Stock Market Index Computer Programs.
ERIC Educational Resources Information Center
Rowley, Eric
1986-01-01
Provides two computer programs, written in BASIC, to calculate average stock market price levels. The programs allow students to work directly from the raw price data that appear daily in the financial news. Teaching suggestions are provided. (JDH)
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.
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
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
A Comparison of Forecasting the Index of the Korean Stock Market
NASA Astrophysics Data System (ADS)
Shin, Young-Geun; Park, Sang-Sung; Jang, Dong-Sik
2009-08-01
According to the increase of an impact foreigner investor have on the Korean stock market, it is very importance to analyze the investment pattern of the foreigner investors in order to predict the movement of the Korean stock market. Firstly, in this study we collected various factors which influence the Korean stock market in the previous literatures about the movement of stock market. Secondly, Factors which influence significantly to KOPSI 200 Index among the collected factors are extracted through the stepwise selection used in regression analysis. Finally we predicted the movement of the Korean stock market using Back-Propagation Neural Network (BPN) and Support Vector Machine (SVM). And we have done a comparison analysis of obtained results through these methods. As a result of the experiments, prediction accuracy using SVM showed better result than using BPN.
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.
NASA Astrophysics Data System (ADS)
Stefan, F. M.; Atman, A. P. F.
2015-02-01
Models which consider behavioral aspects of the investors have attracted increasing interest in the Finance and Econophysics literature in the last years. Different behavioral profiles (imitation, anti-imitation, indifference) were proposed for the investors, which take their decision based on their trust network (neighborhood). Results from agent-based models have shown that most of the features observed in actual stock market indices can be replicated in simulations. Here, we present a deeper investigation of an agent based model considering different network morphologies (regular, random, small-world) for the investors' trust network, in an attempt to answer the question raised in the title. We study the model by considering four scenarios for the investors and different initial conditions to analyze their influence in the stock market fluctuations. We have characterized the stationary limit for each scenario tested, focusing on the changes introduced when complex networks were used, and calculated the Hurst exponent in some cases. Simulations showed interesting results suggesting that the fluctuations of the stock market index are strongly affected by the network morphology, a remarkable result which we believe was never reported or predicted before.
The distribution and scaling of fluctuations for Hang Seng index in Hong Kong stock market
NASA Astrophysics Data System (ADS)
Wang, B. H.; Hui, P. M.
2001-04-01
The statistical properties of the Hang Seng index in the Hong Kong stock market are analyzed. The data include minute by minute records of the Hang Seng index from January 3, 1994 to May 28, 1997. The probability distribution functions of index returns for the time scales from 1 minute to 128 minutes are given. The results show that the nature of the stochastic process underlying the time series of the returns of Hang Seng index cannot be described by the normal distribution. It is more reasonable to model it by a truncated Lévy distribution with an exponential fall-off in its tails. The scaling of the maximium value of the probability distribution is studied. Results show that the data are consistent with scaling of a Lévy distribution. It is observed that in the tail of the distribution, the fall-off deviates from that of a Lévy stable process and is approximately exponential, especially after removing daily trading pattern from the data. The daily pattern thus affects strongly the analysis of the asymptotic behavior and scaling of fluctuation distributions.
ERIC Educational Resources Information Center
Distel, Brenda D.
This project is designed to teach students the process of buying stocks and to tracking their investments over the course of a semester. The goals of the course are to teach students about the relationships between conditions in the economy and the stock market; to predict the effect of an economic event on a specific stock or industry; to relate
Increasing market efficiency in the stock markets
NASA Astrophysics Data System (ADS)
Yang, Jae-Suk; Kwak, Wooseop; Kaizoji, Taisei; Kim, In-Mook
2008-01-01
We study the temporal evolutions of three stock markets; Standard and Poor's 500 index, Nikkei 225 Stock Average, and the Korea Composite Stock Price Index. We observe that the probability density function of the log-return has a fat tail but the tail index has been increasing continuously in recent years. We have also found that the variance of the autocorrelation function, the scaling exponent of the standard deviation, and the statistical complexity decrease, but that the entropy density increases as time goes over time. We introduce a modified microscopic spin model and simulate the model to confirm such increasing and decreasing tendencies in statistical quantities. These findings indicate that these three stock markets are becoming more efficient.
ERIC Educational Resources Information Center
Anderson, Christine; Cook, Stan
1990-01-01
Offers a field-tested stock market unit designed to develop mathematical skills involving fractions and decimals, basic understanding of the stock market, and hypothesis testing skills in real world situations. Includes tables displaying questions, tally sheets, and instructions, as well as a list of related activities. (MDH)
Arbitrage and Volatility in Chinese Stock's Markets
NASA Astrophysics Data System (ADS)
Lu, Shu Quan; Ito, Takao; Zhang, Jianbo
From the point of view of no-arbitrage pricing, what matters is how much volatility the stock has, for volatility measures the amount of profit that can be made from shorting stocks and purchasing options. With the short-sales constraints or in the absence of options, however, high volatility is likely to mean arbitrage from stock market. As emerging stock markets for China, investors are increasingly concerned about volatilities of Chinese two stock markets. We estimate volatility's models for Chinese stock markets' indexes using Markov chain Monte Carlo (MCMC) method and GARCH. We find that estimated values of volatility parameters are very high for all data frequencies. It suggests that stock returns are extremely volatile even at long term intervals in Chinese markets. Furthermore, this result could be considered that there seems to be arbitrage opportunities in Chinese stock markets.
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
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…
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.
NASA Astrophysics Data System (ADS)
Porto, Markus; Roman, H. Eduardo
2002-04-01
We consider autoregressive conditional heteroskedasticity (ARCH) processes in which the variance σ2y depends linearly on the absolute value of the random variable y as σ2y=a+b\\|y\\|. While for the standard model, where σ2y=a+by2, the corresponding probability distribution function (PDF) P(y) decays as a power law for \\|y\\|-->∞, in the linear case it decays exponentially as P(y)~exp(-α\\|y\\|), with α=2/b. We extend these results to the more general case σ2y=a+b\\|y\\|q, with 0stock market index. When the history of the ARCH process is taken into account, the resulting PDF becomes a stretched exponential even for q=1, with a stretched exponent β=2/3, in a much better agreement with the empirical data.
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.
NASA Astrophysics Data System (ADS)
Gu, Rongbao; Shao, Yanmin; Wang, Qingnan
2013-01-01
In this paper, we propose an efficiency index and multifractality degree for financial markets, and investigate the dynamics of the relationship between the two indices for the Shanghai stock market employing the technique of rolling window. By using the DCCA cross-correlation coefficient, we find that, for the Shanghai stock market, the increase in the degree of market multifractality can lead to a lower degree of market efficiency before the equity division reforms, whereas it can result in a lower degree of market efficiency in the short-term and a higher degree of market efficiency in the long-term after the equity division reforms. This finding reflects the process of development of the Shanghai stock market and also provides strong evidence which supports Liu’s argument that the increase in the degree of market complexity can improve the market efficiency Liu (2009) [1].
Stocks low, marketers confident
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.
Do Earthquakes Shake Stock Markets?
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
Gain loss asymmetry for emerging stock markets
NASA Astrophysics Data System (ADS)
Karpio, Krzysztof; Za?uskaKotur, Magdalena A.; Or?owski, Arkadiusz
2007-03-01
Stock indexes for some European emerging markets are analyzed using an investment-horizon approach. Austrian ATX index and Dow Jones have been studied and compared with several emerging European markets. The optimal investment horizons are plotted as a function of an absolute return value. Gain-loss asymmetry, originally found for American DJIA index, is observed for all analyzed data. It is shown, that this asymmetry has different character for emerging and for established markets. For established markets, gain curve lies typically above loss curve, whereas in the case of emerging markets the situation is just the opposite. We propose a measure quantifying the gain-loss asymmetry that clearly exhibits a difference between emerging and established markets.
Scaling analysis of stock markets.
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
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.
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.
Greed, fear and stock market dynamics
NASA Astrophysics Data System (ADS)
Westerhoff, Frank H.
2004-11-01
We present a behavioral stock market model in which traders are driven by greed and fear. In general, the agents optimistically believe in rising markets and thus buy stocks. But if stock prices change too abruptly, they panic and sell stocks. Our model mimics some stylized facts of stock market dynamics: (1) stock prices increase over time, (2) stock markets sometimes crash, (3) stock prices show little pair correlation between successive daily changes, and (4) periods of low volatility alternate with periods of high volatility. A strong feature of the model is that stock prices completely evolve according to a deterministic low-dimensional nonlinear law of motion.
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.
Alternation of different fluctuation regimes in the stock market dynamics
NASA Astrophysics Data System (ADS)
Kwapie?, J.; Dro?d?, 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 Lvy-stable component.
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.
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.
NASA Astrophysics Data System (ADS)
Dose, Christian; Porto, Markus; Roman, H. Eduardo
2003-06-01
We employ autoregressive conditional heteroskedasticity processes to model the probability distribution function (PDF) of high-frequency relative variations of the Standard & Poors 500 market index data, obtained at the time horizon of 1 min. The model reproduces quantitatively the shape of the PDF, characterized by a Lévy-type power-law decay around its center, followed by a crossover to a faster decay at the tails. Furthermore, it is able to reproduce accurately the anomalous decay of the central part of the PDF at larger time horizons and, by the introduction of a short-range memory, also the crossover behavior of the corresponding standard deviations and the time scale of the exponentially decaying autocorrelation function of returns displayed by the empirical data.
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.
Is the stock market efficient?
Malkiel, B G
1989-03-10
A stock market is said to be efficient if it accurately reflects all relevant information in determining security prices. Critics have asserted that share prices are far too volatile to be explained by changes in objective economic events-the October 1987 crash being a case in point. Although the evidence is not unambiguous, reports of the death of the efficient market hypothesis appear premature. PMID:17808264
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.
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)
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.
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.
Empirical study of recent Chinese stock market
NASA Astrophysics Data System (ADS)
Jiang, J.; Li, W.; Cai, X.; Wang, Qiuping A.
2009-05-01
We investigate the statistical properties of the empirical data taken from the Chinese stock market during the time period from January, 2006 to July, 2007. By using the methods of detrended fluctuation analysis (DFA) and calculating correlation coefficients, we acquire the evidence of strong correlations among different stock types, stock index, stock volume turnover, A share (B share) seat number, and GDP per capita. In addition, we study the behavior of “volatility”, which is now defined as the difference between the new account numbers for two consecutive days. It is shown that the empirical power-law of the number of aftershock events exceeding the selected threshold is analogous to the Omori law originally observed in geophysics. Furthermore, we find that the cumulative distributions of stock return, trade volume and trade number are all exponential-like, which does not belong to the universality class of such distributions found by Xavier Gabaix et al. [Xavier Gabaix, Parameswaran Gopikrishnan, Vasiliki Plerou, H. Eugene Stanley, Nature, 423 (2003)] for major western markets. Through the comparison, we draw a conclusion that regardless of developed stock markets or emerging ones, “cubic law of returns” is valid only in the long-term absolute return, and in the short-term one, the distributions are exponential-like. Specifically, the distributions of both trade volume and trade number display distinct decaying behaviors in two separate regimes. Lastly, the scaling behavior of the relation is analyzed between dispersion and the mean monthly trade value for each administrative area in China.
Comparable Stocks, Boundedly Rational Stock Markets and IPO Entry Rates
Chok, Jay; Qian, Jifeng
2013-01-01
In this study, we examine how initial public offerings (IPO) entry rates are affected when stock markets are boundedly rational and IPO firms infer information from their counterparts in the market. We hypothesize a curvilinear relationship between the number of comparable stocks and initial public offerings (IPO) entry rates into the NASDAQ Stock Exchange. Furthermore, we argue that trading volume and changes in stock returns partially mediates the relationship between the number of comparable stocks and IPO entry rates. The statistical evidence provides strong support for the hypotheses. PMID:23690924
Comparable stocks, boundedly rational stock markets and IPO entry rates.
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
Stock Market Expectations of Dutch Households
Hurd, Michael; van Rooij, Maarten; Winter, Joachim
2013-01-01
Despite its importance for the analysis of life-cycle behavior and, in particular, retirement planning, stock ownership by private households is poorly understood. Among other approaches to investigate this puzzle, recent research has started to elicit private households’ expectations of stock market returns. This paper reports findings from a study that collected data over a two-year period both on households’ stock market expectations (subjective probabilities of gains or losses) and on whether they own stocks. We document substantial heterogeneity in financial market expectations. Expectations are correlated with stock ownership. Over the two years of our data, stock market prices increased, and expectations of future stock market price changes also increased, lending support to the view that expectations are influenced by recent stock gains or losses. PMID:23997423
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.
Looking Forward to the Stock Market.
ERIC Educational Resources Information Center
Dickneider, William
1992-01-01
Discusses the advantages of using the stock market to add new dimensions to social studies classes. Suggests that changes in society will make knowledge of financial markets essential for students. Includes two lesson plans with handouts that use the Disney company and changes in the operation of the stock market to capture student interest. (DK)
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.
Scaling and predictability in stock markets: a comparative study.
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
Scaling and Predictability in Stock Markets: A Comparative Study
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
Students Invest in the Stock Market
ERIC Educational Resources Information Center
Parker, George O.
1977-01-01
How one teacher motivated students to learn about the stock market by allowing them to actually invest money. Class discussion covered inexpensive ways to buy stock, choosing securities, and buying and selling stock. Suggestions are offered for adapting this project for use at the secondary level. (TA)
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…
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
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.
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.
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.
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.
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.
Inverse statistics in stock markets: Universality and idiosyncracy
NASA Astrophysics Data System (ADS)
Zhou, Wei-Xing; Yuan, Wei-Kang
2005-08-01
Investigations of inverse statistics (a concept borrowed from turbulence) in stock markets, exemplified with filtered Dow Jones Industrial Average, S&P 500, and NASDAQ, have uncovered a novel stylized fact that the distribution of exit times ??, defined as the waiting time needed to obtain a certain increase ? in the price, follows a power law p(??)???-? with ??1.5 for large ?? and the optimal investment horizon ??* scales as ?? when ? is not too small (Eur. Phys. J. B 27 (2002) 583-586; Physica A 324 (2003) 338-343; Int. J. Mod. Phys. B 17 (2003) 4003-4012). We have performed extensive analyses based on unfiltered daily indices and stock prices as well as high-frequency (5-min) records in numerous stock markets all over the world. Our analysis confirms that the power-law distribution of exit times with an exponent of about ?=1.5 is universal for all the data sets analyzed. In addition, all data sets show that the power-law scaling in the optimal investment horizon holds, but with idiosyncratic exponents. Specifically, ??1.5 for the daily data in most of the developed stock markets and the 5-min high-frequency data, while the ? values for the daily indexes and stock prices in emerging markets are significantly less than 1.5. We show that there is little chance that the discrepancy in ? is due to the difference in sample sizes of the two kinds of 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
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…
The volatility of stock market prices.
Shiller, R J
1987-01-01
If the volatility of stock market prices is to be understood in terms of the efficient markets hypothesis, then there should be evidence that true investment value changes through time sufficiently to justify the price changes. Three indicators of change in true investment value of the aggregate stock market in the United States from 1871 to 1986 are considered: changes in dividends, in real interest rates, and in a direct measure of intertemporal marginal rates of substitution. Although there are some ambiguities in interpreting the evidence, dividend changes appear to contribute very little toward justifying the observed historical volatility of stock prices. The other indicators contribute some, but still most of the volatility of stock market prices appears unexplained. PMID:17769311
Stock or stroke? Stock market movement and stroke incidence in Taiwan.
Chen, Chun-Chih; Chen, Chin-Shyan; Liu, Tsai-Ching; Lin, Ying-Tzu
2012-12-01
This paper investigates the impact of stock market movement on incidences of stroke utilizing population-based aggregate data in Taiwan. Using the daily data from the Taiwan Stock Exchange Capitalization Weighted Stock Index and from the National Health Insurance Research Database during 2001/1/1-2007/12/31, which consist of 2556 observations, we examine the effects of stock market on stroke incidence - the level effect and the daily change effects. In general, we find that both a low stock index level and a daily fall in the stock index are associated with greater incidences of stroke. We further partition the data on sex and age. The level effect is found to be significant for either gender, in the 45-64 and 65 ≥ age groups. In addition, two daily change effects are found to be significant for males and the elderly. Although stockholdings can increase wealth, they can also increase stroke incidence, thereby representing a cost to health. PMID:22951009
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.
Stock Markets Indices in Artificial Insymmetrization Patterns
NASA Astrophysics Data System (ADS)
Makowiec, Danuta
2002-04-01
The daily data of indices of Warsaw Stock Exchange --- WIG, and New York Stock Exchange --- NASDAQ, NYSE and S&P 500 for the last two years are being studied. Properties of fluctuations of daily returns found from scaling analysis of tails are confronted with patterns obtained by the artificial insymmetrization method to specify difference between the world-wide American market and local and rather marginal Polish market.
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.
Relationships among Energy Price Shocks, Stock Market, and the Macroeconomy: Evidence from China
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
Relationships among energy price shocks, stock market, and the macroeconomy: evidence from China.
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
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.
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…
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.
Quantifying the behavior of stock correlations under market stress.
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
Quantifying the Behavior of Stock Correlations Under Market Stress
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
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…
Modeling stock markets through bosonic operators
NASA Astrophysics Data System (ADS)
Bagarello, Fabio
2008-11-01
We review our results on a quantum-like approach recently developed in the attempt of modeling a simplified stock-market. Under suitable approximations we deduce the time evolution of the portfolio of the various traders of the market, as well as of other observable quantities.
Quantifying Stock Return Distributions in Financial Markets
Botta, Federico; Moat, Helen Susannah; Stanley, H. Eugene; Preis, Tobias
2015-01-01
Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales. PMID:26327593
Quantifying Stock Return Distributions in Financial Markets.
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
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.
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.
How High Frequency Trading Affects a Market Index
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
Zoo Techniques in the Stock Market.
ERIC Educational Resources Information Center
Berzosa, Maria Jose Garcia
1999-01-01
Outlines a stock market activity that has helped English for specific purposes students in business school learn technical vocabulary. The objective is to minimize confusion by using visuals with written and spoken words, and to find effective ways of promoting learning and generating motivation. (Author/VWL)
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.
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.
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.
Extreme value modelling of Ghana stock exchange index.
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
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.
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.
Phases and Frequencies in the Stock Market
NASA Astrophysics Data System (ADS)
Silva, A. Christian; Neto, Camilo; Crepaldi, Antonio; Ferreira, Fernando
2010-03-01
We apply several multi-resolution analysis to filter the stock market time series. We use wavelet based techniques and the Empirical mode decomposition technique. Here, filtering financial series, removes high frequency components and lead to a smooth or a more deterministic time series. When working with wavelets, we use a neural network to select the resolution level to get the maximum prediction. This approach helps to increase the predictive performance of the deterministic and statistical tools. Then we study the frequencies by computing the spectrogram for the average of 328 stocks. We find that similar patterns are detected when using Empirical mode decomposition technique. We also study the correlation in the time-frequency space among all set of stocks. This is done by computing the cross wavelet and EMD transform of the standardized time series. The statistical significance level of all the measures used in the preset paper was carried out by comparing the empirical results with a surrogate and random data, with critical values fixed at 5% significance level. These results may be helpful to investigate how the stocks are clustered and to determine a subset of synchronized stocks in this region.
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).
Federal Register 2010, 2011, 2012, 2013, 2014
2013-07-05
... COMMISSION Order Exempting Market Makers Participating in NASDAQ Stock Market LLC's Market Quality Program... Rule 5950'') to establish the Market Quality Program (``MQP'' or ``Program'').\\1\\ In connection with... MQP (``MQP Market Makers'') to enhance the market quality of an MQP Security. \\1\\ Securities...
26 CFR 1.1296-1 - Mark to market election for marketable stock.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 26 Internal Revenue 11 2012-04-01 2012-04-01 false Mark to market election for marketable stock. 1... Losses § 1.1296-1 Mark to market election for marketable stock. (a) Definitions—(1) Eligible RIC. An... respect to any section 1296 stock, the excess, if any, of— (A) The amount of mark to market gain...
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... Losses § 1.1296-1 Mark to market election for marketable stock. (a) Definitions—(1) Eligible RIC. An... respect to any section 1296 stock, the excess, if any, of— (A) The amount of mark to market gain...
26 CFR 1.1296-1 - Mark to market election for marketable stock.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 26 Internal Revenue 11 2013-04-01 2013-04-01 false Mark to market election for marketable stock. 1... Losses § 1.1296-1 Mark to market election for marketable stock. (a) Definitions—(1) Eligible RIC. An... respect to any section 1296 stock, the excess, if any, of— (A) The amount of mark to market gain...
26 CFR 1.1296-1 - Mark to market election for marketable stock.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 26 Internal Revenue 11 2014-04-01 2014-04-01 false Mark to market election for marketable stock. 1... Losses § 1.1296-1 Mark to market election for marketable stock. (a) Definitions—(1) Eligible RIC. An... respect to any section 1296 stock, the excess, if any, of— (A) The amount of mark to market gain...
STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS.
Hudomiet, Péter; Kézdi, Gábor; Willis, Robert J
2011-01-01
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
STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS*
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
Simplified stock markets described by number operators
NASA Astrophysics Data System (ADS)
Bagarello, F.
2009-06-01
In this paper we continue our systematic analysis of the operatorial approach previously proposed in an economical context and we discuss a mixed toy model of a simplified stock market, i.e. a model in which the price of the shares is given as an input. We deduce the time evolution of the portfolio of the various traders of the market, as well as of other observable quantities. As in a previous paper, we solve the equations of motion by means of a fixed point like approximation.
Fear and its implications for stock markets
NASA Astrophysics Data System (ADS)
Simonsen, I.; Ahlgren, P. T. H.; Jensen, M. H.; Donangelo, R.; Sneppen, K.
2007-05-01
The value of stocks, indices and other assets, are examples of stochastic processes with unpredictable dynamics. In this paper, we discuss asymmetries in short term price movements that can not be associated with a long term positive trend. These empirical asymmetries predict that stock index drops are more common on a relatively short time scale than the corresponding raises. We present several empirical examples of such asymmetries. Furthermore, a simple model featuring occasional short periods of synchronized dropping prices for all stocks constituting the index is introduced with the aim of explaining these facts. The collective negative price movements are imagined triggered by external factors in our society, as well as internal to the economy, that create fear of the future among investors. This is parameterized by a “fear factor” defining the frequency of synchronized events. It is demonstrated that such a simple fear factor model can reproduce several empirical facts concerning index asymmetries. It is also pointed out that in its simplest form, the model has certain shortcomings.
Comparison of Gain--Loss Asymmetry Behavior for Stocks and Indexes
NASA Astrophysics Data System (ADS)
Zaluska-Kotur, M.; Karpio, K.; Orlowski, A.
2006-11-01
Investment horizon approach has been used to analyze indexes of Polish stock market. Optimal time horizon for each return value is evaluated by fitting appropriate function form of the distribution. Strong asymmetry of gain-loss curves is observed for WIG index, whereas gain and loss curves look similar for WIG20 and for most stocks of individual companies. The gain-loss asymmetry for these data, measured by a coefficient, that we postulated before [submitted to {ITALIC Physica A}], has opposite sign to this for WIG index.
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.
26 CFR 1.1296-1 - Mark to market election for marketable stock.
Code of Federal Regulations, 2010 CFR
2010-04-01
... with respect to the X stock, effective for taxable year 2007. The fair market value of the X stock was...) Recognition of gain. If the fair market value of section 1296 stock on the last day of the United States... for its taxable year the excess of the fair market value of such stock over its adjusted basis...
Performance of technical trading rules: evidence from Southeast Asian stock markets.
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
26 CFR 1.1296-2 - Definition of marketable stock.
Code of Federal Regulations, 2014 CFR
2014-04-01
... separate exchange. (d) Stock in certain PFICs—(1) General rule. Except as provided in paragraph (d)(2) of... 26 Internal Revenue 11 2014-04-01 2014-04-01 false Definition of marketable stock. 1.1296-2....1296-2 Definition of marketable stock. (a) General rule. For purposes of section 1296, the...
26 CFR 1.1296-2 - Definition of marketable stock.
Code of Federal Regulations, 2012 CFR
2012-04-01
... separate exchange. (d) Stock in certain PFICs—(1) General rule. Except as provided in paragraph (d)(2) of... 26 Internal Revenue 11 2012-04-01 2012-04-01 false Definition of marketable stock. 1.1296-2....1296-2 Definition of marketable stock. (a) General rule. For purposes of section 1296, the...
The Stock Performance of C. Everett Koop Award Winners Compared With the Standard & Poor's 500 Index
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
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.
Risk-Adjusted Returns and Stock Market Games.
ERIC Educational Resources Information Center
Kagan, Gary; And Others
1995-01-01
Maintains that stock market games are designed to provide students with a background for investing in securities, especially stocks. Reviews two games used with secondary students, analyzes statistical data from these experiences, and considers weaknesses in the games. (CFR)
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.
Scale-free avalanche dynamics in the stock market
NASA Astrophysics Data System (ADS)
Bartolozzi, M.; Leinweber, D. B.; Thomas, A. W.
2006-10-01
Self-organized criticality (SOC) has been claimed to play an important role in many natural and social systems. In the present work we empirically investigate the relevance of this theory to stock-market dynamics. Avalanches in stock-market indices are identified using a multi-scale wavelet-filtering analysis designed to remove Gaussian noise from the index. Here, new methods are developed to identify the optimal filtering parameters which maximize the noise removal. The filtered time series is reconstructed and compared with the original time series. A statistical analysis of both high-frequency Nasdaq E-mini Futures and daily Dow Jones data is performed. The results of this new analysis confirm earlier results revealing a robust power-law behaviour in the probability distribution function of the sizes, duration and laminar times between avalanches. This power-law behaviour holds the potential to be established as a stylized fact of stock market indices in general. While the memory process, implied by the power-law distribution of the laminar times, is not consistent with classical models for SOC, we note that a power-law distribution of the laminar times cannot be used to rule out self-organized critical behaviour.
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.
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.
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.
Estimating time-varying conditional correlations between stock and foreign exchange markets
NASA Astrophysics Data System (ADS)
Tastan, Hüseyin
2006-02-01
This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.
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/
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.
Modeling and computing of stock index forecasting based on neural network and Markov chain.
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
Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chain
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
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, ??*, which defines the most likely waiting time for obtaining a given return ?. 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).
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.
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.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-03-31
... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule Change To Establish Strike Price Intervals and Trading Hours for Options on Index-Linked Securities March... Stock Market LLC (``NASDAQ'' or ``Exchange'') filed with the Securities and Exchange...
NASA Astrophysics Data System (ADS)
Ma, Feng; Wei, Yu; Huang, Dengshi
2013-04-01
In this paper, we investigate the cross-correlations between the stock market in China and markets in Japan, South Korea and Hong Kong. We use not only the qualitative analysis of the cross-correlation test, but also the quantitative analysis of the MF-X-DFA. Our findings confirm the existence of cross-correlations between the stock market in China and markets in Japan, South Korea and Hong Kong, which have strongly multifractal features. We find that the cross-correlations display the characteristic of multifractality in the short term. Moreover, the cross-correlations of small fluctuations are persistent and those of large fluctuations are anti-persistent in the short term, while the cross-correlations of all kinds of fluctuations are persistent in the long term. Furthermore, based on the multifractal spectrum, we also find that the multifractality of cross-correlation between stock markets in China and Japan are stronger than those between China and South Korea, as well as between China and Hong Kong.
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)
Statistics of extreme events in Chinese stock markets
NASA Astrophysics Data System (ADS)
Wu, Gan-Hua; Qiu, Lu; Mutua, Stephen; Li, Xin-Li; Yang, Yue; Yang, Hui-Jie; Jiang, Yan
2014-12-01
We investigate the impact of financial factors on daily volume recurrent time intervals in the developing Chinese stock markets. The tails of probability distribution functions (PDFs) of volume recurrent intervals behave as a power-law, and the scaling exponent decreases with the increase of stock lifetime, which are similar to those in the US stock markets, and they are typical representatives of developed markets. The difference is that the power-law exponent values remain almost the same with the changes of market capitalization, mean volume, and mean trading value, respectively. These findings enrich the results for event statistics for financial markets.
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.
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.
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.
Cross-Correlation Asymmetries and Causal Relationships between Stock and Market Risk
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
Cross-correlation asymmetries and causal relationships between stock and market risk.
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
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.
The Stock Market Game: Classroom Use and Strategy.
ERIC Educational Resources Information Center
Wood, William C.; And Others
1992-01-01
Discusses the Stock Market Game in which teams of students buy and sell stocks. Reviews information on the costs and benefits of the game and its uses. Examines game strategies through the economics of capital markets. Concludes that substantial costs in class time may be outweighed by benefits in some classroom situations. (DK)
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.
The US Stock Market Leads the Federal Funds Rate and Treasury Bond Yields
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
The US stock market leads the federal funds rate and treasury bond yields.
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
Exploring Market State and Stock Interactions on the Minute Timescale
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
Exploring Market State and Stock Interactions on the Minute Timescale.
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
How Random is the Walk: Efficiency of Indian Stock and Futures Markets
NASA Astrophysics Data System (ADS)
Basu, Udayan Kumar
Time series of prices of stock and its rates of return has been one of the major areas of study in Econophysics. The price of a stock depends on a number of factors as well as information related thereto, and how quickly and effectively the price of a stock assimilates all such information decides the efficiency of the stock market. Instead of individual stocks, people often study the behaviour of stock indices to get a feel of the market as a whole, and the outcomes of such studies for the Dow Jones Industrial Average (DJIA), the Nasdaq Index and the S & P 500 Index have been listed in a number of articles. In this context, it has also been argued that for a market to be considered sufficiently liquid, correlation between successive price movements and rates of return should be insignificant, because any significant correlation would lead to an arbitrage opportunity that is expected to be rapidly exploited and thus washed out. The residual correlations are those little enough not to be profitable for strategies due to imperfect market conditions. Unless transaction costs or slippages or any other impediment exists, leading to some transactional inefficiency, arbitrages would take place to bring back the markets to a stage of insignifficant correlations [1, 2].
Multifractal detrended cross-correlations between the Chinese exchange market and stock market
NASA Astrophysics Data System (ADS)
Cao, Guangxi; Xu, Longbing; Cao, Jie
2012-10-01
Based on the daily price data of the Chinese Yuan (RMB)/US dollar exchange rate and the Shanghai Stock Composite Index, we conducted an empirical analysis of the cross-correlations between the Chinese exchange market and stock market using the multifractal cross-correlation analysis method. The results demonstrate the overall significance of the cross-correlation based on the analysis of a statistic. Multifractality exists in cross-correlations, and the cross-correlated behavior of small fluctuations is more persistent than that of large fluctuations. Moreover, using the rolling windows method, we find that the cross-correlations between the Chinese exchange market and stock market vary with time and are especially sensitive to the reform of the RMB exchange rate regime. The previous reduction in the flexibility of the RMB exchange rate in July 2008 strengthened the persistence of cross-correlations and decreased the degree of multifractality, whereas the enhancement of the flexibility of the RMB exchange rate in June 2010 weakened the persistence of cross-correlations and increased the multifractality. Finally, several relevant discussions are provided to verify the robustness of our empirical analysis.
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.
Stochastic cellular automata model for stock market dynamics.
Bartolozzi, M; Thomas, A W
2004-04-01
In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, sigma(i) (t)=+1, or sell, sigma(i) (t)=-1, a stock at a certain discrete time step. The remaining cells are inactive, sigma(i) (t)=0. The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P 500 index. PMID:15169074
Stochastic cellular automata model for stock market dynamics
NASA Astrophysics Data System (ADS)
Bartolozzi, M.; Thomas, A. W.
2004-04-01
In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.
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.
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.
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.
Impact of monetary policy changes on the Chinese monetary and stock markets
NASA Astrophysics Data System (ADS)
Tang, Yong; Luo, Yong; Xiong, Jie; Zhao, Fei; Zhang, Yi-Cheng
2013-10-01
The impact of monetary policy changes on the monetary market and stock market in China is investigated in this study. The changes of two major monetary policies, the interest rate and required reserve ratio, are analyzed in a study period covering seven years on the interbank monetary market and Shanghai stock market. We find that the monetary market is related to the macro economy trend and we also find that the monetary change surprises both of lowering and raising bring significant impacts to the two markets and the two markets respond to the changes differently. The results suggest that the impact of fluctuations is much larger for raising policy changes than lowering changes in the monetary market on policy announcing and effective dates. This is consistent with the “sign effect”, i.e. bad news brings a greater impact than good news. By studying the event window of each policy change, we also find that the “sign effect” still exists before and after each change in the monetary market. A relatively larger fluctuation is observed before the event date, which indicates that the monetary market might have a certain ability to predict a potential monetary change, while it is kept secret by the central bank before official announcement. In the stock market, we investigate how the returns and spreads of the Shanghai stock market index respond to the monetary changes. Evidences suggest the stock market is influenced but in a different way than the monetary market. The climbing of returns after the event dates for the lowering policy agrees with the theory that lowering changes can provide a monetary supply to boost the market and drive the stock returns higher but with a delay of 2 to 3 trading days on average. While in the bear market, the lowering policy brings larger volatility to the market on average than the raising ones. These empirical findings are useful for policymakers to understand how monetary policy changes impact the monetary and stock markets especially in an emerging market like China where the economy is booming and the policy changes impact the markets as surprises by the central bank without a pre-decided schedule. This is totally different from previous studies on FED, which follows pre-decided schedules for monetary policy changes.
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.
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.
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…
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
Using the Stock Market for Relevance in Teaching Number Sense
ERIC Educational Resources Information Center
Leonard, Jacqueline; Campbell, Louise L.
2004-01-01
This article describes the lessons introduced to middle school children in the Washington, D.C., area on the stock market. Students kept eight weeks of records and learned about decimals and place value. (Contains 5 figures.)
What the 2008 stock market crash means for retirement security.
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. PMID:20924891
Bullish on Mathematics: Using Stock Market Simulations To Enhance Learning.
ERIC Educational Resources Information Center
Alsup, John K.; Altmyer, Donald J.
2002-01-01
Describes how a stock market simulation can be an excellent tool for motivating students to learn real-world mathematics in a middle school classroom. Details four activities that can accompany the simulation. (Contains 12 references.) (YDS)
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.
Possible causes of long-range dependence in the Brazilian stock market
NASA Astrophysics Data System (ADS)
Cajueiro, Daniel O.; Tabak, Benjamin M.
2005-01-01
While the presence of long-range dependence in the asset returns seems to be a stylized fact, the issue of arguing the possible causes of this phenomena is totally obscure. Trying to shed light in this problem, we investigate the possible sources of the long-range dependence phenomena in the Brazilian Stock Market. For this purpose, we employ a sample which comprises stocks traded in the Brazilian financial market (BOVESPA Index). The Hurst exponent here is considered as our measure of long-range dependence and it is evaluated by six different methods. We have found evidence of statistically significant rank correlation between specific variables of the Brazilian firms which subscribe stocks and the long-range dependence phenomena present in these stocks.
Effects of daylight savings time changes on stock market volatility.
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. PMID:20524568
Nonextensive statistical features of the Polish stock market fluctuations
NASA Astrophysics Data System (ADS)
Rak, R.; Drożdż, S.; Kwapień, J.
2007-01-01
The statistics of return distributions on various time scales constitutes one of the most informative characteristics of the financial dynamics. Here, we present a systematic study of such characteristics for the Polish stock market index WIG20 over the period 04.01.1999 31.10.2005 for the time lags ranging from 1min up to 1 h. This market is commonly classified as emerging. Still on the shortest time scales studied we find that the tails of the return distributions are consistent with the inverse cubic power law, as identified previously for majority of the mature markets. Within the time scales studied, a quick and considerable departure from this law towards a Gaussian can however be traced. Interestingly, all the forms of the distributions observed can be comprised by the single q-Gaussians which provide a satisfactory and at the same time compact representation of the distribution of return fluctuations over all magnitudes of their variation. The corresponding nonextensivity parameter q was found to systematically decrease when increasing the time scales. The temporal correlations quantified here in terms of multifractality provide further arguments in favor of nonextensivity.
Habitat Suitability Index Models: Coastal Stocks of Striped Bass
Bain, Mark B.; Bain, Jane L.
1982-01-01
A review and synthesis of existing information were used to develop estuarine habitat models for coastal stocks of striped bass (Morone saxatilis). Models for five life stages are scaled to produce an index of habitat suitability between 0 (unsuitable habitat) and 1 (optimally suitable habitat) for estuarine areas of the continental United States. Habitat suitability indexes are designed for use with the habitat evaluation procedures developed by the U.S. Fish and Wildlife Service. Guidelines for coastal striped bass model applications and techniques for estimating model variable are described.
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.
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.
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.
Empirical behavior of a world stock index from intra-day to monthly time scales
NASA Astrophysics Data System (ADS)
Breymann, W.; Lüthi, D. R.; Platen, E.
2009-10-01
Most of the papers that study the distributional and fractal properties of financial instruments focus on stock prices or foreign exchange rates. This typically leads to mixed results concerning the distributions of log-returns and some multi-fractal properties of exchange rates, stock prices, and regional indices. This paper uses a well diversified world stock index as the central object of analysis. Such index approximates the growth optimal portfolio, which is demonstrated under the benchmark approach, it is the ideal reference unit for studying basic securities. When denominating this world index in units of a given currency, one measures the movements of the currency against the entire market. This provides a least disturbed observation of the currency dynamics. In this manner, one can expect to disentangle, e.g., the superposition of the two currencies involved in an exchange rate. This benchmark approach to the empirical analysis of financial data allows us to establish remarkable stylized facts. Most important is the observation that the repeatedly documented multi-fractal appearance of financial time series is very weak and much less pronounced than the deviation of the mono-scaling properties from Brownian-motion type scaling. The generalized Hurst exponent H(2) assumes typical values between 0.55 and 0.6. Accordingly, autocorrelations of log-returns decay according to a power law, and the quadratic variation vanishes when going to vanishing observation time step size. Furthermore, one can identify the Student t distribution as the log-return distribution of a well-diversified world stock index for long time horizons when a long enough data series is used for estimation. The study of dependence properties, finally, reveals that jumps at daily horizon originate primarily in the stock market while at 5min horizon they originate in the foreign exchange market. The principal message of the empirical analysis is that there is evidence that a diffusion model without multi-scaling could reasonably well model the dynamics of a broadly diversified world stock index. in here
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 issue.
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.
Using the Stock Market Game in the Social Studies Classroom.
ERIC Educational Resources Information Center
Cox, Allen C.
1997-01-01
Describes an educational game designed to help students (fourth grade through adult) understand how financial markets work within the free enterprise system and how the basic economic principles impact the stock market. Discusses the paper and Internet versions of the game and provides some teaching guidelines. (MJP)
Universal Behavior of Extreme Price Movements in Stock Markets
Fuentes, Miguel A.; Gerig, Austin; Vicente, Javier
2009-01-01
Many studies assume stock prices follow a random process known as geometric Brownian motion. Although approximately correct, this model fails to explain the frequent occurrence of extreme price movements, such as stock market crashes. Using a large collection of data from three different stock markets, we present evidence that a modification to the random model—adding a slow, but significant, fluctuation to the standard deviation of the process—accurately explains the probability of different-sized price changes, including the relative high frequency of extreme movements. Furthermore, we show that this process is similar across stocks so that their price fluctuations can be characterized by a single curve. Because the behavior of price fluctuations is rooted in the characteristics of volatility, we expect our results to bring increased interest to stochastic volatility models, and especially to those that can produce the properties of volatility reported here. PMID:20041178
Universal behavior of extreme price movements in stock markets.
Fuentes, Miguel A; Gerig, Austin; Vicente, Javier
2009-01-01
Many studies assume stock prices follow a random process known as geometric Brownian motion. Although approximately correct, this model fails to explain the frequent occurrence of extreme price movements, such as stock market crashes. Using a large collection of data from three different stock markets, we present evidence that a modification to the random model--adding a slow, but significant, fluctuation to the standard deviation of the process--accurately explains the probability of different-sized price changes, including the relative high frequency of extreme movements. Furthermore, we show that this process is similar across stocks so that their price fluctuations can be characterized by a single curve. Because the behavior of price fluctuations is rooted in the characteristics of volatility, we expect our results to bring increased interest to stochastic volatility models, and especially to those that can produce the properties of volatility reported here. PMID:20041178
Multifractal cross-correlation spectra analysis on Chinese stock markets
NASA Astrophysics Data System (ADS)
Zhao, Xiaojun; Shang, Pengjian; Shi, Wenbin
2014-05-01
In this paper, the long-range cross-correlation of Chinese stock indices is systematically studied. The multifractal detrended cross-correlation analysis (MF-DXA) appears to be one of the most effective methods in detecting long-range cross-correlation of two non-stationary variables. The Legendre spectrum and the large deviations spectrum are extended to the cross-correlation case, so as to present multifractal structure of stock return and volatility series. It is characterized of the multifractality in Chinese stock markets, partly due to clusters of local detrended covariance with large and small magnitudes.
Fractal profit landscape of the stock market.
Grönlund, Andreas; Yi, Il Gu; Kim, Beom Jun
2012-01-01
We investigate the structure of the profit landscape obtained from the most basic, fluctuation based, trading strategy applied for the daily stock price data. The strategy is parameterized by only two variables, p and q Stocks are sold and bought if the log return is bigger than p and less than -q, respectively. Repetition of this simple strategy for a long time gives the profit defined in the underlying two-dimensional parameter space of p and q. It is revealed that the local maxima in the profit landscape are spread in the form of a fractal structure. The fractal structure implies that successful strategies are not localized to any region of the profit landscape and are neither spaced evenly throughout the profit landscape, which makes the optimization notoriously hard and hypersensitive for partial or limited information. The concrete implication of this property is demonstrated by showing that optimization of one stock for future values or other stocks renders worse profit than a strategy that ignores fluctuations, i.e., a long-term buy-and-hold strategy. PMID:22558079
Quantifying the semantics of search behavior before stock market moves
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
Quantifying the semantics of search behavior before stock market moves.
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. PMID:25071193
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
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.
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.
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.
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.
Analysis of the market difference using the stock board
NASA Astrophysics Data System (ADS)
Toriumi, Fujio; Nishiok, Hirokazu; Umeoka, Toshimits; Ishii, Kenichiro
The financial markets are fluctuating consistently. Therefore, it is difficult to analyze the financial market based on the same theory, without depending on the state of the market. So we use the concept ofmarket condition change. To estimate the points when the market change occurred in a real market is effective for market analysis. Thus, in this paper, we propose a method to detect the changes in market conditions. In the proposed method, we focuse on the stock board instead of the price data. From the stock board data, we classify short time series data to clusters by using k-means clustering method. Then, we generate Hidden Markov Model(HMM) from the transition probability of each clusters. By using the likelihood of HMM, we analyze the similarities of each time series data. We performed an experiment to evaluate the effectiveness of the method by discriminant analysis of time series data which created from opening session and continuous session. As a result, two time series data are discriminated with high accuracy. Finally, we compared the discriminate performance of proposed method with another discriminant analysis methods. We used three types of time series data of stock board and price data, before the Lehman's fall financial crisis. From the result, the proposed method shows the best performance in discriminating each financial data.
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, Chens (1996), Yus (2005), Chengs (2006) and Chens (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.
Behaviorly realistic simulations of stock market traders with a soul
NASA Astrophysics Data System (ADS)
Solomon, Sorin
1999-09-01
The price fluctuations of the stocks in the financial markets are the result of the individual operations by many individual investors. However for many decades the financial theory did not use directly this “microscopic representation” of the markets. The main difficulties preventing this approach were solved recently with the advent of modern computer technology: - massive detailed data on the individual market operations became available; - “microscopic simulations” of the stock markets in terms of their individual participating agents allow very realistic treatment of the problem. By taking advantage of the modern computer processing and simulation techniques, we are now able to confront real market data with the results of simulating “microscopic” realistic models of the markets. These models have the potential to include and study the effects on the market of any desired feature in the investors behavior: departures from rationality, herding effects, heterogeneous investor-specific trading strategies. We propose to use the comparison of computer simulations of microscopic models with the actual market data in order to validate and enhance the knowledge on the financial behavior of individuals. Moreover we hope to explain, understand (and may be predict and control) macroscopic market dynamical features (e.g., cycles of booms and crashes, investors wealth distribution, market returns probability distribution etc.) based on realistic models using this knowledge.
Stroke: a Hidden Danger of Margin Trading in Stock Markets.
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. PMID:26014381
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.
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.
Temporal evolution into a more efficient stock market
NASA Astrophysics Data System (ADS)
Yang, Jae-Suk; Kaizoji, Taisei; Kwak, Wooseop
2011-06-01
Using the price change and the log return of 10 stock market indices, we examine the temporal evolution of the time scale. The 10 stock markets had similar properties. Their log-return time series had patterns and long-range correlations until the mid-1990s. In the 2000s, however, the long-range correlations for most markets shortened, and the patterns weakened. These phenomena were due to advances in communication infrastructure such as the Internet and internet-based trading systems, which increased the speed of information dissemination. We examined the temporal evolution of the time scale in the markets by comparing the probability density function of log returns for the 2000s with that in the 1990s and by using the minimum entropy density method.
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.
Cointegration-based financial networks study in Chinese stock market
NASA Astrophysics Data System (ADS)
Tu, Chengyi
2014-05-01
We propose a method based on cointegration instead of correlation to construct financial complex network in Chinese stock market. The network is obtained starting from the matrix of p-value calculated by Engle-Granger cointegration test between all pairs of stocks. Then some tools for filtering information in complex network are implemented to prune the complete graph described by the above matrix, such as setting a level of statistical significance as a threshold and Planar Maximally Filtered Graph. We also calculate Partial Correlation Planar Graph of these stocks to compare the above networks. Last, we analyze these directed, weighted and non-symmetric networks by using standard methods of network analysis, including degree centrality, PageRank, HITS, local clustering coefficient, K-shell and strongly and weakly connected components. The results shed a new light on the underlying mechanisms and driving forces in a financial market and deepen our understanding of financial complex network.
Stylized facts in internal rates of return on stock index and its derivative transactions
NASA Astrophysics Data System (ADS)
Pichl, Lukáš; Kaizoji, Taisei; Yamano, Takuya
2007-08-01
Universal features in stock markets and their derivative markets are studied by means of probability distributions in internal rates of return on buy and sell transaction pairs. Unlike the stylized facts in normalized log returns, the probability distributions for such single asset encounters incorporate the time factor by means of the internal rate of return, defined as the continuous compound interest. Resulting stylized facts are shown in the probability distributions derived from the daily series of TOPIX, S & P 500 and FTSE 100 index close values. The application of the above analysis to minute-tick data of NIKKEI 225 and its futures market, respectively, reveals an interesting difference in the behavior of the two probability distributions, in case a threshold on the minimal duration of the long position is imposed. It is therefore suggested that the probability distributions of the internal rates of return could be used for causality mining between the underlying and derivative stock markets. The highly specific discrete spectrum, which results from noise trader strategies as opposed to the smooth distributions observed for fundamentalist strategies in single encounter transactions may be useful in deducing the type of investment strategy from trading revenues of small portfolio investors.
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
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…
Unraveling chaotic attractors by complex networks and measurements of stock market complexity.
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. PMID:24697396
Unraveling chaotic attractors by complex networks and measurements of stock market complexity
Cao, Hongduo; Li, Ying
2014-03-15
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.
Unraveling chaotic attractors by complex networks and measurements of stock market complexity
NASA Astrophysics Data System (ADS)
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.
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.
Multivariate Markov chain modeling for stock markets
NASA Astrophysics Data System (ADS)
Maskawa, Jun-ichi
2003-06-01
We study a multivariate Markov chain model as a stochastic model of the price changes of portfolios in the framework of the mean field approximation. The time series of price changes are coded into the sequences of up and down spins according to their signs. We start with the discussion for small portfolios consisting of two stock issues. The generalization of our model to arbitrary size of portfolio is constructed by a recurrence relation. The resultant form of the joint probability of the stationary state coincides with Gibbs measure assigned to each configuration of spin glass model. Through the analysis of actual portfolios, it has been shown that the synchronization of the direction of the price changes is well described by the model.
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.
Confidence and the stock market: an agent-based approach.
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
Confidence and the Stock Market: An Agent-Based Approach
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
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2012-08-29
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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.
Multifractal Model of Asset Returns Versus Real Stock Market Dynamics
NASA Astrophysics Data System (ADS)
Oswiecimka, P.; Kwapieñ, J.; Drozdz, S.; Gorski, A. Z.; Rak, R.
2006-11-01
There is more and more empirical evidence that multifractality constitutes another and perhaps the most significant financial stylized fact. A realistic model of the financial dynamics should therefore incorporate this effect. The most promising in this respect is the Multifractal Model of Asset Returns (MMAR) introduced by Mandelbrot {ITALIC et al.} [1] in which multifractality is carried by time deformation. In our study we focus on the Lux extension to MMAR and empirical data from Warsaw Stock Exchange. We show that this model is able to reproduce relevant aspects of the real stock market dynamics.
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.
Market dynamics and stock price volatility
NASA Astrophysics Data System (ADS)
Li, H.; Rosser, J. B., Jr.
2004-06-01
This paper presents a possible explanation for some of the empirical properties of asset returns within a heterogeneous-agents framework. The model turns out, even if we assume the input fundamental value follows an simple Gaussian distribution lacking both fat tails and volatility dependence, these features can show up in the time series of asset returns. In this model, the profit comparison and switching between heterogeneous play key roles, which build a connection between endogenous market and the emergence of stylized facts.
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.
The normalisation of terror: the response of Israel's stock market to long periods of terrorism.
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. PMID:20735455
Understanding the complex dynamics of stock markets through cellular automata.
Qiu, G; Kandhai, D; Sloot, P M A
2007-04-01
We present a cellular automaton (CA) model for simulating the complex dynamics of stock markets. Within this model, a stock market is represented by a two-dimensional lattice, of which each vertex stands for a trader. According to typical trading behavior in real stock markets, agents of only two types are adopted: fundamentalists and imitators. Our CA model is based on local interactions, adopting simple rules for representing the behavior of traders and a simple rule for price updating. This model can reproduce, in a simple and robust manner, the main characteristics observed in empirical financial time series. Heavy-tailed return distributions due to large price variations can be generated through the imitating behavior of agents. In contrast to other microscopic simulation (MS) models, our results suggest that it is not necessary to assume a certain network topology in which agents group together, e.g., a random graph or a percolation network. That is, long-range interactions can emerge from local interactions. Volatility clustering, which also leads to heavy tails, seems to be related to the combined effect of a fast and a slow process: the evolution of the influence of news and the evolution of agents' activity, respectively. In a general sense, these causes of heavy tails and volatility clustering appear to be common among some notable MS models that can confirm the main characteristics of financial markets. PMID:17500970
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.
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.
Profitability of Contrarian Strategies in the Chinese Stock Market
Shi, Huai-Long; Jiang, Zhi-Qiang; Zhou, Wei-Xing
2015-01-01
This paper reexamines the profitability of loser, winner and contrarian portfolios in the Chinese stock market using monthly data of all stocks traded on the Shanghai Stock Exchange and Shenzhen Stock Exchange covering the period from January 1997 to December 2012. We find evidence of short-term and long-term contrarian profitability in the whole sample period when the estimation and holding horizons are 1 month or longer than 12 months and the annualized return of contrarian portfolios increases with the estimation and holding horizons. We perform subperiod analysis and find that the long-term contrarian effect is significant in both bullish and bearish states, while the short-term contrarian effect disappears in bullish states. We compare the performance of contrarian portfolios based on different grouping manners in the estimation period and unveil that decile grouping outperforms quintile grouping and tertile grouping, which is more evident and robust in the long run. Generally, loser portfolios and winner portfolios have positive returns and loser portfolios perform much better than winner portfolios. Both loser and winner portfolios in bullish states perform better than those in the whole sample period. In contrast, loser and winner portfolios have smaller returns in bearish states, in which loser portfolio returns are significant only in the long term and winner portfolio returns become insignificant. These results are robust to the one-month skipping between the estimation and holding periods and for the two stock exchanges. Our findings show that the Chinese stock market is not efficient in the weak form. These findings also have obvious practical implications for financial practitioners. PMID:26368537
Profitability of Contrarian Strategies in the Chinese Stock Market.
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
The cellular automaton model of investment behavior in the stock market
NASA Astrophysics Data System (ADS)
Wei, Yi-ming; Ying, Shang-jun; Fan, Ying; Wang, Bing-Hong
2003-07-01
The modeling theory and method using cellular automata are applied to the study on the complexity in the stock market. An evolution model based on cellular automaton for the investment behavior in the stock market is formulated. The simulation results and analyses of various states of the stock market show that investors’ imitation degree and the macro factors are the key determinants to the stability of the stock market. We observed that more diversity in the investment views of agents and lower imitation among investors are in favor of the normal development of the stock market.
A network analysis of the Chinese stock market
NASA Astrophysics Data System (ADS)
Huang, Wei-Qiang; Zhuang, Xin-Tian; Yao, Shuang
2009-07-01
In many practical important cases, a massive dataset can be represented as a very large network with certain attributes associated with its vertices and edges. Stock markets generate huge amounts of data, which can be use for constructing the network reflecting the market’s behavior. In this paper, we use a threshold method to construct China’s stock correlation network and then study the network’s structural properties and topological stability. We conduct a statistical analysis of this network and show that it follows a power-law model. We also detect components, cliques and independent sets in this network. These analyses allows one to apply a new data mining technique of classifying financial instruments based on stock price data, which provides a deeper insight into the internal structure of the stock market. Moreover, we test the topological stability of this network and find that it displays a topological robustness against random vertex failures, but it is also fragile to intentional attacks. Such a network stability property would be also useful for portfolio investment and risk management.
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.
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.
The multiscale analysis between stock market time series
NASA Astrophysics Data System (ADS)
Shi, Wenbin; Shang, Pengjian
2015-11-01
This paper is devoted to multiscale cross-correlation analysis on stock market time series, where multiscale DCCA cross-correlation coefficient as well as multiscale cross-sample entropy (MSCE) is applied. Multiscale DCCA cross-correlation coefficient is a realization of DCCA cross-correlation coefficient on multiple scales. The results of this method present a good scaling characterization. More significantly, this method is able to group stock markets by areas. Compared to multiscale DCCA cross-correlation coefficient, MSCE presents a more remarkable scaling characterization and the value of each log return of financial time series decreases with the increasing of scale factor. But the results of grouping is not as good as multiscale DCCA cross-correlation coefficient.
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)
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. PMID:23746973
Federal Register 2010, 2011, 2012, 2013, 2014
2012-04-09
... 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 Newly Listed Indexes April 3, 2012. Pursuant to Section 19(b)(1) of the Securities...
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.
Stock markets and quantum dynamics: A second quantized description
NASA Astrophysics Data System (ADS)
Bagarello, F.
2007-12-01
In this paper we continue our description of stock markets in terms of some non-abelian operators which are used to describe the portfolio of the various traders and other observable quantities. After a first prototype model with only two traders, we discuss a more realistic model of market involving an arbitrary number of traders. For both models we find approximated solutions for the time evolution of the portfolio of each trader. In particular, for the more realistic model, we use the stochastic limit approach and a fixed point like approximation.
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.
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.
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.
What stock market returns to expect for the future?
Diamond, P A
2000-01-01
In evaluating proposals for reforming Social Security that involve stock investments, the Office of the Chief Actuary (OCACT) has generally used a 7.0 percent real return for stocks. The 1994-96 Advisory Council specified that OCACT should use that return in making its 75-year projections of investment-based reform proposals. The assumed ultimate real return on Treasury bonds of 3.0 percent implies a long-run equity premium of 4.0 percent. There are two equity-premium concepts: the realized equity premium, which is measured by the actual rates of return; and the required equity premium, which investors expect to receive for being willing to hold available stocks and bonds. Over the past two centuries, the realized premium was 3.5 percent on average, but 5.2 percent for 1926 to 1998. Some critics argue that the 7.0 percent projected stock returns are too high. They base their arguments on recent developments in the capital market, the current high value of the stock market, and the expectation of slower economic growth. Increased use of mutual funds and the decline in their costs suggest a lower required premium, as does the rising fraction of the American public investing in stocks. The size of the decrease is limited, however, because the largest cost savings do not apply to the very wealthy and to large institutional investors, who hold a much larger share of the stock market's total value than do new investors. These trends suggest a lower equity premium for projections than the 5.2 percent of the past 75 years. Also, a declining required premium is likely to imply a temporary increase in the realized premium because a rising willingness to hold stocks tends to increase their price. Therefore, it would be a mistake during a transition period to extrapolate what may be a temporarily high realized return. In the standard (Solow) economic growth model, an assumption of slower long-run growth lowers the marginal product of capital if the savings rate is constant. But lower savings as growth slows should partially or fully offset that effect. The present high stock prices, together with projected slow economic growth, are not consistent with a 7.0 percent return. With a plausible level of adjusted dividends (dividends plus net share repurchases), the ratio of stock value to gross domestic product (GDP) would rise more than 20-fold over 75 years. Similarly, the steady-state Gordon formula--that stock returns equal the adjusted dividend yield plus the growth rate of stock prices (equal to that of GDP)--suggests a return of roughly 4.0 percent to 4.5 percent. Moreover, when relative stock values have been high, returns over the following decade have tended to be low. To eliminate the inconsistency posed by the assumed 7.0 percent return, one could assume higher GDP growth, a lower long-run stock return, or a lower short-run stock return with a 7.0 percent return on a lower base thereafter. For example, with an adjusted dividend yield of 2.5 percent to 3.0 percent, the market would have to decline about 35 percent to 45 percent in real terms over the next decade to reach steady state. In short, either the stock market is overvalued and requires a correction to justify a 7.0 percent return thereafter, or it is correctly valued and the long-run return is substantially lower than 7.0 percent (or some combination). This article argues that the "overvalued" view is more convincing, since the "correctly valued" hypothesis implies an implausibly small equity premium. Although OCACT could adopt a lower rate for the entire 75-year period, a better approach would be to assume lower returns over the next decade and a 7.0 percent return thereafter. PMID:11131980
An analysis of stock market efficiency: Developed vs Islamic stock markets using MF-DFA
NASA Astrophysics Data System (ADS)
Rizvi, Syed Aun R.; Dewandaru, Ginanjar; Bacha, Obiyathulla I.; Masih, Mansur
An efficient market has been theoretically proven to be a key component for effective and efficient resource allocation in an economy. This paper incorporates econophysics with Efficient Market Hypothesis to undertake a comparative analysis of Islamic and developed countries’ markets by extending the understanding of their multifractal nature. By applying the Multifractal Detrended Fluctuation Analysis (MFDFA) we calculated the generalized Hurst exponents, multifractal scaling exponents and generalized multifractal dimensions for 22 broad market indices. The findings provide a deeper understanding of the markets in Islamic countries, where they have traces of highly efficient performance particularly in crisis periods. A key finding is the empirical evidence of the impact of the ‘stage of market development’ on the efficiency of the market. If Islamic countries aim to improve the efficiency of resource allocation, an important area to address is to focus, among others, on enhancing the stage of market development.
Capability of markets to accept a new stock
NASA Astrophysics Data System (ADS)
Vahabi, M.; Jafari, G. R.
2007-11-01
Privatization is one of the most important elements of the continuing global phenomenon of the increasing use of markets to allocate resources. One important motivation for privatization is to help develop factor and product markets, as well as security markets. Among the various factors of market development, we try to answer to one of the main question: ‘which group of markets or indices is better to develop and absorb a new company?’. Our method is based on Level Crossing to quantify the following factors: stage of development, activity and risk of indices. As an example, considering Tehran Price Index (TEPIX), we compare financial and industrial indices to find which index is more preferable to absorb a new company in its group.
Scale-dependent price fluctuations for the Indian stock market
NASA Astrophysics Data System (ADS)
Matia, K.; Pal, M.; Salunkay, H.; Stanley, H. E.
2004-06-01
Classic studies of the probability density of price fluctuations g for stocks and foreign exchanges of several highly developed economies have been interpreted using a power law probability density function P(g) ~ g-(α + 1) with exponent values α > 2. To test the ubiquity of this relationship we analyze daily returns for the period November 1994 June 2002 for the 49 largest stocks of the National Stock Exchange which has the highest trade volume in India. We find the surprising result that P(g) decays as an exponential function P(g) ~ exp [ - βg] with a characteristic decay scale β = 1.51 ± 0.05 for the negative tail and β = 1.34 ± 0.04 for the positive tail. The exponential function is significantly different from the power law function observed for highly developed economies. Thus, we conclude that the stock market of the less highly developed economy of India belongs to a different class from that of highly developed countries.
Hidden temporal order unveiled in stock market volatility variance
NASA Astrophysics Data System (ADS)
Shapira, Y.; Kenett, D. Y.; Raviv, Ohad; Ben-Jacob, E.
2011-06-01
When analyzed by standard statistical methods, the time series of the daily return of financial indices appear to behave as Markov random series with no apparent temporal order or memory. This empirical result seems to be counter intuitive since investor are influenced by both short and long term past market behaviors. Consequently much effort has been devoted to unveil hidden temporal order in the market dynamics. Here we show that temporal order is hidden in the series of the variance of the stocks volatility. First we show that the correlation between the variances of the daily returns and means of segments of these time series is very large and thus cannot be the output of random series, unless it has some temporal order in it. Next we show that while the temporal order does not show in the series of the daily return, rather in the variation of the corresponding volatility series. More specifically, we found that the behavior of the shuffled time series is equivalent to that of a random time series, while that of the original time series have large deviations from the expected random behavior, which is the result of temporal structure. We found the same generic behavior in 10 different stock markets from 7 different countries. We also present analysis of specially constructed sequences in order to better understand the origin of the observed temporal order in the market sequences. Each sequence was constructed from segments with equal number of elements taken from algebraic distributions of three different slopes.
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
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
Market impact and trading profile of hidden orders in stock markets.
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. PMID:20365226
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?
Quantifying the Relationship Between Financial News and the Stock Market
NASA Astrophysics Data System (ADS)
Alanyali, Merve; Moat, Helen Susannah; Preis, Tobias
2013-12-01
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.
Dynamics of cross-correlations in the stock market
NASA Astrophysics Data System (ADS)
Rosenow, Bernd; Gopikrishnan, Parameswaran; Plerou, Vasiliki; Eugene Stanley, H.
2003-06-01
Co-movements of stock price fluctuations are described by the cross-correlation matrix C. The application of random matrix theory (RMT) allows to distinguish between spurious correlations in C due to measurement noise and true correlations containing economically meaningful information. By calculating cross-correlations for different time windows, we study the time dependence of eigenvectors of C, which are related to economic sectors, and the time evolution of the largest eigenvalue, which describes the average correlation strength. We use these results to forecast cross-correlations, and test the quality of our forecast by constructing investments in the stock market which expose the invested capital to a minimum level of risk only.
17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 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 2013-04-01 2013-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities...
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...
17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 17 Commodity and Securities Exchanges 3 2012-04-01 2012-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities Exchanges SECURITIES AND EXCHANGE COMMISSION (CONTINUED) GENERAL RULES AND REGULATIONS, SECURITIES EXCHANGE ACT OF 1934 Rules and Regulations Under...
17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 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 4 2014-04-01 2014-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities...
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...
Soccer and stock market risk: empirical evidence from the Istanbul Stock Exchange.
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. PMID:24245071
Federal Register 2010, 2011, 2012, 2013, 2014
2011-01-19
... COMMISSION Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change Relating to Routing Fees for the NASDAQ Options Market January 12, 2011...,\\2\\ notice is hereby given that on January 6, 2011, The NASDAQ Stock Market LLC (``NASDAQ''...
Skewness and Kurtosis as Applied to a Portfolio in the Korean Stock Market
NASA Astrophysics Data System (ADS)
Ahn, Tae-Sung
2009-04-01
A well diversified portfolio is critical to prudent investment in a stock market. To lessen risk in a volatile market, portfolios should minimize dispersion. This paper analyzes skewness and kurtosis of businesses listed on Korean stock markets, e.g., KOSPI and KOSDAQ. It looks at distribution using the Gauss function, and examines how mean and variance can be applied in building a portfolio.
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.
Testing for unit root bilinearity in the Brazilian stock market
NASA Astrophysics Data System (ADS)
Tabak, Benjamin M.
2007-11-01
In this paper a simple test for detecting bilinearity in a stochastic unit root process is used to test for the presence of nonlinear unit roots in Brazilian equity shares. The empirical evidence for a set of 53 individual stocks, after adjusting for GARCH effects, suggests that for more than 66%, the hypothesis of unit root bilinearity is accepted. Therefore, the dynamics of Brazilian share prices is in conformity with this type of nonlinearity. These nonlinearities in spot prices may emerge due to the sophistication of the derivatives market.
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.
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.
Linkages between international stock markets: A multivariate long-memory approach
NASA Astrophysics Data System (ADS)
Ozdemir, Zeynel Abidin
2009-06-01
This paper aims to analyze the linkages between international stock markets and to search for an optimum model for analyzing their interactions taking into consideration their geographical location, using the vector fractionally integrated autoregressive moving-average (VARFIMA) model. This model has not so far been employed in examining the interdependence among the stock markets of Germany, Japan, the UK, and the USA. The results of the paper show that there is an interconnection among the stock markets of these countries.
Kamstra, Mark J; Kramer, Lisa A; Levi, Maurice D
2013-02-01
In a 2011 reply to our 2010 comment in this journal, Berument and Dogen maintained their challenge to the existence of the negative daylight-saving effect in stock returns reported by Kamstra, Kramer, and Levi in 2000. Unfortunately, in their reply, Berument and Dogen ignored all of the points raised in the comment, failing even to cite the Kamstra, et al. comment. Berument and Dogen continued to use inappropriate estimation techniques, over-parameterized models, and low-power tests and perhaps most surprisingly even failed to replicate results they themselves reported in their previous paper, written by Berument, Dogen, and Onar in 2010. The findings reported by Berument and Dogen, as well as by Berument, Dogen, and Onar, are neither well-supported nor well-reasoned. We maintain our original objections to their analysis, highlight new serious empirical and theoretical problems, and emphasize that there remains statistically significant evidence of an economically large negative daylight-saving effect in U.S. stock returns. The issues raised in this rebuttal extend beyond the daylight-saving effect itself, touching on methodological points that arise more generally when deciding how to model financial returns data. PMID:23654029
ERIC Educational Resources Information Center
Morris, Michael W.; Sheldon, Oliver J.; Ames, Daniel R.; Young, Maia J.
2007-01-01
We investigated two types of metaphors in stock market commentary. "Agent" metaphors describe price trajectories as volitional actions, whereas "object" metaphors describe them as movements of inanimate objects. Study 1 examined the consequences of commentators' metaphors for their investor audience. Agent metaphors, compared with object metaphors
ERIC Educational Resources Information Center
Morris, Michael W.; Sheldon, Oliver J.; Ames, Daniel R.; Young, Maia J.
2007-01-01
We investigated two types of metaphors in stock market commentary. "Agent" metaphors describe price trajectories as volitional actions, whereas "object" metaphors describe them as movements of inanimate objects. Study 1 examined the consequences of commentators' metaphors for their investor audience. Agent metaphors, compared with object metaphors…
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.
Web Search Queries Can Predict Stock Market Volumes
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
Web search queries can predict stock market volumes.
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
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.
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.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Lin, Aijing; Ma, Hui; Shang, Pengjian
2015-10-01
Here we propose the new method DH-MMA, based on multiscale multifractal detrended fluctuation analysis(MMA), to investigate the scaling properties in stock markets. It is demonstrated that our approach can provide a more stable and faithful description of the scaling properties in comprehensive range rather than fixing the window length and slide length. It allows the assessment of more universal and subtle scaling characteristics. We illustrate DH-MMA by selecting power-law artificial data sets and six stock markets from US and China. The US stocks exhibit very strong multifractality for positive values of q, however, the Chinese stocks show stronger multifractality for negative q than positive q. In general, the US stock markets show similar behaviors, but Chinese stock markets display distinguishing characteristics.
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.
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.
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.
Liquidity Spillover in International Stock Markets through Distinct Time Scales
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
Evidence of Multifractality from Emerging European Stock Markets
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. PMID:22815792
Statistical Properties and Pre-Hit Dynamics of Price Limit Hits in the Chinese Stock Markets
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
Statistical properties and pre-hit dynamics of price limit hits in the Chinese stock markets.
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
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Kenett, Dror Y.; Tumminello, Michele; Madi, Asaf; Gur-Gershgoren, Gitit; Mantegna, Rosario N.; Ben-Jacob, Eshel
2010-01-01
What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question—the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001–2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market. PMID:21188140
Kenett, Dror Y; Tumminello, Michele; Madi, Asaf; Gur-Gershgoren, Gitit; Mantegna, Rosario N; Ben-Jacob, Eshel
2010-01-01
What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001-2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market. PMID:21188140
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.
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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.
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.
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.
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. Although the emphasis of this thesis is on the extent to which multi-agent models can produce complex dynamics, some attempt is also made to relate this work with empirical data. Firstly, the trading strategy applied by the agents in the second model is demonstrated to be adequate, if not optimal, and to have some surprising consequences. Secondly, the claim put forth by Sornette et al. [1] that large financial crashes may be heralded by accelerating precursory oscillations is also tested. It is shown that there is weak evidence for the existence of log-periodic precursors but the signal is probably too indistinct to allow for reliable predictions.
Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.
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
NASA Astrophysics Data System (ADS)
Czarnecki, Łukasz; Grech, Dariusz; Pamuła, Grzegorz
2008-12-01
We confront global and local methods to analyze the financial crash-like events on the Polish financial market from the critical phenomena point of view. These methods are based on the analysis of log-periodicity and the local fractal properties of financial time series in the vicinity of phase transitions (crashes). The whole history (1991-2008) of Warsaw Stock Exchange Index (WIG) describing the largest developing financial market in Europe, is analyzed in a daily time horizon. We find that crash-like events on the Polish financial market are described better by the log-divergent price model decorated with log-periodic behavior than the corresponding power-law-divergent price model. Predictions coming from log-periodicity scenario are verified for all main crashes that took place in WIG history. It is argued that crash predictions within log-periodicity model strongly depend on the amount of data taken to make a fit and therefore are likely to contain huge inaccuracies. Turning to local fractal description, we calculate the so-called local (time dependent) Hurst exponent H for the WIG time series and we find the dependence between the behavior of the local fractal properties of the WIG time series and the crashes appearance on the financial market. The latter method seems to work better than the global approach - both for developing as for developed markets. The current situation on the market, particularly related to the Fed intervention in September’07 and the situation on the market immediately after this intervention is also analyzed from the fractional Brownian motion point of view.
Impact of stock market structure on intertrade time and price dynamics.
Ivanov, Plamen Ch; Yuen, Ainslie; Perakakis, Pandelis
2014-01-01
We analyse times between consecutive transactions for a diverse group of stocks registered on the NYSE and NASDAQ markets, and we relate the dynamical properties of the intertrade times with those of the corresponding price fluctuations. We report that market structure strongly impacts the scale-invariant temporal organisation in the transaction timing of stocks, which we have observed to have long-range power-law correlations. Specifically, we find that, compared to NYSE stocks, stocks registered on the NASDAQ exhibit significantly stronger correlations in their transaction timing on scales within a trading day. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing on scales within a trading day, indicating influences of market structure. We also report a persistent decrease in correlation strength of intertrade times with increasing average intertrade time and with corresponding decrease in companies' market capitalization-a trend which is less pronounced for NASDAQ stocks. Surprisingly, we observe that stronger power-law correlations in intertrade times are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of intertrade times and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ markets, we demonstrate that the stronger correlations we find in intertrade times for NASDAQ stocks are associated with stronger correlations in absolute price returns and with higher volatility, suggesting that market structure may affect price behavior through information contained in transaction timing. These findings do not support the hypothesis of universal scaling behavior in stock dynamics that is independent of company characteristics and stock market structure. Further, our results have implications for utilising transaction timing patterns in price prediction and risk management optimization on different stock markets. PMID:24699376
Impact of Stock Market Structure on Intertrade Time and Price Dynamics
Ivanov, Plamen Ch.; Yuen, Ainslie; Perakakis, Pandelis
2014-01-01
We analyse times between consecutive transactions for a diverse group of stocks registered on the NYSE and NASDAQ markets, and we relate the dynamical properties of the intertrade times with those of the corresponding price fluctuations. We report that market structure strongly impacts the scale-invariant temporal organisation in the transaction timing of stocks, which we have observed to have long-range power-law correlations. Specifically, we find that, compared to NYSE stocks, stocks registered on the NASDAQ exhibit significantly stronger correlations in their transaction timing on scales within a trading day. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing on scales within a trading day, indicating influences of market structure. We also report a persistent decrease in correlation strength of intertrade times with increasing average intertrade time and with corresponding decrease in companies' market capitalization–a trend which is less pronounced for NASDAQ stocks. Surprisingly, we observe that stronger power-law correlations in intertrade times are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of intertrade times and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ markets, we demonstrate that the stronger correlations we find in intertrade times for NASDAQ stocks are associated with stronger correlations in absolute price returns and with higher volatility, suggesting that market structure may affect price behavior through information contained in transaction timing. These findings do not support the hypothesis of universal scaling behavior in stock dynamics that is independent of company characteristics and stock market structure. Further, our results have implications for utilising transaction timing patterns in price prediction and risk management optimization on different stock markets. PMID:24699376
Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets
NASA Astrophysics Data System (ADS)
Eom, Cheoljun; Choi, Sunghoon; Oh, Gabjin; Jung, Woo-Sung
2008-07-01
We empirically investigated the relationships between the degree of efficiency and the predictability in financial time-series data. The Hurst exponent was used as the measurement of the degree of efficiency, and the hit rate calculated from the nearest-neighbor prediction method was used for the prediction of the directions of future price changes. We used 60 market indexes of various countries. We empirically discovered that the relationship between the degree of efficiency (the Hurst exponent) and the predictability (the hit rate) is strongly positive. That is, a market index with a higher Hurst exponent tends to have a higher hit rate. These results suggested that the Hurst exponent is useful for predicting future price changes. Furthermore, we also discovered that the Hurst exponent and the hit rate are useful as standards that can distinguish emerging capital markets from mature capital markets.
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.
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.
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2012-08-20
..., that of other market participants, the integrity of trading on the securities markets, or the stability... other order information common to all order types, such as buy/sell side, shares and price.\\6\\ \\5\\ See... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Instituting Proceedings...
Fractional Market Model and its Verification on the Warsaw STOCK Exchange
NASA Astrophysics Data System (ADS)
Kozłowska, Marzena; Kasprzak, Andrzej; Kutner, Ryszard
We analyzed the rising and relaxation of the cusp-like local peaks superposed with oscillations which were well defined by the Warsaw Stock Exchange index WIG in a daily time horizon. We found that the falling paths of all index peaks were described by a generalized exponential function or the Mittag-Leffler (ML) one superposed with various types of oscillations. However, the rising paths (except the first one of WIG which rises exponentially and the most important last one which rises again according to the ML function) can be better described by bullish anti-bubbles or inverted bubbles.2-4 The ML function superposed with oscillations is a solution of the nonhomogeneous fractional relaxation equation which defines here our Fractional Market Model (FMM) of index dynamics which can be also called the Rheological Model of Market. This solution is a generalized analog of an exactly solvable fractional version of the Standard or Zener Solid Model of viscoelastic materials commonly used in modern rheology.5 For example, we found that the falling paths of the index can be considered to be a system in the intermediate state lying between two complex ones, defined by short and long-time limits of the Mittag-Leffler function; these limits are given by the Kohlrausch-Williams-Watts (KWW) law for the initial times, and the power-law or the Nutting law for asymptotic time. Some rising paths (i.e., the bullish anti-bubbles) are a kind of log-periodic oscillations of the market in the bullish state initiated by a crash. The peaks of the index can be viewed as precritical or precrash ones since: (i) the financial market changes its state too early from the bullish to bearish one before it reaches a scaling region (defined by the diverging power-law of return per unit time), and (ii) they are affected by a finite size effect. These features could be a reminiscence of a significant risk aversion of the investors and their finite number, respectively. However, this means that the scaling region (where the relaxations of indexes are described by the KWW law or stretched exponential decay) was not observed. Hence, neither was the power-law of the instantaneous returns per unit time observed. Nevertheless, criticality or crash is in a natural way contained in our FMM and we found its "finger print".
NASA Astrophysics Data System (ADS)
Dionisio, A.; Menezes, R.; Mendes, D. A.
2006-03-01
In recent years there has been a closer interrelationship between several scientific areas trying to obtain a more realistic and rich explanation of the natural and social phenomena. Among these it should be emphasized the increasing interrelationship between physics and financial theory. In this field the analysis of uncertainty, which is crucial in financial analysis, can be made using measures of physics statistics and information theory, namely the Shannon entropy. One advantage of this approach is that the entropy is a more general measure than the variance, since it accounts for higher order moments of a probability distribution function. An empirical application was made using data collected from the Portuguese Stock Market.
Predictive fuzzy reasoning method for time series stock market data mining
NASA Astrophysics Data System (ADS)
Khokhar, Rashid H.; Md Sap, Mohd Noor
2005-03-01
Data mining is able to uncover hidden patterns and predict future trends and behaviors in financial markets. In this research we approach quantitative time series stock selection as a data mining problem. We present another modification of extraction of weighted fuzzy production rules (WFPRs) from fuzzy decision tree by using proposed similarity-based fuzzy reasoning method called predictive reasoning (PR) method. In proposed predictive reasoning method weight parameter can be assigned to each proposition in the antecedent of a fuzzy production rule (FPR) and certainty factor (CF) to each rule. Certainty factors are calculated by using some important variables like effect of other companies, effect of other local stock market, effect of overall world situation, and effect of political situation from stock market. The predictive FDT has been tested using three data sets including KLSE, NYSE and LSE. The experimental results show that WFPRs rules have high learning accuracy and also better predictive accuracy of stock market time series data.
Convergence of fundamentalists and chartists’ expectations: An alarm for stock market crash
NASA Astrophysics Data System (ADS)
Bolgorian, Meysam; Raei, Reza
2010-09-01
We construct a network of the Tehran stock market based on the cross-correlation of trading volume of stocks both for fundamentalists and chartists. In order to investigate the dynamics of expectations of fundamentalists and chartists over time we introduced a homogeneity coefficient. Our results show that in the Tehran Stock Exchange (TSE) which is an emerging market, chartists in comparison with fundamentalists more strongly believe the stocks’ co-movements. We also found that in a bull market (booming period), the optimism of fundamentalists and chartists about the similarity of stocks’ performance diverge from each other while in a bear market (recession period) both groups of traders have approximately same level of pessimism about the simultaneous collapse of stock prices.
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.
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.
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2010-07-06
... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule... that on June 21, 2010, The NASDAQ Stock Market LLC (the ``Exchange'' or ``NASDAQ'') filed with the... mechanism of a free and open market and a national market system, and, in general, to protect investors...
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2011-03-02
... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...\\ notice is hereby given that, on February 23, 2011, The NASDAQ Stock Market LLC (the ``Exchange'' or... mechanism of a free and open market and a national market system, and, in general, to protect investors...
Impact of Stock Market Structure on Intertrade Time and Price Dynamics
NASA Astrophysics Data System (ADS)
Yuen, Ainslie; Ivanov, Plamen Ch.
2005-08-01
The NYSE and NASDAQ stock markets have very different structures and there is continuing controversy over whether differences in stock price behaviour are due to market structure or company characteristics. As the influence of market structure on stock prices may be obscured by exogenous factors such as demand and supply, we hypothesize that modulation of the flow of transactions due to market operations may carry a stronger imprint of the internal market mechanism. We analyse times between consecutive transactions (ITT) for NYSE and NASDAQ stocks, and we relate the dynamical properties of the ITT with those of the corresponding price fluctuations. We find a robust scale-invariant temporal organisation in the ITT of stocks which is independent of individual company characteristics and industry sector, but which depends on market structure. We find that stocks registered on the NASDAQ exhibit stronger correlations in their transaction timing within a trading day, compared with NYSE stocks. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing within a trading day, after the move, suggesting influences of market structure. Surprisingly, we also observe that stronger power-law correlations in the ITT are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of ITT and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ, we demonstrate that the higher correlations we find in ITT for NASDAQ stocks are matched by higher correlations in absolute price returns and by higher volatility, suggesting that market structure may affect price behaviour through information contained in transaction timing.
NASA Astrophysics Data System (ADS)
Liu, Li; Wan, Jieqiu
2012-12-01
This paper explores the co-movement of Shanghai stock market and China Yuan (CNY) exchange rates. First, we find that stock price and exchange rate are significantly cross-correlated. Second, employing a cointegration test allowing for a structural break, we find that the Shanghai Composite Index (SCI) is not cointegrated with the exchange rate of CNY/USD. The so-called cointegration found in previous studies is just caused by the shock of the recent financial crisis. Third, using linear and nonlinear Granger causality tests, we find no causality between stock prices and exchange rates during the period before the recent financial crisis. After the financial crisis, a unidirectional causality behavior running from exchange rates to stock index is present.
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2013-06-11
... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...,\\2\\ notice is hereby given that on May 24, 2013 The NASDAQ Stock Market LLC (``NASDAQ'' or the... those MOPB orders that execute at the New York Stock Exchange, which will be charged $0.0027 per...
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2010-03-12
... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Approval of Proposed Rule Change To Modify the Fees for Listing on the Nasdaq Stock Market and the Fee for Written Interpretations of Nasdaq Listing Rules March 5, 2010. I. Introduction On October 6, 2009, The NASDAQ Stock...
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.
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.
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.
NASA Astrophysics Data System (ADS)
Grech, Dariusz; Pamuła, Grzegorz
2008-07-01
We investigate the local fractal properties of the financial time series based on the whole history evolution (1991-2007) of the Warsaw Stock Exchange Index (WIG), connected with the largest developing financial market in Europe. Calculating the so-called local time-dependent Hurst exponent H for the WIG time series we find the dependence between the behavior of the local fractal properties of the WIG time series and the crashes’ appearance on the financial market. We formulate the necessary conditions based on the H behavior which have to be satisfied if the rupture or crash point is expected soon. As a result we show that the signal to sell or the signal to buy on the stock exchange market can be translated into H evolution pattern. We also find a relation between the rate of the H drop and the total correction the WIG index gains after the crash. The current situation on the market, particularly related to the recent Fed intervention in September ’07, is also discussed.
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 that there is already some research on the domain of Econophysics, which points out that as a measure of disorder, distance from equilibrium or even ignorance, entropy might present some advantages. However another question arises: since there is several measures of entropy which one since there are several measures of entropy, which one shall be used? As a starting point we discuss the potentialities of Shannon entropy and Tsallis entropy. The main difference between them is that both Renyi and Tsallis are adequate for anomalous systems while Shannon has revealed optimal for equilibrium systems.
HMO behavior and stock market valuation: what does Wall Street reward and punish?
Pauly, M V; Hillman, A L; Furukawa, M F; McCullough, J S
2001-01-01
This article analyzes the variation in returns to owning stock in investor-owned health maintenance organizations (IOHMOs) for the period 1994-1997. The average return (measured by the change in the market value of the stock plus dividends) was close to zero, but returns were positive and high for firms operating in local markets that were and remained less competitive, with large nationwide scope, and with less rapidly growing panels of contracted physicians. Indicators of a firm's strategic direction were abstracted from their annual reports; firms pursuing a merger or acquisition strategy, and those emphasizing a utilization review strategy, showed lower returns than those that did not. Other strategy and market variables were not related to stock market returns over this period, and were also generally not related to price-earnings ratios. This analysis supports the view that competitive HMO markets best constrain profits to investor-owned firms. PMID:11669294
The Dow is Killing Me: Risky Health Behaviors and the Stock Market.
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. PMID:24803424
Dynamic Evolution of Cross-Correlations in the Chinese Stock Market
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
Dynamic evolution of cross-correlations in the Chinese stock market.
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
Modeling EU electricity market competition using the residual supply index
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)
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…
Association between Stock Market Gains and Losses and Google Searches.
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
Association between Stock Market Gains and Losses and Google Searches
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
Bull and Bear: The Stock Market. Social Studies: 6448.13.
ERIC Educational Resources Information Center
Cooper, Sidney H.
This political and economic study unit is designed to provide students with an understanding of how the stock market works; an examination of the corporate form of business organization; principles of investment; analysis of market action and patterns; types of securities; sources of financial information; and the rationale of investment choices.
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.
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2011-09-26
... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Disapproving a Proposed Rule Change To Link Market Data Fees and Transaction Execution Fees September 20, 2011. I. Introduction On January 10, 2011, The NASDAQ Stock Market...
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... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of a Proposed Rule Change To Update the NASDAQ Options Market Message Traffic Mitigation Rule June... 19b-4 \\2\\ thereunder, notice is hereby given that, on May 29, 2012, The NASDAQ Stock Market...
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... 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 April 16, 2010...,\\2\\ notice is hereby given that on April 13, 2010, The NASDAQ Stock Market LLC (``NASDAQ'')...
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.
Speculative bubbles and crashes in stock markets: an interacting-agent model of speculative activity
NASA Astrophysics Data System (ADS)
Kaizoji, Taisei
2000-12-01
In this paper, we present an interacting-agent model of speculative activity explaining bubbles and crashes in stock markets. We describe stock markets through an infinite-range Ising model to formulate the tendency of traders getting influenced by the investment attitude of other traders. Bubbles and crashes are understood and described qualitatively and quantitatively in terms of the classical phase transitions. When the interactions among traders become stronger and reach some critical values, a second-order phase transition and critical behavior can be observed, and a bull market phase and a bear market phase appear. When the system stays at the bull market phase, speculative bubbles occur in the stock market. For a certain range of the investment environment (the external field), multistability and hysteresis phenomena are observed. When the investment environment reaches some critical values, the rapid changes (the first-order phase transitions) in the distribution of investment attitude are caused. The phase transition from a bull market phase to a bear market phase is considered as a stock market crash. Furthermore, we estimate the parameters of the model using the actual financial data. As an example of large crashes we analyze Japan crisis (the bubble and the subsequent crash in the Japanese stock market in 1987-1992), and show that the good quality of the fits, as well as the consistency of the parameter values are obtained from Japan crisis. The results of the empirical study demonstrate that Japan crisis can be explained quite naturally by the model that bubbles and crashes have their origin in the collective crowd behavior of many interacting agents.
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.
Who wins? Study of long-run trader survival in an artificial stock market
NASA Astrophysics Data System (ADS)
Cincotti, Silvano; M. Focardi, Sergio; Marchesi, Michele; Raberto, Marco
2003-06-01
We introduce a multi-asset artificial financial market with finite amount of cash and number of stocks. The background trading is characterized by a random trading strategy constrained by the finiteness of resources and by market volatility. Stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Three active trading strategies have been introduced and studied in two different market conditions: steady market and growing market with asset inflation. We show that the profitability of each strategy depends both on the periodicity of portfolio reallocation and on the market condition. The best performing strategy is the one that exploits the mean reversion characteristic of asset price processes.
Life insurance investment and stock market participation in Europe.
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. PMID:24797469
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.
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.
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.
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.
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).
Investor Behavior and Flow-through Capability in the US Stock Market
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.
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.
26 CFR 1.1296-2 - Definition of marketable stock.
Code of Federal Regulations, 2010 CFR
2010-04-01
... trading volume, listing, financial disclosure, surveillance, and other requirements designed to prevent... financial statements of the foreign corporation that include balance sheets (statements of assets... calendar year in which a corporation initiates a public offering of a class of stock for trading on one...
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
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
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Effects of Daylight Saving Time changes on stock market volatility: a reply.
Berument, Hakan; Dogan, Nukhet
2011-12-01
There is a rich array of evidence that suggests that changes in sleeping patterns affect an individual's decision-making processes. A nationwide sleeping-pattern change happens twice a year when the Daylight Saving Time (DST) change occurs. Kamstra, Kramer, and Levi argued in 2000 that a DST change lowers stock market returns. This study presents evidence that DST changes affect the relationship between stock market return and volatility. Empirical evidence suggests that the positive relationship between return and volatility becomes negative on the Mondays following DST changes. PMID:22420117
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.
Research on Prediction of Stock Index based on PCA and SVM
NASA Astrophysics Data System (ADS)
Xue, Hongxin; Bai, Yanping
This paper combines principal component analysis and support vector machine (SVM) regression to analysis stock. Principal component analysis method is applied to extract contribution rate to meet 90% of the principal component as the input variables with Shanghai Composite Index and Shenhua Holdings to be modeled and predicted. Results of the demonstration shows that PCA-SVM model is more accurate to predict the opening price of the Shanghai Composite Index and Shenhua Holding. The final result of fitting that mean squared error of train set and test set and squared correlation coefficient of train set R2 and test set R2 of the Shanghai Composite Index and Shenhua Holding in PCA-SVM model are 0.000029, 0.000059, 99.91%, 99.10%, 0.000073, 0.000060, 99.74%, 98.43%, respectively. Meanwhile, the results in SVM model are 0.000038, 0.000799, 99.86%, 93.44%, 0.000042, 0.000268, 99.85%, 91.93%, respectively. The above data prove the advantages of the PCA-SVM model in the stock prediction.
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.
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.
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.
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.
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-Jones index for the time lags from 1 to 250 trading days. For time lags longer than the relaxation time of variance, the probability distribution can be expressed in a scaling form using a Bessel function. The Dow-Jones data follow the scaling function for seven orders of magnitude.
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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.
New Results on Gain-Loss Asymmetry for Stock Markets Time Series
NASA Astrophysics Data System (ADS)
Grudziecki, M.; Gnatowska, E.; Karpio, K.; Orłowski, A.; Załuska-Kotur, M.
2008-09-01
A method called investment horizon approach was successfully used to analyze stock markets of many different countries. Here we apply a version of this method to study characteristics of the Polish Pioneer mutual funds. We decided to analyze Pioneer because of its longest involvement in investing on the Polish market. Moreover, it apparently manages the biggest amount of money among all similar institutions in Poland. We compare various types of Pioneer mutual funds, characterized by different financial instruments they invest in. Previously, investment horizon approach produced different characteristics of emerging markets as opposed to mature ones, providing a possible way to quantify stock market maturity. Here we generalize the above mentioned results for mutual funds of various types.
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.
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.
Are stock market returns related to the weather effects? Empirical evidence from Taiwan
NASA Astrophysics Data System (ADS)
Chang, Tsangyao; Nieh, Chien-Chung; Yang, Ming Jing; Yang, Tse-Yu
2006-05-01
In this study, we employ a recently developed econometric technique of the threshold model with the GJR-GARCH process on error terms to investigate the relationships between weather factors and stock market returns in Taiwan using daily data for the period of 1 July 1997-22 October 2003. The major weather factors studied include temperature, humidity, and cloud cover. Our empirical evidence shows that temperature and cloud cover are two important weather factors that affect the stock returns in Taiwan. Our empirical findings further support the previous arguments that advocate the inclusion of economically neutral behavioral variables in asset pricing models. These results also have significant implications for individual investors and financial institutions planning to invest in the Taiwan stock market.
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.
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.
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…
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.…
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.
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.
A morphological perceptron with gradient-based learning for Brazilian stock market forecasting.
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
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.
Cross-Correlations in Warsaw Stock Exchange
NASA Astrophysics Data System (ADS)
Rak, R.; Kwapień, J.; Oświęcimka, P.; Drożdż, S.
2008-09-01
We study the inter-stock correlations for the largest companies listed on Warsaw Stock Exchange and included in the WIG20 index. Our results from the correlation matrix analysis indicate that the Polish stock market can be well described by a one-factor model. We also show that the stock- stock correlations tend to increase with the timescale of returns and they approach a saturation level for the timescales of at least 200 min, i.e. an order of magnitude longer than in the case of some developed markets. We also show that the strength of correlations among the stocks crucially depends on their capitalization. These results combined with our earlier findings together suggest that now the Polish stock market situates itself somewhere between an emerging market phase and a mature market phase.
Dream characteristics of stock brokers after a major market downturn.
Kroth, Jerry; Thompson, Lisa; Jackson, Judy; Pascali, Lesa; Ferreira, Marie
2002-06-01
Dream characteristics of 28 stock brokers during the second worst weekly performance of the Dow Jones Industrial Average in the last 11 yr. were measured using the KJP Dream Inventory. Additional measures of powerlessness and stress were administered as well. Significant correlations appeared between the amount of stress brokers reported during this week and the appearance of recurring nightmares (.59), feelings of being chased (.42), and dreams' pleasantness (-.64). The brokers' clients' investment performance was correlated significantly with changes in the brokers' experience of traumatic dreams (-.57) and dreams of falling (-.43). Further, as the brokers' own personal investments deteriorated overall, dreaming increased (.48), suggesting compensatory mechanisms. Results were discussed in terms of the relationship between onset of acute traumatic states and dreaming. PMID:12150390
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.
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
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…
26 CFR 1.1296-2 - Definition of marketable stock.
Code of Federal Regulations, 2011 CFR
2011-04-01
... exchange has trading volume, listing, financial disclosure, surveillance, and other requirements designed... annually, independent auditors prepare financial statements of the foreign corporation that include balance... trading on one or more qualified exchanges or other markets, as defined in paragraph (c) of this...
26 CFR 1.1296-2 - Definition of marketable stock.
Code of Federal Regulations, 2013 CFR
2013-04-01
... exchange has trading volume, listing, financial disclosure, surveillance, and other requirements designed... annually, independent auditors prepare financial statements of the foreign corporation that include balance... trading on one or more qualified exchanges or other markets, as defined in paragraph (c) of this...
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.
Stock markets as Minority Games: cognitive heterogeneity and equilibrium emergence
NASA Astrophysics Data System (ADS)
Brandouy, O.
2005-04-01
Standard finance theory generally assumes homogeneous agents relatively to their preferences, heuristics and investment strategies. We propose to study, in an agent-based simulation, the emergence of equilibrium under various heterogeneous conditions. Market interaction is stylized with the Minority Game representation. It is shown that inductive rational equilibrium emerges even though agents do not share the same representations of the value. This may lead to consider again the roots of EMH and REH.
Multifractality in the stock market: price increments versus waiting times
NASA Astrophysics Data System (ADS)
Oświeçimka, P.; Kwapień, J.; Drożdż, S.
2005-03-01
By applying the multifractal detrended fluctuation analysis to the high-frequency tick-by-tick data from Deutsche Börse both in the price and in the time domains, we investigate multifractal properties of the time series of logarithmic price increments and inter-trade intervals of time. We show that both quantities reveal multiscaling and that this result holds across different stocks. The origin of the multifractal character of the corresponding dynamics is, among others, the long-range correlations in price increments and in inter-trade time intervals as well as the non-Gaussian distributions of the fluctuations. Since the transaction-to-transaction price increments do not strongly depend on or are almost independent of the inter-trade waiting times, both can be sources of the observed multifractal behaviour of the fixed-delay returns and volatility. The results presented also allow one to evaluate the applicability of the Multifractal Model of Asset Returns in the case of tick-by-tick data.
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.
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
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
Mood and the market: can press reports of investors' mood predict stock prices?
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. PMID:24015202
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).
Mood and the Market: Can Press Reports of Investors' Mood Predict Stock Prices?
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
ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting
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
ℓ(p)-Norm multikernel learning approach for stock market price forecasting.
Shao, Xigao; Wu, Kun; Liao, Bifeng
2012-01-01
Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-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 ℓ(p)-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 ℓ(1)-norm multiple support vector regression model. PMID:23365561
NASA Astrophysics Data System (ADS)
Solomon, Sorin; Levy, Moshe
2001-06-01
The LLS stock market model (see Levy Levy and Solomon Academic Press 2000 "Microscopic Simulation of Financial Markets; From Investor Behavior to Market Phenomena" for a review) is a model of heterogeneous quasi-rational investors operating in a complex environment about which they have incomplete information. We review the main features of this model and several of its extensions. We study the effects of investor heterogeneity and show that predation, competition, or symbiosis may occur between different investor populations. The dynamics of the LLS model lead to the empirically observed Pareto wealth distribution. Many properties observed in actual markets appear as natural consequences of the LLS dynamics: - truncated Levy distribution of short-term returns, - excess volatility, - a return autocorrelation "U-shape" pattern, and - a positive correlation between volume and absolute returns.
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.
On the scaling of the distribution of daily price fluctuations in the Mexican financial market index
NASA Astrophysics Data System (ADS)
Alfonso, Léster; Mansilla, Ricardo; Terrero-Escalante, César A.
2012-05-01
In this paper, a statistical analysis of log-return fluctuations of the IPC, the Mexican Stock Market Index is presented. A sample of daily data covering the period from 04/09/2000-04/09/2010 was analyzed, and fitted to different distributions. Tests of the goodness of fit were performed in order to quantitatively asses the quality of the estimation. Special attention was paid to the impact of the size of the sample on the estimated decay of the distributions tail. In this study a forceful rejection of normality was obtained. On the other hand, the null hypothesis that the log-fluctuations are fitted to a α-stable Lévy distribution cannot be rejected at the 5% significance level.
Information-driven trade and price-volume relationship in artificial stock markets
NASA Astrophysics Data System (ADS)
Liu, Xinghua; Liu, Xin; Liang, Xiaobei
2015-07-01
The positive relation between stock price changes and trading volume (price-volume relationship) as a stylized fact has attracted significant interest among finance researchers and investment practitioners. However, until now, consensus has not been reached regarding the causes of the relationship based on real market data because extracting valuable variables (such as information-driven trade volume) from real data is difficult. This lack of general consensus motivates us to develop a simple agent-based computational artificial stock market where extracting the necessary variables is easy. Based on this model and its artificial data, our tests have found that the aggressive trading style of informed agents can produce a price-volume relationship. Therefore, the information spreading process is not a necessary condition for producing price-volume relationship.
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.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-11-19
... orders that incur risk by setting the inside market or allowing NASDAQ to join another trading center... registered as market makers, they risk capital by offering immediately executable liquidity at the price most... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and...
Federal Register 2010, 2011, 2012, 2013, 2014
2012-01-24
... Markets Local Debt Fund); 62623 (August 2, 2010), 75 FR 47652 (August 6, 2010) (SR-NYSEArca-2010-51...., Investment Company Act Release No. 9011 (Oct. 30, 1975), 40 FR 54241 (November 21, 1975). Money Market... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed...
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2012-03-06
... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Approval of Proposed Rule Change Relating to the Listing and Trading of Shares of the Emerging Markets Corporate Bond Fund... Market LLC (``Nasdaq'' or ``Exchange'') filed with the Securities and Exchange Commission...
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2010-08-04
... given that on July 28, 2010, The NASDAQ Stock Market LLC (``NASDAQ'') filed with the Securities and... Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Increase Closing Cross Fees for Market-on-Close and Limit-on-Close Orders July 29, 2010. Pursuant to Section 19(b)(1)...
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2013-03-21
... Rule 5250 and NASDAQ IM-5250, which require overnight material disclosures to be forwarded to Market... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change to Extend the Pre-Market Hours of the Exchange to 4:00 a.m. EST March...
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2011-02-15
... 4, 2011), 76 FR 1653 (January 11, 2011) (SR-NYSE-2010-87). Second, NASDAQ is modifying the fee for... value to an exchange's market quality associated with higher levels of market activity, such as higher... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and...
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.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-12-27
... 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 to Modify Rule 7034 Regarding Low Latency Network Connections December 20, 2011. I. Introduction On October 31, 2011, the NASDAQ Stock...
Federal Register 2010, 2011, 2012, 2013, 2014
2011-08-16
... individual stock trading pause, Nasdaq will pause trading in that security until trading has resumed on the... Arca''), and National Stock Exchange, Inc. (collectively, the ``Exchanges''), to pause trading during...), 75 FR 34186 (June 16, 2010) (SR-NASDAQ-2010-061). \\4\\ The term ``Listing Markets''...
Federal Register 2010, 2011, 2012, 2013, 2014
2012-08-03
... Exchange Act of 1934. If a primary listing market issues an individual stock trading pause, Nasdaq will... Arca''), and National Stock Exchange, Inc. (collectively, the ``Exchanges''), to pause trading during... Act Release No. 62252 (June 10, 2010), 75 FR 34186 (June 16, 2010) (SR-NASDAQ-2010-061). \\4\\ The...
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...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-05-10
... given that on April 24, 2013, The NASDAQ Stock Market LLC (``NASDAQ'' or ``Exchange'') filed with the... proposed rule change conforms to the current practice of the New York Stock Exchange (``NYSE'') and... From the Federal Register Online via the Government Publishing Office SECURITIES AND...
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…
Some new results on the Levy, Levy and Solomon microscopic stock market model
NASA Astrophysics Data System (ADS)
Zschischang, Elmar; Lux, Thomas
2001-03-01
We report some findings from our simulations of the Levy, Levy and Solomon microscopic stock market model. Our results cast doubts on some of the results published in the original papers (i.e., chaotic stock price movements). We also point out the possibility of sensitive dependence on initial conditions of the emerging wealth distribution among agents. Extensions of the model set-up show that with varying degrees of risk aversion, the less risk averse traders will tend to dominate the market. Similarly, when introducing a new trader group (or even a single trader) with a constant share of stocks in their portfolio, the latter will eventually take over and marginalize the other groups. The better performance of the more sober investors is in accordance with traditional perceptions in financial economics. Hence, the survival of ‘noise traders’ looking at short-term trends and patterns remains as much of a puzzle in this framework as in the traditional Efficient Market Theory.
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.
Note on the stock market's reaction to the accident at Three Mile Island
Spudeck, R.E.; Moyer, C.R. )
1989-08-01
This note provides new information regarding the market reaction toward electric utility stocks that resulted both from the accident at Three Mile Island, and the events predating and postdating the accident. The results suggest that some of the market reaction heretofore ascribed to the accident resulted instead from regulatory activity occurring before the accident. We also provide results suggesting that regulatory activity by the Pennsylvania Public Utilities Commission in the wake of the accident served to offset a majority of the increased systematic risk resulting from the accident. Our results imply that previously reported lingering effects of the accident at Three Mile Island may be regulatory effects from events predating the accident.
ERIC Educational Resources Information Center
Bailey, Anne Lowrey
1987-01-01
Giving patterns in the six years following a stock market drop in 1960 showed that giving actually went up during those years. However, in the case of very wealthy donors, they reduced large gifts to colleges. ( MLW)
NASA Astrophysics Data System (ADS)
Pajor, A.
2006-11-01
In the paper we compare the modelling ability of discrete-time multivariate Stochastic Volatility (SV) models to describe the conditional correlations between stock index returns. We consider four tri-variate SV models, which differ in the structure of the conditional covariance matrix. Specifications with zero, constant and time-varying conditional correlations are taken into account. As an example we study tri-variate volatility models for the daily log returns on the WIG, S&P 500, and FTSE 100 indexes. In order to formally compare the relative explanatory power of SV specifications we use the Bayesian principles of comparing statistic models. Our results are based on the Bayes factors and implemented through Markov Chain Monte Carlo techniques. The results indicate that the most adequate specifications are those that allow for time-varying conditional correlations and that have as many latent processes as there are conditional variances and covariances. The empirical results clearly show that the data strongly reject the assumption of constant conditional correlations.
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.
A wavelet analysis of scaling laws and long-memory in stock market volatility
NASA Astrophysics Data System (ADS)
Vuorenmaa, Tommi A.
2005-05-01
This paper studies the time-varying behavior of scaling laws and long-memory. This is motivated by the earlier finding that in the FX markets a single scaling factor might not always be sufficient across all relevant timescales: a different region may exist for intradaily time-scales and for larger time-scales. In specific, this paper investigates (i) if different scaling regions appear in stock market as well, (ii) if the scaling factor systematically differs from the Brownian, (iii) if the scaling factor is constant in time, and (iv) if the behavior can be explained by the heterogenuity of the players in the market and/or by intraday volatility periodicity. Wavelet method is used because it delivers a multiresolution decomposition and has excellent local adaptiviness properties. As a consequence, a wavelet-based OLS method allows for consistent estimation of long-memory. Thus issues (i)-(iv) shed light on the magnitude and behavior of a long-memory parameter, as well. The data are the 5-minute volatility series of Nokia Oyj at the Helsinki Stock Exchange around the burst of the IT-bubble. Period one represents the era of "irrational exuberance" and another the time after it. The results show that different scaling regions (i.e. multiscaling) may appear in the stock markets and not only in the FX markets, the scaling factor and the long-memory parameter are systematically different from the Brownian and they do not have to be constant in time, and that the behavior can be explained for a significant part by an intraday volatility periodicity called the New York effect. This effect was magnified by the frenzy trading of short-term speculators in the bubble period. The found stronger long-memory is also attributable to irrational exuberance.
Code of Federal Regulations, 2014 CFR
2014-04-01
... Exempted from Registration § 240.12a-7 Exemption of stock contained in standardized market baskets from section 12(a) of the Act. (a) Any component stock of a standardized market basket shall be exempt from the... 17 Commodity and Securities Exchanges 4 2014-04-01 2014-04-01 false Exemption of stock...
Code of Federal Regulations, 2012 CFR
2012-04-01
... Exempted from Registration § 240.12a-7 Exemption of stock contained in standardized market baskets from section 12(a) of the Act. (a) Any component stock of a standardized market basket shall be exempt from the... 17 Commodity and Securities Exchanges 3 2012-04-01 2012-04-01 false Exemption of stock...
Code of Federal Regulations, 2011 CFR
2011-04-01
... Exempted from Registration § 240.12a-7 Exemption of stock contained in standardized market baskets from section 12(a) of the Act. (a) Any component stock of a standardized market basket shall be exempt from the... 17 Commodity and Securities Exchanges 3 2011-04-01 2011-04-01 false Exemption of stock...
Do stock prices drive people crazy?
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. PMID:24526705
Financial factor influence on scaling and memory of trading volume in stock market.
Li, Wei; Wang, Fengzhong; Havlin, Shlomo; Stanley, H Eugene
2011-10-01
We study the daily trading volume volatility of 17,197 stocks in the US stock markets during the period 1989-2008 and analyze the time return intervals τ between volume volatilities above a given threshold q. For different thresholds q, the probability density function P(q)(τ) scales with mean interval 〈τ〉 as P(q)(τ)=〈τ〉(-1)f(τ/〈τ〉), and the tails of the scaling function can be well approximated by a power law f(x)∼x(-γ). We also study the relation between the form of the distribution function P(q)(τ) and several financial factors: stock lifetime, market capitalization, volume, and trading value. We find a systematic tendency of P(q)(τ) associated with these factors, suggesting a multiscaling feature in the volume return intervals. We analyze the conditional probability P(q)(τ|τ(0)) for τ following a certain interval τ(0), and find that P(q)(τ|τ(0)) depends on τ(0) such that immediately following a short (long) return interval a second short (long) return interval tends to occur. We also find indications that there is a long-term correlation in the daily volume volatility. We compare our results to those found earlier for price volatility. PMID:22181232
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.
Financial factor influence on scaling and memory of trading volume in stock market
NASA Astrophysics Data System (ADS)
Li, Wei; Wang, Fengzhong; Havlin, Shlomo; Stanley, H. Eugene
2011-10-01
We study the daily trading volume volatility of 17 197 stocks in the US stock markets during the period 1989-2008 and analyze the time return intervals τ between volume volatilities above a given threshold q. For different thresholds q, the probability density function Pq(τ) scales with mean interval <τ> as Pq(τ)=<τ>-1f(τ/<τ>), and the tails of the scaling function can be well approximated by a power law f(x)˜x-γ. We also study the relation between the form of the distribution function Pq(τ) and several financial factors: stock lifetime, market capitalization, volume, and trading value. We find a systematic tendency of Pq(τ) associated with these factors, suggesting a multiscaling feature in the volume return intervals. We analyze the conditional probability Pq(τ|τ0) for τ following a certain interval τ0, and find that Pq(τ|τ0) depends on τ0 such that immediately following a short (long) return interval a second short (long) return interval tends to occur. We also find indications that there is a long-term correlation in the daily volume volatility. We compare our results to those found earlier for price volatility.
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.
Recession Depression: Mental Health Effects of the 2008 Stock Market Crash*
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
Correlation of coming limit price with order book in stock markets
NASA Astrophysics Data System (ADS)
Maskawa, Jun-ichi
2007-09-01
We examine the correlation of the limit price with the order book, when a limit order comes. We analyzed the Rebuild Order Book of Stock Exchange Electronic Trading Service, which is the centralized order book market of London Stock Exchange. As a result, the limit price is broadly distributed around the best price according to a power-law, and it is not randomly drawn from the distribution, but has a strong correlation with the size of cumulative unexecuted limit orders on the price. It was also found that the limit price, on the coarse-grained price scale, tends to gather around the price which has a large size of cumulative unexecuted limit orders.
Recession depression: mental health effects of the 2008 stock market crash.
McInerney, Melissa; Mellor, Jennifer M; Nicholas, Lauren Hersch
2013-12-01
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
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.
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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…
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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.
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). PMID:18701221
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.
Self-Organized Criticality and Stock Market Dynamics: an Empirical Study
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.
Self-organized criticality and stock market dynamics: an empirical study
NASA Astrophysics Data System (ADS)
Bartolozzi, M.; Leinweber, D. B.; Thomas, A. W.
2005-05-01
The stock market is a complex self-interacting system, characterized by intermittent behaviour. Periods of high activity alternate with periods of relative calm. In the present work we investigate empirically 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 found in sandpile models, from quiescent. A statistical analysis of the filtered data shows a power law behaviour 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 behaviour.
Effects of daylight-saving time changes on stock market volatility: a comment.
Kamstra, Mark J; Kramer, Lisa A; Levi, Maurice D
2010-12-01
In a recent article in this journal, Berument, Dogan, and Onar (2010) challenged the existence of the previously documented daylight-saving effect. Kamstra, Kramer, and Levi's original finding (2000) was that average stock market returns on Mondays following time changes are economically and statistically significantly lower than typical Monday returns. Kamstra, et al. hypothesized that the effect may arise due to heightened anxiety or risk aversion on the part of market participants after they experience a 1-hr. disruption in their sleep habits, in accordance with prior findings in the psychology literature linking sleep desynchronosis with anxiety. Berument, et al. replicated the original findings using ordinary least squares estimation, but when they modeled the mean of returns using a method prone to producing biased estimates, they obtained puzzling results. The analysis here, based on standard, unbiased modeling techniques, shows that the daylight-saving effect remains intact in the U.S. PMID:21323146
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.
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.
Fundamental factors versus herding in the 2000 2005 US stock market and prediction
NASA Astrophysics Data System (ADS)
Zhou, Wei-Xing; Sornette, Didier
2006-02-01
We present a general methodology to incorporate fundamental economic factors to the theory of herding developed in our group to describe bubbles and antibubbles. We start from the strong form of rational expectation and derive the general method to incorporate factors in addition to the log-periodic power law (LPPL) signature of herding developed in ours and others’ works. These factors include interest rate, interest spread, historical volatility, implied volatility and exchange rates. Standard statistical AIC and Wilks tests allow us to compare the explanatory power of the different proposed factor models. We find that the historical volatility played the key role before August of 2002. Around October 2002, the interest rate dominated. In the first six months of 2003, the foreign exchange rate became the key factor. Since the end of 2003, all factors have played an increasingly large role. However, the most surprising result is that the best model is the second-order LPPL without any factor. We thus present a scenario for the future evolution of the US stock market based on the extrapolation of the fit of the second-order LPPL formula, which suggests that herding is still the dominating force and that the unraveling of the US stock market antibubble since 2000 is still qualitatively similar to (but quantitatively different from) the Japanese Nikkei case after 1990.
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.
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.
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.
Evolution of worldwide stock markets, correlation structure, and correlation-based graphs.
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
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.
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.
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.
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.
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.
Code of Federal Regulations, 2013 CFR
2013-04-01
... quotations and other information relating to the penny stock market. 240.15g-3 Section 240.15g-3 Commodity... other information relating to the penny stock market. (a) Requirement. It shall be unlawful for a broker... CFR 240.10b-10 of this chapter. (2) A broker or dealer, at the time of making the disclosure...
Code of Federal Regulations, 2010 CFR
2010-04-01
... quotations and other information relating to the penny stock market. 240.15g-3 Section 240.15g-3 Commodity... other information relating to the penny stock market. (a) Requirement. It shall be unlawful for a broker... CFR 240.10b-10 of this chapter. (2) A broker or dealer, at the time of making the disclosure...
Code of Federal Regulations, 2012 CFR
2012-04-01
... quotations and other information relating to the penny stock market. 240.15g-3 Section 240.15g-3 Commodity... other information relating to the penny stock market. (a) Requirement. It shall be unlawful for a broker... CFR 240.10b-10 of this chapter. (2) A broker or dealer, at the time of making the disclosure...
Code of Federal Regulations, 2011 CFR
2011-04-01
... quotations and other information relating to the penny stock market. 240.15g-3 Section 240.15g-3 Commodity... other information relating to the penny stock market. (a) Requirement. It shall be unlawful for a broker... CFR 240.10b-10 of this chapter. (2) A broker or dealer, at the time of making the disclosure...
Code of Federal Regulations, 2014 CFR
2014-04-01
... quotations and other information relating to the penny stock market. 240.15g-3 Section 240.15g-3 Commodity... other information relating to the penny stock market. (a) Requirement. It shall be unlawful for a broker... CFR 240.10b-10 of this chapter. (2) A broker or dealer, at the time of making the disclosure...
Multifractal properties of price change and volume change of stock market indices
NASA Astrophysics Data System (ADS)
Stošić, Dusan; Stošić, Darko; Stošić, Tatijana; Eugene Stanley, H.
2015-06-01
We study auto-correlations and cross-correlations of daily price changes and daily volume changes of thirteen global stock market indices, using multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DXA). We find rather distinct multifractal behavior of price and volume changes. Our results indicate that the time series of price changes are more complex than those of volume changes, and that large fluctuations dominate multifractal behavior of price changes, while small fluctuations dominate multifractal behavior of volume changes. We also find that there is an absence of correlations in price changes, there are anti-persistent long-term correlations in volume changes, and there are anti-persistent long-term cross-correlations between price and volume changes. Shuffling the series reveals that multifractality of both price changes and volume changes arises from a broad probability density function.
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.
Intra-day variability of the stock market activity versus stationarity of the financial time series
NASA Astrophysics Data System (ADS)
Gubiec, T.; Wiliński, M.
2015-08-01
In this paper we propose a new approach to a well-known phenomena of intra-day activity pattern on the stock market. We suggest that seasonality of inter-transaction times has a more significant impact than intra-day pattern of volatility. Our aim is not to remove the intra-day pattern from the data but to describe its impact on autocorrelation function estimators. We obtain an exact, analytical formula relating estimators of the autocorrelation functions of non-stationary (seasonal) process to its stationary counterpart. Hence, we prove that the day seasonality of inter-transaction times extends the memory of the process. That is, autocorrelation of both, price returns and their absolute values, relaxation to zero is longer.
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.
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