009)(SR-NASDAQ-2009-039). Prior to the closing of the Stock Repurchase and... (approximately $497 million in aggregate) from Borse Dubai Limited (``Borse Dubai'') (the ``Stock Repurchase... NASDAQ OMX common stock from Borse Dubai (``Nomura Purchase''). The Stock Repurchase and Nomura...

  3. Empirical shape function of limit-order books in the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gu, Gao-Feng; Chen, Wei; Zhou, Wei-Xing

    2008-09-01

    We have analyzed the statistical probabilities of limit-order book (LOB) shape through building the book using the ultra-high-frequency data from 23 liquid stocks traded on the Shenzhen Stock Exchange in 2003. We find that the averaged LOB shape has a maximum away from the same best price for both buy and sell sides of the LOB. The LOB shape function has nice exponential form in the right tail. The buy side of the LOB is found to be abnormally thicker for the price levels close to the same best although there are much more sell orders on the book. We also find that the LOB shape functions for both buy and sell sides have periodic peaks with a period of five. The 1-min averaged volumes at fixed tick level follow log-normal distributions except for the left tails which display power-law behaviors, exhibit abnormal intraday patterns with increasing trend, and possess long memory that cannot be explained by the intraday patterns. Academic implications of our empirical results are also briefly discussed.

  4. Preferred numbers and the distributions of trade sizes and trading volumes in the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Mu, G.-H.; Chen, W.; Kertész, J.; Zhou, W.-X.

    2009-03-01

    The distributions of trade sizes and trading volumes are investigated based on the limit order book data of 22 liquid Chinese stocks listed on the Shenzhen Stock Exchange in the whole year 2003. We observe that the size distribution of trades for individualstocks exhibits jumps, which is caused by the number preference of traders when placing orders. We analyze the applicability of the “q-Gamma” function for fitting the distribution by the Cramér-von Mises criterion. The empirical PDFs of tradingvolumes at different timescales Δt ranging from 1 min to 240 min can be well modeled. The applicability of the q-Gamma functions for multiple trades is restricted to the transaction numbers Δn≤ 8. We find that all the PDFs have power-law tails for large volumes. Using careful estimation of the average tail exponents α of the distributions of trade sizes and trading volumes, we get α> 2, well outside the Lévy regime.

  5. Mechanistic approach to generalized technical analysis of share prices and stock market indices

    NASA Astrophysics Data System (ADS)

    Ausloos, M.; Ivanova, K.

    2002-05-01

    Classical technical analysis methods of stock evolution are recalled, i.e. the notion of moving averages and momentum indicators. The moving averages lead to define death and gold crosses, resistance and support lines. Momentum indicators lead the price trend, thus give signals before the price trend turns over. The classical technical analysis investment strategy is thereby sketched. Next, we present a generalization of these tricks drawing on physical principles, i.e. taking into account not only the price of a stock but also the volume of transactions. The latter becomes a time dependent generalized mass. The notion of pressure, acceleration and force are deduced. A generalized (kinetic) energy is easily defined. It is understood that the momentum indicators take into account the sign of the fluctuations, while the energy is geared toward the absolute value of the fluctuations. They have different patterns which are checked by searching for the crossing points of their respective moving averages. The case of IBM evolution over 1990-2000 is used for illustrations.

  6. 17 CFR 240.15g-3 - Broker or dealer disclosure of quotations and other information relating to the penny stock market.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... CFR 240.10b-10 of this chapter. (2) A broker or dealer, at the time of making the disclosure pursuant... such disclosure for the period specified in 17 CFR 240.17a-4(b). (c) Definitions. For purposes of this... quotations and other information relating to the penny stock market. 240.15g-3 Section 240.15g-3...

  7. 17 CFR 240.15g-3 - Broker or dealer disclosure of quotations and other information relating to the penny stock market.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... CFR 240.10b-10 of this chapter. (2) A broker or dealer, at the time of making the disclosure pursuant... such disclosure for the period specified in 17 CFR 240.17a-4(b). (c) Definitions. For purposes of this... quotations and other information relating to the penny stock market. 240.15g-3 Section 240.15g-3...

  8. Effect of trading momentum and price resistance on stock market dynamics: a Glauber Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Castiglione, F.; Pandey, R. B.; Stauffer, D.

    2001-01-01

    A Monte Carlo computer simulation model is presented to study the evolution of stock price and the distribution of price fluctuation. The resistance is described by an elastic energy Ee= e· x2 resulting from the price deviation x from an initial value and the momentum trading by the potential energy Ep=- b· y in a price gradient y field. The distribution of price fluctuation ( P( y)) is symmetric and shows a long time tail compatible over some range with a power-law, P( y)∼ y- μ with μ≃4 at e=1.0, b=5 . The volatility auto-correlation function ( c( τ)) is positive for several iterations.

  9. A copula approach on the dynamics of statistical dependencies in the US stock market

    NASA Astrophysics Data System (ADS)

    Münnix, Michael C.; Schäfer, Rudi

    2011-11-01

    We analyze the statistical dependence structure of the S&P 500 constituents in the 4-year period from 2007 to 2010 using intraday data from the New York Stock Exchange’s TAQ database. Instead of using a given parametric copula with a predetermined shape, we study the empirical pairwise copula directly. We find that the shape of this copula resembles the Gaussian copula to some degree, but exhibits a stronger tail dependence, for both correlated and anti-correlated extreme events. By comparing the tail dependence dynamically to the market’s average correlation level as a commonly used quantity we disclose the average level of error of the Gaussian copula, which is implied in the calculation of many correlation coefficients.

  10. The Leverage Effect on Wealth Distribution in a Controllable Laboratory Stock Market

    PubMed Central

    Zhu, Chenge; Yang, Guang; An, Kenan; Huang, Jiping

    2014-01-01

    Wealth distribution has always been an important issue in our economic and social life, since it affects the harmony and stabilization of the society. Under the background of widely used financial tools to raise leverage these years, we studied the leverage effect on wealth distribution of a population in a controllable laboratory market in which we have conducted several human experiments, and drawn the conclusion that higher leverage leads to a higher Gini coefficient in the market. A higher Gini coefficient means the wealth distribution among a population becomes more unequal. This is a result of the ascending risk with growing leverage level in the market plus the diversified trading abilities and risk preference of the participants. This work sheds light on the effects of leverage and its related regulations, especially its impact on wealth distribution. It also shows the capability of the method of controllable laboratory markets which could be helpful in several fields of study such as economics, econophysics and sociology. PMID:24968222

  11. How High Can a Dead Cat Bounce?: Metaphor and the Hong Kong Stock Market.

    ERIC Educational Resources Information Center

    Smith, Geoff P.

    1995-01-01

    This paper investigates metaphor in the language of economics, in particular, the way the vicissitudes of the Hong Kong financial markets are reported in the press. It analyzes the content from an English for Specific Purposes (ESP) perspective, probing for the significance in the negotiation of meaning in the subject area. Text samples were…

  12. The leverage effect on wealth distribution in a controllable laboratory stock market.

    PubMed

    Zhu, Chenge; Yang, Guang; An, Kenan; Huang, Jiping

    2014-01-01

    Wealth distribution has always been an important issue in our economic and social life, since it affects the harmony and stabilization of the society. Under the background of widely used financial tools to raise leverage these years, we studied the leverage effect on wealth distribution of a population in a controllable laboratory market in which we have conducted several human experiments, and drawn the conclusion that higher leverage leads to a higher Gini coefficient in the market. A higher Gini coefficient means the wealth distribution among a population becomes more unequal. This is a result of the ascending risk with growing leverage level in the market plus the diversified trading abilities and risk preference of the participants. This work sheds light on the effects of leverage and its related regulations, especially its impact on wealth distribution. It also shows the capability of the method of controllable laboratory markets which could be helpful in several fields of study such as economics, econophysics and sociology. PMID:24968222

  13. 76 FR 6506 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Instituting Proceedings To...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-04

    ... additional audit committee requirements applicable to commodity stockpiling companies. In addition to the existing audit committee requirements in Nasdaq rules, audit committees for commodity stockpiling companies... would be risks such pricing information may be available to some market participants sooner than...

  14. 77 FR 2335 - Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-17

    ... Release No. 61358 (January 14, 2010), 75 FR 3594 (January 21, 2010) (Concept Release on Equity Market... December 31, 2011. See Securities Exchange Act Release Nos. 57579 (March 28, 2008), 73 FR 18587 (April 4... (October 23, 2009), 74 FR 56682 (November 2, 2009)(SR-NASDAQ-2009-091)(notice of filing and...

  15. Multilayer Stock Forecasting Model Using Fuzzy Time Series

    PubMed Central

    Javedani Sadaei, Hossein; Lee, Muhammad Hisyam

    2014-01-01

    After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting systems, is outstanding. In this study, we propose a multilayer model for stock market forecasting including five logical significant layers. Every single layer has its detailed concern to assist forecast development by reconciling certain problems exclusively. To verify the model, a set of huge data containing Taiwan Stock Index (TAIEX), National Association of Securities Dealers Automated Quotations (NASDAQ), Dow Jones Industrial Average (DJI), and S&P 500 have been chosen as experimental datasets. The results indicate that the proposed methodology has the potential to be accepted as a framework for model development in stock market forecasts using FTS. PMID:24605058

  16. Virtual Volatility, an Elementary New Concept with Surprising Stock Market Consequences

    NASA Astrophysics Data System (ADS)

    Prange, Richard; Silva, A. Christian

    2006-03-01

    Textbook investors start by predicting the future price distribution, PDF, of a candidate stock (or portfolio) at horizon T, e.g. a year hence. A (log)normal PDF with center (=drift =expected return) μT and width (=volatility) σT is often assumed on Central Limit Theorem grounds, i.e. by a random walk of daily (log)price increments δs. The standard deviation, stdev, of historical (ex post) δs `s is usually a fair predictor of the coming year's (ex ante) stdev(δs) = σdaily, but the historical mean E(δs) at best roughly limits the true, to be predicted, drift by μtrueT˜ μhistT ± σhistT. Textbooks take a PDF with σ ˜ σdaily and μ as somehow known, as if accurate predictions of μ were possible. It is elementary and presumably new to argue that an average of PDF's over a range of μ values should be taken, e.g. an average over forecasts by different analysts. We estimate that this leads to a PDF with a `virtual' volatility σ ˜ 1.3σdaily. It is indeed clear that uncertainty in the value of the expected gain parameter increases the risk of investment in that security by most measures, e. g. Sharpe's ratio μT/σT will be 30% smaller because of this effect. It is significant and surprising that there are investments which benefit from this 30% virtual increase in the volatility

  17. Implied adjusted volatility functions: Empirical evidence from Australian index option market

    NASA Astrophysics Data System (ADS)

    Harun, Hanani Farhah; Hafizah, Mimi

    2015-02-01

    This study aims to investigate the implied adjusted volatility functions using the different Leland option pricing models and to assess whether the use of the specified implied adjusted volatility function can lead to an improvement in option valuation accuracy. The implied adjusted volatility is investigated in the context of Standard and Poor/Australian Stock Exchange (S&P/ASX) 200 index options over the course of 2001-2010, which covers the global financial crisis in the mid-2007 until the end of 2008. Both in- and out-of-sample resulted in approximately similar pricing error along the different Leland models. Results indicate that symmetric and asymmetric models of both moneyness ratio and logarithmic transformation of moneyness provide the overall best result in both during and post-crisis periods. We find that in the different period of interval (pre-, during and post-crisis) is subject to a different implied adjusted volatility function which best explains the index options. Hence, it is tremendously important to identify the intervals beforehand in investigating the implied adjusted volatility function.

  18. Effects of financial crisis on the industry sector of Chinese stock market — from a perspective of complex network

    NASA Astrophysics Data System (ADS)

    Yang, Chunxia; Chen, Yanhua; Hao, Weiwei; Shen, Ying; Tang, Minxuan; Niu, Lei

    2014-05-01

    In this paper, we use mutual information to measure the statistical interdependence between 23 industry sectors of Shanghai stock market and construct corresponding correlation network to analyze the shock of 2008 financial crisis on industry sectors. The obtained meaningful facts are as follows. First, such crisis has only a limited impact on leading industries such as Manufacturing, Commercial trade and Machinery & Equipment, which still play an important role in Chinese economy. Second, the crisis badly attacks China's export industries like Electronics, Wood & Furniture and Textile & Clothing. The damage further hurts other industries, and then export industries' influence becomes larger. Third, the crisis adversely impacts the import industries like Petrochemical, Metal & Nonmetal and Pharmaceutical Biotechnology. While due to the stimulation of macroeconomic policies, the influence of crisis on import industries is limited. Similarly, due to relatively strict capital control and the macroeconomic policies stimulating the domestic demand, those industries like Construction, Real Estate and Financial Services are slightly wounded. All these findings suggest that Chinese government should transform from the external demand to the domestic consumption to sustain economic growth.

  19. State and group dynamics of world stock market by principal component analysis

    NASA Astrophysics Data System (ADS)

    Nobi, Ashadun; Lee, Jae Woo

    2016-05-01

    We study the dynamic interactions and structural changes by a principal component analysis (PCA) to cross-correlation coefficients of global financial indices in the years 1998-2012. The variances explained by the first PC increase with time and show a drastic change during the crisis. A sharp change in PC coefficient implies a transition of market state, a situation which occurs frequently in the American and Asian indices. However, the European indices remain stable over time. Using the first two PC coefficients, we identify indices that are similar and more strongly correlated than the others. We observe that the European indices form a robust group over the observation period. The dynamics of the individual indices within the group increase in similarity with time, and the dynamics of indices are more similar during the crises. Furthermore, the group formation of indices changes position in two-dimensional spaces due to crises. Finally, after a financial crisis, the difference of PCs between the European and American indices narrows.

  20. A unified econophysics explanation for the power-law exponents of stock market activity

    NASA Astrophysics Data System (ADS)

    Gabaix, Xavier; Gopikrishnan, Parameswaran; Plerou, Vasiliki; Stanley, Eugene

    2007-08-01

    We survey a theory (first sketched in Nature in 2003, then fleshed out in the Quarterly Journal of Economics in 2006) of the economic underpinnings of the fat-tailed distributions of a number of financial variables, such as returns and trading volume. Our theory posits that they have a common origin in the strategic trading behavior of very large financial institutions in a relatively illiquid market. We show how the fat-tailed distribution of fund sizes can indeed generate extreme returns and volumes, even in the absence of fundamental news. Moreover, we are able to replicate the individually different empirical values of the power-law exponents for each distribution: 3 for returns, 3/2 for volumes, 1 for the assets under management of large investors. Large investors moderate their trades to reduce their price impact; coupled with a concave price impact function, this leads to volumes being more fat-tailed than returns but less fat-tailed than fund sizes. The trades of large institutions also offer a unified explanation for apparently disconnected empirical regularities that are otherwise a challenge for economic theory.

  1. 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.

  2. Efficiency of financial markets and algorithmic complexity

    NASA Astrophysics Data System (ADS)

    Giglio, R.; da Silva, S.; Gleria, Iram; Ranciaro, A.; Matsushita, R.; Figueiredo, A.

    2010-09-01

    In this work we are interested in the concept of market efficiency and its relationship with the algorithmic complexity theory. We employ a methodology based on the Lempel-Ziv index to analyze the relative efficiency of high-frequency data coming from the Brazilian stock market.

  3. Trading Network Predicts Stock Price

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  4. Trading network predicts stock price.

    PubMed

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

    2014-01-16

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  5. 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.

  6. Index Fund Optimization Using a Genetic Algorithm and a Heuristic Local Search

    NASA Astrophysics Data System (ADS)

    Orito, Yukiko; Inoguchi, Manabu; Yamamoto, Hisashi

    It is well known that index funds are popular passively managed portfolios and have been used very extensively for the hedge trading. Index funds consist of a certain number of stocks of listed companies on a stock market such that the fund's return rates follow a similar path to the changing rates of the market indices. However it is hard to make a perfect index fund consisting of all companies included in the given market index. Thus, the index fund optimization can be viewed as a combinatorial optimization for portfolio managements. In this paper, we propose an optimization method that consists of a genetic algorithm and a heuristic local search algorithm to make strong linear association between the fund's return rates and the changing rates of market index. We apply the method to the Tokyo Stock Exchange and make index funds whose return rates follow a similar path to the changing rates of Tokyo Stock Price Index (TOPIX). The results show that our proposal method makes the index funds with strong linear association to the market index by small computing time.

  7. Multifractal analysis of stock exchange crashes

    NASA Astrophysics Data System (ADS)

    Siokis, Fotios M.

    2013-03-01

    We analyze the complexity of rare events of the DJIA Index. We reveal that the returns of the time series exhibit strong multifractal properties meaning that temporal correlations play a substantial role. The effect of major stock market crashes can be best illustrated by the comparison of the multifractal spectra of the time series before and after the crash. Aftershock periods compared to foreshock periods exhibit richer and more complex dynamics. Compared to an average crash, calculated by taking into account the larger 5 crashes of the DJIA Index, the 1929 event exhibits significantly more increase in multifractality than the 1987 crisis.

  8. 76 FR 62484 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-07

    ... (March 8, 2011), 76 FR 14111 (March 15, 2011). At this time, NASDAQ proposes to permit wider bid/ask... Effectiveness of Proposed Rule Change To Modify NASDAQ Options Market Rules Chapter VII, Section 6, Market Maker... NASDAQ Options Market (``NOM'') to amend Chapter VII, Section 6, Market Maker Quotations, to permit...

  9. 77 FR 38875 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-29

    ... a form of STGY in which the entering firm instructs the System to bypass any market centers included... crossing market center. SKIP is a form of SCAN in which the entering firm instructs the System to...

  10. 75 FR 38857 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-06

    ... installation fee of $925 if the customer chooses to use an on- site router. 2. Statutory Basis NASDAQ believes... mechanism of a free and open market and a national market system, and, in general, to protect investors...

  11. 77 FR 47455 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-08

    ... of component securities from the following twenty-one (21) emerging market countries: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Morocco... securities from the following twenty-two (22) developed market countries: Australia, Austria,...

  12. 75 FR 9982 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-04

    ... (March 31, 2009), 74 FR 15552 (April 6, 2009)(SR-NASDAQ-2009-018). \\8\\ Former Rule 4420(d)(1) required... requirements of the New York Stock Exchange (``NYSE'').\\9\\ \\9\\ See SR-NYSE-2009-115 (December 2, 2009), 74 FR... Effectiveness of Proposed Rule Change To Adopt a Round Lot Holder Initial Listing Requirement for Listing...

  13. 77 FR 71464 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-30

    ... the New York Stock Exchange (``NYSE'')\\9\\ and is also similar to a rule of NYSE MKT.\\10\\ Nasdaq now... change is below. Proposed new language is in italics; proposed deletions are in brackets.\\3\\ \\3\\ Changes... securities that raise significant new regulatory issues, which would require a separate rule filing...

  14. 77 FR 6610 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-08

    ... clearing of trades executed on behalf of Canadian broker- dealers on the Boston Stock Exchange); Letter... which it establishes a relationship for that purpose. In such a relationship, the US broker-dealer... Act Release No. 34-36918 (March 4, 1996), 61 FR 9739 (March 11, 1996) (SR-NASD-95-49)...

  15. 77 FR 3021 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-20

    .... 51983 (July 7, 2005) 70 FR 40614 (July 13, 2005). A number of companies have indicated a preference to... Amendments to the Penny Stock Rules, Securities Exchange Act Release No. 49037 (January 8, 2004), 69 FR 2531..., 2007), 72 FR 20410 (April 24, 2007). \\12\\ The net tangible asset or revenue requirements would...

  16. 77 FR 24549 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Amendment No. 1...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-24

    ... respect to penny stocks. See, e.g., Securities Exchange Act Release No. 49037 (January 16, 2004), 69 FR...\\ See Securities Exchange Act Release No. 66159 (January 13, 2012), 77 FR 3021 (January 20, 2012... Act Release No. 66499 (March 1, 2012), 77 FR 13680 (March 7, 2012). \\6\\ In Amendment No. 1,...

  17. 77 FR 73104 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving Proposed Rule Change...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-07

    ..., stock price, the number of publicly traded shares, and corporate governance standards to ensure... corporate governance listing standards, Nasdaq Rule 5101 also gives the Exchange discretion to deny listing..., 2012), 77 FR 64369. II. Description of the Proposal Before an issuer lists its securities on...

  18. 78 FR 15392 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-11

    ... in securities, and to remove impediments to and perfect the mechanism of a free and open market and a... perfect the mechanism of a free and open market and a national market system because it will allow member... competition for retail orders. B. Self-Regulatory Organization's Statement on Burden on Competition...

  19. 75 FR 6246 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-02-08

    ... transparency and fosters competition among orders and markets. Member firms may use the NASDAQ Ouch BBO Feed to... and perfect the mechanism of a free and open market and a national market system, and, in general, to... Statement on Burden on Competition Nasdaq does not believe that the proposed rule change will result in...

  20. 77 FR 65596 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-29

    ... means for clients to receive third party market data and NASDAQ TotalView ITCH market data. NASDAQ proposes to offer wireless connectivity for co-located clients in NASDAQ's Carteret data center to receive Direct Edge, BATS, NYSE, and NYSE ARCA multi-cast market data feeds. It also proposes to offer...

  1. 76 FR 44076 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-22

    ... (November 3, 2010), 75 FR 69792 (November 15, 2010). In order to comply with the Market Access Rule, NES and... NASDAQ Options Market Rules Chapter VI July 18, 2011. Pursuant to Section 19(b)(1) of the Securities... 4758 and NASDAQ Options Market Rules Chapter VI, Section 10 and 11. The text of the proposed...

  2. 75 FR 69489 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-12

    ... Release No. 61358 (January 14, 2010), 75 FR 3594 (January 21, 2010) (Concept Release on Equity Market Structure, ``Concept Release''). See also Mary L. Schapiro, Strengthening Our Equity Market Structure... comment on a wide range of market structure issues, including high frequency trading and un-displayed,...

  3. 78 FR 31616 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-05-24

    ...)(2)(F) and (G). See Securities Exchange Act Release No. 68528 (December 21, 2012), 77 FR 77165... exception. Nothing in this rule shall preclude a Market Maker from designating a more aggressive offset from... Market Maker Peg Order. If a Market Maker designates a more aggressive offset from the National Best...

  4. 78 FR 41489 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-10

    ... Effectiveness to Conform Rule 5705 Governing Exchange Traded Funds to the Listing Requirements of Another Market... making these changes to ] conform its rules with those of another market. The text of the proposed rule... of another market, namely NYSE Arca (``Arca''). The proposed changes are all based on, and...

  5. 76 FR 65765 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-24

    ... Effectiveness of Proposed Rule Change Relating to the Establishment of a Direct Market Data Product, NASDAQ... proposes to establish a direct market data product, NASDAQ Options Trade Outline (``NOTO''). The text of... data product. NOTO is a market data product offered by the Exchange that is designed to...

  6. 75 FR 9632 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-03

    ... Effectiveness of Proposed Rule Change To Modify Pricing for the NASDAQ Options Market (``NOM'') February 24... NOM and firms that make markets on other options markets. This pricing convention, which is currently..., Nasdaq may expand this pricing model to other options in the future. 2. Statutory Basis Nasdaq...

  7. 78 FR 7831 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-04

    ... Rule 201 of Regulation SHO) to stipulate how Participants in the NASDAQ Market Center System may modify... purpose of the proposed rule change is to stipulate how Participants in the NASDAQ Market Center System... of the order) does not cause the order to lose priority on the NASDAQ Market Center book....

  8. 75 FR 77034 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-10

    ... Effectiveness of Proposed Rule Change To Clarify Market Maker Quote Management Procedures December 6, 2010... change to clarify market maker quote management procedures. The text of the proposed rule change is below... immediately re-adjust and display the Market Maker's quote to the appropriate Designated Percentage set...

  9. 76 FR 12178 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-04

    ... Effectiveness of Proposed Rule Change To Offer Market Data to the Public at No Charge February 25, 2011... NASDAQ Options Market (``NOM'') rules the proprietary data feeds of NOM market information that NASDAQ... trading system includes ``a data feed(s) that can be used to display without attribution to...

  10. Market ecology of active and passive investors

    NASA Astrophysics Data System (ADS)

    Capocci, Andrea; Zhang, Yi-Cheng

    2001-09-01

    We study the role of active and passive investors in an investment market with uncertainties. Active investors concentrate on a single or a few stocks with a given probability of determining the quality of them. Passive investors spread their investment uniformly, resembling buying the market index. In this toy market stocks are introduced as good and bad. If a stock receives sufficient investment it will survive, otherwise die. Active players exert a selective pressure since they can determine to an extent the investment quality. We show that the active players provide the driving force, whereas the passive ones act as free riders. While their gains do not differ too much, we show that the active players enjoy an edge. Their presence also provides better gains to the passive players and stocks themselves.

  11. The level crossing and inverse statistic analysis of German stock market index (DAX) and daily oil price time series

    NASA Astrophysics Data System (ADS)

    Shayeganfar, F.; Hölling, M.; Peinke, J.; Reza Rahimi Tabar, M.

    2012-01-01

    The level crossing and inverse statistics analysis of DAX and oil price time series are given. We determine the average frequency of positive-slope crossings, να+, where Tα=1/να+ is the average waiting time for observing the level α again. We estimate the probability P(K,α), which provides us the probability of observing K times of the level α with positive slope, in time scale Tα. For analyzed time series, we found that maximum K is about ≈6. We show that by using the level crossing analysis one can estimate how the DAX and oil time series will develop. We carry out the same analysis for the increments of DAX and oil price log-returns (which is known as inverse statistics), and provide the distribution of waiting times to observe some level for the increments.

  12. 77 FR 77165 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-31

    ..., 2013, thereby retiring AQR.\\7\\ \\5\\ Securities Exchange Act Release No. 67584 (August 2, 2012), 77 FR... Market Maker Peg Order, which was designed to replace the automated quotation refresh functionality... to sunset AQR three months after fully implementing the Market Maker Peg Order.\\6\\ On October...

  13. 75 FR 39315 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Order Granting...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-08

    ... Accelerated Approval to a Proposed Rule Change To Extend the Last Sale Data Feeds Pilot Program July 1, 2010... to extend for three months the pilot that created the NASDAQ Last Sale (``NLS'') market data products. NLS allows data distributors to have access to real-time market data for a capped fee, enabling...

  14. 75 FR 19444 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Order Granting...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-14

    ... Accelerated Approval to a Proposed Rule Change To Extend the Last Sale Data Feeds Pilot Program April 8, 2010... the NASDAQ Last Sale (``NLS'') market data products. NLS allows data distributors to have access to real-time market data for a capped fee, enabling those distributors to provide free access to the...

  15. 75 FR 64375 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-19

    ... Act Release No. 51808 (June 9, 2005), 70 FR 37496 (June 29, 2005). By removing ``unnecessary... and exploit this competition by sending their order flow and transaction reports to multiple markets..., order routers and market data vendors can facilitate single or multiple broker-dealers' production...

  16. 78 FR 76179 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-16

    .... \\5\\ See Securities Exchange Act Release No. 68640 (January 11, 2013), 78 FR 4554 (January 22, 2013... November 5, 2012; and (ii) Letter from Robert B. Lamm, Chair, Securities Law Committee, Society of... to and perfect the mechanism of a free and open market and a national market system, and, in...

  17. 75 FR 49543 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-08-13

    ... (July 6, 2010), 75 FR 38857 (``Notice''). In its proposal, NASDAQ proposed to establish fees for direct... the customer chooses to use an on- site router. After careful review, the Commission finds that the... mechanism of a free and open market and a national market system and, in general, to protect investors...

  18. 77 FR 49034 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-15

    ...\\ 17 CFR 240.19b-4. \\3\\ See Securities Exchange Act Release No. 67246 (June 25, 2012), 77 FR 38875... process directs the order to NASDAQ before attempting to access available liquidity at other markets and... blended fees associated with transacting on multiple markets. As such, simultaneous routing of such...

  19. 77 FR 34453 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-11

    ... Effectiveness of a Proposed Rule Change To Update the NASDAQ Options Market Message Traffic Mitigation Rule June... Market (``NOM'' or ``Exchange'') to update its quote mitigation rule. Specifically, NASDAQ proposes to amend Chapter VI, Section 17, Message Traffic Mitigation, by deleting paragraph (c) and...

  20. 76 FR 6646 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-07

    ... Change To Modify NASDAQ Options Market Rules Chapter VII, Various Sections, Dealing With Market Maker... Terms of Substance of the Proposed Rule Change NASDAQ proposes to amend Chapter VII, Section 3... organization that is registered with the Exchange pursuant to Chapter II of the NOM Rules for purposes...