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Sample records for stock market index

  1. 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)

  2. Stock market index prediction using neural networks

    NASA Astrophysics Data System (ADS)

    Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

    1994-03-01

    A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

  3. Portfolio optimization for index tracking modelling in Malaysia stock market

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  4. Power tails of index distributions in chinese stock market

    NASA Astrophysics Data System (ADS)

    Zhang, J. W.; Zhang, Y.; Kleinert, H.

    2007-04-01

    The power α of the Lévy tails of stock market fluctuations discovered in recent years are generally believed to be universal. We show that for the Chinese stock market this is not true, the powers depending strongly on anomalous daily index changes short before market closure, and weakly on the opening data.

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

    2015-01-01

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

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

    PubMed

    Qiu, Mingyue; Song, Yu

    2016-01-01

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

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

    PubMed Central

    Qiu, Mingyue; Song, Yu

    2016-01-01

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

  9. 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.

  10. Effects of Intraday Patterns on Analysis of STOCK Market Index and Trading Volume

    NASA Astrophysics Data System (ADS)

    Choi, Hyung Wooc; Maeng, Seong Eun; Lee, Jae Woo

    We review the stylized properties of the stock market and consider effects of the intraday patterns on the analysis of the time series for the stock index and the trading volume in Korean stock market. In the stock market the probability distribution function (pdf) of the return and volatility followed the power law for the stock index and the change of the volume traded. The volatility of the stock index showed the long-time memory and the autocorrelation function followed a power law. We applied two eliminating methods of the intraday patterns: the intraday patterns of the time series itself, and the intraday patterns of the absolute return for the index or the absolute volume change. We scaled the index and return by two types of the intraday patterns. We considered the probability distribution function and the autocorrelation function (ACF) for the time series scaled by the intraday patterns. The cumulative probability distribution function of the returns scaled by the intraday patterns showed a power law, P>(r) r-α±, where α± corresponds to the exponent of the positive and negative fat tails. The pdf of the return scaled by intraday patterns by the absolute return decayed much steeper than that of the return scaled by intraday patterns of the index itself. The pdf for the volume change also followed the power law for both methods of eliminating intraday patterns. However, the exponents of the power law at fat tails do not depend on the intraday patterns. The ACF of the absolute return showed long-time correlation and followed the power law for the scaled index and for the scaled volume. The daily periodicity of the ACF was removed for scaled time series by the intraday patterns of the absolute return or the absolute volume change.

  11. Microscopic spin model for the dynamics of the return distribution of the Korean stock market index

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

    In this paper, we studied the dynamics of the log-return distribution of the Korean Composition Stock Price Index (KOSPI) from 1992 to 2004. Based on the microscopic spin model, we found that while the index during the late 1990s showed a power-law distribution, the distribution in the early 2000s was exponential. This change in distribution shape was caused by the duration and velocity, among other parameters, of the information that flowed into the market.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  13. Distribution characteristics of stock market liquidity

    NASA Astrophysics Data System (ADS)

    Luo, Jiawen; Chen, Langnan; Liu, Hao

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki

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

  15. Stock Market Index Data and indicators for Day Trading as a Binary Classification problem.

    PubMed

    Bruni, Renato

    2017-02-01

    Classification is the attribution of labels to records according to a criterion automatically learned from a training set of labeled records. This task is needed in a huge number of practical applications, and consequently it has been studied intensively and several classification algorithms are available today. In finance, a stock market index is a measurement of value of a section of the stock market. It is often used to describe the aggregate trend of a market. One basic financial issue would be forecasting this trend. Clearly, such a stochastic value is very difficult to predict. However, technical analysis is a security analysis methodology developed to forecast the direction of prices through the study of past market data. Day trading consists in buying and selling financial instruments within the same trading day. In this case, one interesting problem is the automatic individuation of favorable days for trading. We model this problem as a binary classification problem, and we provide datasets containing daily index values, the corresponding values of a selection of technical indicators, and the class label, which is 1 if the subsequent time period is favorable for day trading and 0 otherwise. These datasets can be used to test the behavior of different approaches in solving the day trading problem.

  16. Is there any connection between the network morphology and the fluctuations of the stock market index?

    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.

  17. Optimization of investment portfolio weight of stocks affected by market index

    NASA Astrophysics Data System (ADS)

    Azizah, E.; Rusyaman, E.; Supian, S.

    2017-01-01

    Stock price assessment, selection of optimum combination, and measure the risk of a portfolio investment is one important issue for investors. In this paper single index model used for the assessment of the stock price, and formulation optimization model developed using Lagrange multiplier technique to determine the proportion of assets to be invested. The level of risk is estimated by using variance. These models are used to analyse the stock price data Lippo Bank and Bumi Putera.

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

    NASA Astrophysics Data System (ADS)

    Gu, Rongbao; Shao, Yanmin

    2016-07-01

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

  19. Stock Market Project.

    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…

  20. 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.

  1. A Stock Market Project.

    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)

  2. LETTER: Synchronization model for stock market asymmetry

    NASA Astrophysics Data System (ADS)

    Donangelo, Raul; Jensen, Mogens H.; Simonsen, Ingve; Sneppen, Kim

    2006-11-01

    The waiting time needed for a stock market index to undergo a given percentage change in its value is found to have an up down asymmetry, which, surprisingly, is not observed for the individual stocks composing that index. To explain this, we introduce a market model consisting of randomly fluctuating stocks that occasionally synchronize their short term draw-downs. These synchronous events are parametrized by a 'fear factor', that reflects the occurrence of dramatic external events which affect the financial market.

  3. 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.

  4. Stock market dynamics: Before and after stock market crashes

    NASA Astrophysics Data System (ADS)

    Siokis, Fotios M.

    2012-02-01

    This paper presents a brief analysis on the distribution of magnitude of major stock market shocks. Based on the Gutenberg-Richter law in geophysics, we model the dynamics of market index returns prior and after major crashes in search of statistical regularities. For a large number of market crashes, our analysis suggests that the distribution of market volatility before and after the stock market crash is described well by the Gutenberg-Richter law, which reflects the scale-invariance and self-similarity of the underlying dynamics by a robust power-law relation. In addition, the rate of the decay of the aftershock sequence is well described by another power law, which is known as the Omori law. Power law relaxation seems to be a common behavior observed in complex systems such as the financial markets.

  5. Multifractality in stock indexes: Fact or Fiction?

    NASA Astrophysics Data System (ADS)

    Jiang, Zhi-Qiang; Zhou, Wei-Xing

    2008-06-01

    Multifractal analysis and extensive statistical tests are performed upon intraday minutely data within individual trading days for four stock market indexes (including HSI, SZSC, S&P 500, and NASDAQ) to check whether the indexes (instead of the returns) possess multifractality. We find that the mass exponent τ(q) is linear and the singularity α(q) is close to 1 for all trading days and all indexes. Furthermore, we find strong evidence showing that the scaling behaviors of the original data sets cannot be distinguished from those of shuffled time series. Hence, the so-called multifractality in the intraday stock market indexes is merely an illusion.

  6. Stock Market Savvy.

    ERIC Educational Resources Information Center

    Okula, Susan

    2003-01-01

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

  7. Causalities of the Taiwan stock market

    NASA Astrophysics Data System (ADS)

    Ting, Julian Juhi-Lian

    2003-06-01

    Volatility, fitting with first-order Landau expansion, stationarity, and causality of the Taiwan stock market (TAIEX) are investigated based on daily records. Instead of consensuses that consider stock market index change as a random time series we propose the market change as a dual time series consists of the index and the corresponding volume. Therefore, causalities between these two time series are investigated. Our results suggest the volume time series is of second-order importance than the index time series. The index time series receives slightly stronger influence from the previous 67th trading day, while the volume time series is slightly stronger influenced by the previous 62nd trading day.

  8. 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.

  9. Autoregressive processes with exponentially decaying probability distribution functions: applications to daily variations of a stock market index.

    PubMed

    Porto, Markus; Roman, H Eduardo

    2002-04-01

    We consider autoregressive conditional heteroskedasticity (ARCH) processes in which the variance sigma(2)(y) depends linearly on the absolute value of the random variable y as sigma(2)(y) = a+b absolute value of y. While for the standard model, where sigma(2)(y) = a + b y(2), the corresponding probability distribution function (PDF) P(y) decays as a power law for absolute value of y-->infinity, in the linear case it decays exponentially as P(y) approximately exp(-alpha absolute value of y), with alpha = 2/b. We extend these results to the more general case sigma(2)(y) = a+b absolute value of y(q), with 0 < q < 2. We find stretched exponential decay for 1 < q < 2 and stretched Gaussian behavior for 0 < q < 1. As an application, we consider the case q=1 as our starting scheme for modeling the PDF of daily (logarithmic) variations in the Dow Jones stock 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 beta = 2/3, in a much better agreement with the empirical data.

  10. 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.

  11. Is the efficiency of stock market correlated with multifractality? An evidence from the Shanghai stock market

    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].

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  14. Do Earthquakes Shake Stock Markets?

    PubMed

    Ferreira, Susana; Karali, Berna

    2015-01-01

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

  15. Do Earthquakes Shake Stock Markets?

    PubMed Central

    2015-01-01

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

  16. 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.

  17. Gain loss asymmetry for emerging stock markets

    NASA Astrophysics Data System (ADS)

    Karpio, Krzysztof; Załuska–Kotur, Magdalena A.; Orłowski, 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.

  18. 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.

  19. A wave function for stock market returns

    NASA Astrophysics Data System (ADS)

    Ataullah, Ali; Davidson, Ian; Tippett, Mark

    2009-02-01

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

  20. 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.

  1. Universal Fluctuations of the S&100 Stock Index Returns

    NASA Astrophysics Data System (ADS)

    Gonçalves, Rui; Pinto, Alberto

    2009-09-01

    We analyze the constituents stocks of the well known Standard & Poor's 100 index (S&P100) that are traded in the NYSE and NASDAQ markets. We observe the data collapse of the histogram of the S&P100 index fluctuations to the universal non-parametric Bramwell-Holdsworth-Pinton (BHP) distribution. Since the BHP probability density function appears in several other dissimilar phenomena, our result reveals an universal feature of the stock exchange markets.

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Gu, Rongbao; Xiong, Wei; Li, Xinjie

    2015-12-01

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

  4. Asymmetric joint multifractal analysis in Chinese stock markets

    NASA Astrophysics Data System (ADS)

    Chen, Yuwen; Zheng, Tingting

    2017-04-01

    In this paper, the asymmetric joint multifractal analysis method based on statistical physics is proposed to explore the asymmetric correlation between daily returns and trading volumes in Chinese stock markets. The result shows asymmetric multifractal correlations exist between return and trading volume in Chinese stock markets. Moreover, when the stock indexes are upward, the fluctuations of returns are always weaker than when they are downward, whether the trading volumes are more or less.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  6. 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.

  7. Evidence of multi-affinity in the Japanese stock market

    NASA Astrophysics Data System (ADS)

    Katsuragi, Hiroaki

    2000-04-01

    Fluctuations of the Japanese stock market (Tokyo Stock Price Index: TOPIX) are analyzed using a multi-affine analysis method. In the research to date, only some simulated self-affine models have shown multi-affinity. In most experiments using observations of self-affine fractal profiles, multi-affinity has not been found. However, we find evidence of multi-affinity in fluctuations of the Japanese stock market (TOPIX). The qth-order Hurst exponent Hq varies with changes in q. This multi-affinity indicates that there are plural mechanisms that affect the same time scale as stock market price fluctuation dynamics.

  8. 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)

  9. Autoregressive processes with anomalous scaling behavior: applications to high-frequency variations of a stock market index.

    PubMed

    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.

  10. Stock or stroke? Stock market movement and stroke incidence in Taiwan.

    PubMed

    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.

  11. 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.

  12. Taxonomy of stock market indices

    PubMed

    Bonanno; Vandewalle; Mantegna

    2000-12-01

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

  13. 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.

  14. Stock Market Expectations of Dutch Households

    PubMed Central

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

    2013-01-01

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

  15. Stock Market Expectations of Dutch Households.

    PubMed

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

    2011-04-01

    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.

  16. 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.

  17. 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.

  18. 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.

  19. 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)

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

    PubMed

    Zhang, Huishu; Wei, Jianrong; Huang, Jiping

    2014-01-01

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

  1. 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)

  2. Does Stock Market Performance Influence Retirement Intentions?

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  3. Stock market stability: Diffusion entropy analysis

    NASA Astrophysics Data System (ADS)

    Li, Shouwei; Zhuang, Yangyang; He, Jianmin

    2016-05-01

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

  4. Recurrence quantification analysis of global stock markets

    NASA Astrophysics Data System (ADS)

    Bastos, João A.; Caiado, Jorge

    2011-04-01

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

  5. 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.

  6. Multifractal properties of Chinese stock market in Shanghai

    NASA Astrophysics Data System (ADS)

    Du, Guoxiong; Ning, Xuanxi

    2008-01-01

    In this article, we apply three methods of multifractal analysis, partition function method, singular spectrum method and multifractal detrended fluctuation analysis method, to analyze the closing index fluctuations of Shanghai stock market during the past seven years. We have found that Shanghai stock market has weak multifractal features and there are long-range power-law correlations between index series. The shapes of singular spectrums do not change with time scales and their strengths weaken when the scales shorten. But when the orders of partition function increase, the strengths of multifractal increase, the singular spectrums become rougher and the general Hurst exponents decrease. These results provide solid and important values for further study on the dynamic mechanism of stock market price fluctuation.

  7. A Tale of Two Stock Markets

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  8. 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.

  9. The long-term memory analysis of industrial indices of the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Yong, L.

    2008-02-01

    The main work of this paper is to apply the fractional market theory and time series analysis for analyzing various industrial indices of the Chinese stock market by rescaling range analysis. Hurst index and the long-term memory of price change in Chinese stock market are studied.

  10. 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.

  11. A causality between fund performance and stock market

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

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

    ERIC Educational Resources Information Center

    Draze, Dianne

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

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

    PubMed Central

    Cong, Rong-Gang; Shen, Shaochuan

    2013-01-01

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

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

    PubMed

    Cong, Rong-Gang; Shen, Shaochuan

    2013-01-01

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

  15. 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.

  16. 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.

  17. Quantifying the Behavior of Stock Correlations Under Market Stress

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2012-01-01

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

  19. 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…

  20. Quantifying Stock Return Distributions in Financial Markets

    PubMed Central

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

    2015-01-01

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

  1. Coupling detrended fluctuation analysis of Asian stock markets

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  2. Stock index dynamics worldwide: a comparative analysis

    NASA Astrophysics Data System (ADS)

    Cortines, A. A. G.; Anteneodo, C.; Riera, R.

    2008-09-01

    We perform a comparative analysis of twenty-four daily stock indices across the world, encompassing developed and emerging markets. We compute, directly from the return empirical time series, the Kramers-Moyal (KM) expansion coefficients that govern the evolution of the probability density function of returns throughout timelags. Our study discloses universal patterns of the KM coefficients, which can be described in terms of a few microscopic parameters. These parameters allow to quantify features such as deviations from Gaussianity or from efficiency, providing a tool to discriminate market dynamics.

  3. 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.

  4. Modeling and computing of stock index forecasting based on neural network and Markov chain.

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    Palágyi, Zoltán; Mantegna, Rosario N.

    1999-07-01

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

  6. 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)

  7. Economic Stress and Mental Health: The Relationship Between the Stock Market and Neurotic Disorder Doctor Visits.

    PubMed

    Chen, Chun-Chih; Lin, Ying-Tzu; Liu, Tsai-Ching; Chen, Chin-Shyan

    2016-12-01

    This paper investigates the relationship between the stock market and the neurotic disorder doctor visits. We use aggregate data, partition the population by age and gender and examine the impact of changes in the stock market on neurotic disorders. Using doctor visits as a proxy measure of morbidity, we find evidence of some relationship between neurotic disorder morbidity and stock market variations. A stock market falling in a single day and the accumulation of daily stock market drops are both associated with more neurotic disorder doctor visits. We also observe more neurotic disorder doctor visits during periods of a low stock index for the elderly, regardless of gender. Copyright © 2016 John Wiley & Sons, Ltd.

  8. 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.

  9. Dependence phenomenon analysis of the stock market

    NASA Astrophysics Data System (ADS)

    Cheng, Wuyang; Wang, Jun

    2013-04-01

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

  10. Group identification in Indonesian stock market

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  11. The effect of Malaysia general election on stock market returns.

    PubMed

    Liew, Venus Khim-Sen; Rowland, Racquel

    2016-01-01

    During the latest episode of general election held in Malaysia, it is observed that the FBMKLCI index was lifted 62.52 points in a day soon after the announcement of election outcome. Moreover, the index registered a highest gain of 96.29 points in the middle of the intra-day trade. This suggests that investors who had got the right direction could make profitable intra-day trading the next trading day of the general election date. Results from statistical analysis uncover significant before-election-effect and after-election-effect from the most recent general elections held in Malaysia. Different subsets of macroeconomic variables are found to have significant role on stock market return depending on the market situation. Remarkably, when there was close fight between the two major political parties during the 2008 and 2013 election years, political uncertainty showed up its negative and significant role in influencing the stock market return. The major implication of these findings is that while investors may seek abnormal returns before and after the next general election, which is around the corner, they will have to pay attention on the influence of macroeconomic variables and political uncertainty on stock market return during the election year.

  12. 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.

  13. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

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

  14. 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.

  15. How High Frequency Trading Affects a Market Index

    PubMed Central

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

    2013-01-01

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

  16. 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).

  17. STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS*

    PubMed Central

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

    2011-01-01

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

  18. STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS.

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2007-07-01

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

  20. 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.

  1. 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)

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

    PubMed

    Tharavanij, Piyapas; Siraprapasiri, Vasan; Rajchamaha, Kittichai

    2015-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets

    NASA Astrophysics Data System (ADS)

    Cao, Guangxi; Zhang, Minjia; Li, Qingchen

    2017-04-01

    This study focuses on multifractal detrended cross-correlation analysis of the different volatility intervals of Mainland China, US, and Hong Kong stock markets. A volatility-constrained multifractal detrended cross-correlation analysis (VC-MF-DCCA) method is proposed to study the volatility conductivity of Mainland China, US, and Hong Kong stock markets. Empirical results indicate that fluctuation may be related to important activities in real markets. The Hang Seng Index (HSI) stock market is more influential than the Shanghai Composite Index (SCI) stock market. Furthermore, the SCI stock market is more influential than the Dow Jones Industrial Average stock market. The conductivity between the HSI and SCI stock markets is the strongest. HSI was the most influential market in the large fluctuation interval of 1991 to 2014. The autoregressive fractionally integrated moving average method is used to verify the validity of VC-MF-DCCA. Results show that VC-MF-DCCA is effective.

  8. Fluctuations of trading volume in a stock market

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

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

  9. Statistical pairwise interaction model of stock market

    NASA Astrophysics Data System (ADS)

    Bury, Thomas

    2013-03-01

    Financial markets are a classical example of complex systems as they are compound by many interacting stocks. As such, we can obtain a surprisingly good description of their structure by making the rough simplification of binary daily returns. Spin glass models have been applied and gave some valuable results but at the price of restrictive assumptions on the market dynamics or they are agent-based models with rules designed in order to recover some empirical behaviors. Here we show that the pairwise model is actually a statistically consistent model with the observed first and second moments of the stocks orientation without making such restrictive assumptions. This is done with an approach only based on empirical data of price returns. Our data analysis of six major indices suggests that the actual interaction structure may be thought as an Ising model on a complex network with interaction strengths scaling as the inverse of the system size. This has potentially important implications since many properties of such a model are already known and some techniques of the spin glass theory can be straightforwardly applied. Typical behaviors, as multiple equilibria or metastable states, different characteristic time scales, spatial patterns, order-disorder, could find an explanation in this picture.

  10. 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.

  11. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... marketable stock means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as... (3) Options on stock that is described in paragraph (a)(1) or (2) of this section, to the extent... days remaining in the quarter in which the offering occurs, or 5 days. (3) Anti-abuse rule. Trades...

  12. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... marketable stock means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as... (3) Options on stock that is described in paragraph (a)(1) or (2) of this section, to the extent... days remaining in the quarter in which the offering occurs, or 5 days. (3) Anti-abuse rule. Trades...

  13. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... marketable stock means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as... (3) Options on stock that is described in paragraph (a)(1) or (2) of this section, to the extent... days remaining in the quarter in which the offering occurs, or 5 days. (3) Anti-abuse rule. Trades...

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

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... marketable stock means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as... (3) Options on stock that is described in paragraph (a)(1) or (2) of this section, to the extent... days remaining in the quarter in which the offering occurs, or 5 days. (3) Anti-abuse rule. Trades...

  15. 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)

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

    PubMed Central

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

    2016-01-01

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

  17. 75 FR 16221 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    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...

  18. 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.

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

    PubMed

    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.

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

    PubMed

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

    2017-01-01

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

  1. 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)

  2. 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.

  3. 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.

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

    PubMed Central

    Borysov, Stanislav S.; Balatsky, Alexander V.

    2014-01-01

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

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

    PubMed

    Borysov, Stanislav S; Balatsky, Alexander V

    2014-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  8. 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.

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed

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

    2011-01-01

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

  11. 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.

  12. 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.

  13. Financial earthquakes, aftershocks and scaling in emerging stock markets

    NASA Astrophysics Data System (ADS)

    Selçuk, Faruk

    2004-02-01

    This paper provides evidence for scaling laws in emerging stock markets. Estimated parameters using different definitions of volatility show that the empirical scaling law in every stock market is a power law. This power law holds from 2 to 240 business days (almost 1 year). The scaling parameter in these economies changes after a change in the definition of volatility. This finding indicates that the stock returns may have a multifractal nature. Another scaling property of stock returns is examined by relating the time after a main shock to the number of aftershocks per unit time. The empirical findings show that after a major fall in the stock returns, the stock market volatility above a certain threshold shows a power law decay, described by Omori's law.

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed Central

    Dai, Yonghui; Han, Dongmei; Dai, Weihui

    2014-01-01

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

  16. 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.

  17. Asymmetric responses of international stock markets to trading volume

    NASA Astrophysics Data System (ADS)

    Gerlach, Richard; Chen, Cathy W. S.; Lin, Doris S. Y.; Huang, Ming-Hsiang

    2006-02-01

    The major goal of this paper is to examine the hypothesis that stock returns and return volatility are asymmetric, threshold nonlinear, functions of change in trading volume. A minor goal is to examine whether return spillover effects also display such asymmetry. Employing a double-threshold GARCH model with trading volume as a threshold variable, we find strong evidence supporting this hypothesis in five international market return series. Asymmetric causality tests lend further support to our trading volume threshold model and conclusions. Specifically, an increase in volume is positively associated, while decreasing volume is negatively associated, with the major price index in four of the five markets. The volatility of each series also displays an asymmetric reaction, four of the markets display higher volatility following increases in trading volume. Using posterior odds ratio, the proposed threshold model is strongly favored in three of the five markets, compared to a US news double threshold GARCH model and a symmetric GARCH model. We also find significant nonlinear asymmetric return spillover effects from the US market.

  18. 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.

  19. Stochastic cellular automata model for stock market dynamics.

    PubMed

    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.

  20. 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.

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

    PubMed Central

    Qiao, Haishu; Xia, Yue; Li, Ying

    2016-01-01

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

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

    PubMed

    Qiao, Haishu; Xia, Yue; Li, Ying

    2016-01-01

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

  3. 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.

  4. 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

  5. Statistical properties of stock market indices of different economies

    NASA Astrophysics Data System (ADS)

    Lan, Boon Leong; Tan, Ying Oon

    2007-03-01

    Daily changes in the logarithm of stock market index from 1997 to 2004 are analyzed for countries from three subgroups of economies classified by the International Monetary Fund (IMF): developing Asian countries, newly industrialized Asian economies and major advanced economies. For all markets, the daily changes are well fitted by a non-Gaussian stable probability density. The time evolution of the standard deviation of the daily changes for each market obeys a power law. However, the developing Asian countries have the smallest stable density characteristic parameters α and the largest exponents b of the power law, except China's SSEC and India's SENSEX. The values of α and b for these two markets are closer to those of the newly industrialized Asian economies; in particular, those for China's SSEC are close to those for Hong Kong's HSI. The values of α and b for the newly industrialized Asian economies are in between those for the developing Asian countries and major advanced economies, consistent with the results for generalized Hurst exponent [Physica A 324 (2003) 183]. The daily changes for the developing Asian countries and newly industrialized Asian economies have a weak long-range correlation, whereas the daily changes for the major advanced economies have a weak long-range anti-correlation.

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

    ERIC Educational Resources Information Center

    National Council on Economic Education, New York, NY.

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

  7. 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.)

  8. 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)

  9. What the 2008 stock market crash means for retirement security.

    PubMed

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

    2010-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Výrost, Tomáš; Lyócsa, Štefan; Baumöhl, Eduard

    2015-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-09-01

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

  12. Dependence values of Asia-Pacific stock markets

    NASA Astrophysics Data System (ADS)

    Razak, Ruzanna Ab; Ismail, Noriszura

    2014-06-01

    Return series of stock markets tend to have leptokurtic distribution thus making linear correlation an inappropriate measure of dependence. Copula theory can be used as an alternative to show the dependencies between return series. In this paper, we study the dependence structure of extreme returns between several Asia-Pacific stock markets by applying the Copula based marginal GARCH approach. The results of our study are discussed in this paper.

  13. Effects of daylight savings time changes on stock market volatility.

    PubMed

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

    2010-04-01

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

  14. 75 FR 28839 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-05-24

    ... 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 of a Proposed Rule Change To Establish a Trading Pause for Individual Stocks Contained in the Standard & Poor's 500 Index That Experience a Price Change of 10%...

  15. Statistical Properties of Stock Market Eigensignals

    NASA Astrophysics Data System (ADS)

    Kwapien, J.; Drożdż, S.; Oświecimka, P.

    2005-08-01

    By using the correlation matrix approach, we decompose the evolution of a set of the 100 largest American companies into the components (portfolios) defined by the eigenvectors of the correlation matrix. Among the results, we show that a number of the non-random components exceeds the previous estimates based on much shorter time series of daily returns. This indicates that for short signals the bulk of random eigenvalues defined by Random Matrix Theory can comprise also a significant amount of information. We also show that the components corresponding to a few largest eigenvalues and describing the most collective part of the market evolution reveal strong nonlinear correlation structure in contrast to the other components. All the components are multifractal. Moreover, by using a modified definition of the correlation matrix, we are able to decompose the daily pattern of the German DAX30 index into components which can characterize the recurrent events occurring at precise moments of a trading day.

  16. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2007-08-01

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

  19. 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

  20. 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.

  1. 17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 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 Exchanges... Section 15(d) of the Act § 240.15g-2 Penny stock disclosure document relating to the penny stock...

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

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 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 Exchanges... Section 15(d) of the Act § 240.15g-2 Penny stock disclosure document relating to the penny stock...

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

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 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 Exchanges... Section 15(d) of the Act § 240.15g-2 Penny stock disclosure document relating to the penny stock...

  4. 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... Section 15(d) of the Act § 240.15g-2 Penny stock disclosure document relating to the penny stock...

  5. 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.

  6. Asymmetric MF-DCCA method based on risk conduction and its application in the Chinese and foreign stock markets

    NASA Astrophysics Data System (ADS)

    Cao, Guangxi; Han, Yan; Li, Qingchen; Xu, Wei

    2017-02-01

    The acceleration of economic globalization gradually shows the linkage of the stock markets in various counties and produces a risk conduction effect. An asymmetric MF-DCCA method is conducted based on the different directions of risk conduction (DMF-ADCCA) and by using the traditional MF-DCCA. To ensure that the empirical results are more objective and robust, this study selects the stock index data of China, the US, Germany, India, and Brazil from January 2011 to September 2014 using the asymmetric MF-DCCA method based on different risk conduction effects and nonlinear Granger causality tests to study the asymmetric cross-correlation between domestic and foreign stock markets. Empirical results indicate the existence of a bidirectional conduction effect between domestic and foreign stock markets, and the greater influence degree from foreign countries to domestic market compared with that from the domestic market to foreign countries.

  7. The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH-BEKK model

    NASA Astrophysics Data System (ADS)

    Liu, Xueyong; An, Haizhong; Huang, Shupei; Wen, Shaobo

    2017-01-01

    Aiming to investigate the evolution of mean and volatility spillovers between oil and stock markets in the time and frequency dimensions, we employed WTI crude oil prices, the S&P 500 (USA) index and the MICEX index (Russia) for the period Jan. 2003-Dec. 2014 as sample data. We first applied a wavelet-based GARCH-BEKK method to examine the spillover features in frequency dimension. To consider the evolution of spillover effects in time dimension at multiple-scales, we then divided the full sample period into three sub-periods, pre-crisis period, crisis period, and post-crisis period. The results indicate that spillover effects vary across wavelet scales in terms of strength and direction. By analysis the time-varying linkage, we found the different evolution features of spillover effects between the Oil-US stock market and Oil-Russia stock market. The spillover relationship between oil and US stock market is shifting to short-term while the spillover relationship between oil and Russia stock market is changing to all time scales. That result implies that the linkage between oil and US stock market is weakening in the long-term, and the linkage between oil and Russia stock market is getting close in all time scales. This may explain the phenomenon that the US stock index and the Russia stock index showed the opposite trend with the falling of oil price in the post-crisis period.

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

    NASA Astrophysics Data System (ADS)

    Güloğlu, Bülent; Kaya, Pınar; Aydemir, Resul

    2016-11-01

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

  9. Fractal Profit Landscape of the Stock Market

    PubMed Central

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

    2012-01-01

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

  10. Fractal profit landscape of the stock market.

    PubMed

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

    2012-01-01

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

  11. A quantum anharmonic oscillator model for the stock market

    NASA Astrophysics Data System (ADS)

    Gao, Tingting; Chen, Yu

    2017-02-01

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

  12. Principle Fluctuation Modes of the Global Stock Market

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-08-12

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

  15. Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market

    NASA Astrophysics Data System (ADS)

    Guo, Kun; Sun, Yi; Qian, Xin

    2017-03-01

    With the development of the social network, the interaction between investors in stock market became more fast and convenient. Thus, investor sentiment which can influence their investment decisions may be quickly spread and magnified through the network, and to a certain extent the stock market can be affected. This paper collected the user comments data from a popular professional social networking site of China stock market called Xueqiu, then the investor sentiment data can be obtained through semantic analysis. The dynamic analysis on relationship between investor sentiment and stock market is proposed based on Thermal Optimal Path (TOP) method. The results show that the sentiment data was not always leading over stock market price, and it can be used to predict the stock price only when the stock has high investor attention.

  16. 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.

  17. Quantifying Wikipedia Usage Patterns Before Stock Market Moves

    PubMed Central

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

    2013-01-01

    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.

  18. 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.

  19. 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.

  20. 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

  1. 77 FR 47455 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-08

    ... change is available on the Exchange's Web site at http://www.nasdaq.cchwallstreet.com , at the principal... Understandings with various stock exchanges. Given the capitalization of these indexes and the deep and liquid... deep and liquid markets for the securities underlying both the MSCI EM Index and the MSCI EAFE...

  2. 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.

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

    PubMed

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

    2015-10-01

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

  4. 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.

  5. 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.

  6. Self-organized percolation model for stock market fluctuations

    NASA Astrophysics Data System (ADS)

    Stauffer, Dietrich; Sornette, Didier

    1999-09-01

    In the Cont-Bouchaud model [cond-mat /9712318] of stock markets, percolation clusters act as buying or selling investors and their statistics controls that of the price variations. Rather than fixing the concentration controlling each cluster connectivity artificially at or close to the critical value, we propose that clusters shatter and aggregate continuously as the concentration evolves randomly, reflecting the incessant time evolution of groups of opinions and market moods. By the mechanism of “sweeping of an instability” [Sornette, J. Phys. I 4, 209(1994)], this market model spontaneously exhibits reasonable power-law statistics for the distribution of price changes and accounts for the other important stylized facts of stock market price fluctuations.

  7. Multiscale multifractal time irreversibility analysis of stock markets

    NASA Astrophysics Data System (ADS)

    Jiang, Chenguang; Shang, Pengjian; Shi, Wenbin

    2016-11-01

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

  8. Testing for persistent deviations of stock prices to dividends in the Nasdaq index

    NASA Astrophysics Data System (ADS)

    Cuñado, J.; Gil-Alana, L. A.; Perez de Gracia, F.

    2012-10-01

    In this paper we test for the presence of bubbles in the Nasdaq stock market index over the period 1994-2003 applying fractional integration techniques and allowing for structural breaks and non-linear adjustments of prices to dividends. The results show a significant structural break in 1998 for all model specifications and data periodicity. Furthermore, we do not find evidence of asymmetric adjustment of prices to dividends when using M-TAR and TAR models. The evidence of bubbles varies depending on the data periodicity and model specification used in the analysis. Finally, the results show persistent deviations of stock prices to dividends in all cases considered, though we only find evidence of bubbles in the Nasdaq index when using weekly data for the time period after June 1998.

  9. Stochastic model for market stocks with floors

    NASA Astrophysics Data System (ADS)

    Villarroel, Javier

    2007-08-01

    We present a model to describe the stochastic evolution of stocks that show a strong resistance at some level and generalize to this situation the evolution based upon geometric Brownian motion. If volatility and drift are related in a certain way we show that our model can be integrated in an exact way. The related problem of how to prize general securities that pay dividends at a continuous rate and earn a terminal payoff at maturity T is solved via the martingale probability approach.

  10. 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.

  11. Identifying the Bottom Line after a Stock Market Crash

    NASA Astrophysics Data System (ADS)

    Roehner, B. M.

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

  12. 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…

  13. Fractal Analysis of Prime Indian STOCK Market Indices

    NASA Astrophysics Data System (ADS)

    Samadder, Swetadri; Ghosh, Koushik; Basu, Tapasendra

    2013-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

  15. Probability distribution function and multiscaling properties in the Korean stock market

    NASA Astrophysics Data System (ADS)

    Lee, Kyoung Eun; Lee, Jae Woo

    2007-09-01

    We consider the probability distribution function (pdf) and the multiscaling properties of the index and the traded volume in the Korean stock market. We observed the power law of the pdf at the fat tail region for the return, volatility, the traded volume, and changes of the traded volume. We also investigate the multifractality in the Korean stock market. We consider the multifractality by the detrended fluctuation analysis (MFDFA). We observed the multiscaling behaviors for index, return, traded volume, and the changes of the traded volume. We apply MFDFA method for the randomly shuffled time series to observe the effects of the autocorrelations. The multifractality is strongly originated from the long time correlations of the time series.

  16. Efficiency of Thai stock markets: Detrended fluctuation analysis

    NASA Astrophysics Data System (ADS)

    Sukpitak, Jessada; Hengpunya, Varagorn

    2016-09-01

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

  17. 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.

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

    PubMed

    Cao, Hongduo; Li, Ying

    2014-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  20. 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.

  1. Chaotic behavior in Malaysian stock market: A study with recurrence quantification analysis

    NASA Astrophysics Data System (ADS)

    Niu, Betty Voon Wan; Noorani, Mohd Salmi Md; Jaaman, Saiful Hafizah

    2016-11-01

    The dynamics of stock market has been questioned for decades. Its behavior appeared random yet some found it behaves as chaos. Up to 5000 daily adjusted closing data of FTSE Bursa Malaysia Kuala Lumpur Composite Index (KLSE) was investigated through recurrence plot and recurrence quantification analysis. Results were compared between stochastic system, chaotic system and deterministic system. Results show that KLSE daily adjusted closing data behaves chaotically.

  2. 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.

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  5. 77 FR 2335 - Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-17

    ... COMMISSION Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate... Rule 19b-4 thereunder,\\2\\ notice is hereby given that on January 3, 2012, The NASDAQ Stock Market LLC... Terms of Substance of the Proposed Rule Change The NASDAQ Stock Market LLC proposes to modify Rule...

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  8. 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.

  9. 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.

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

    PubMed Central

    Maskawa, Jun-ichi

    2016-01-01

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

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

    PubMed

    Maskawa, Jun-Ichi

    2016-01-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Profitability of Contrarian Strategies in the Chinese Stock Market

    PubMed Central

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

    2015-01-01

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

  17. Profitability of Contrarian Strategies in the Chinese Stock Market.

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

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

    ERIC Educational Resources Information Center

    Maier, Mark H.

    2002-01-01

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

  1. 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.

  2. Topological Characteristics of the Hong Kong Stock Market: A Test-based P-threshold Approach to Understanding Network Complexity

    NASA Astrophysics Data System (ADS)

    Xu, Ronghua; Wong, Wing-Keung; Chen, Guanrong; Huang, Shuo

    2017-02-01

    In this paper, we analyze the relationship among stock networks by focusing on the statistically reliable connectivity between financial time series, which accurately reflects the underlying pure stock structure. To do so, we firstly filter out the effect of market index on the correlations between paired stocks, and then take a t-test based P-threshold approach to lessening the complexity of the stock network based on the P values. We demonstrate the superiority of its performance in understanding network complexity by examining the Hong Kong stock market. By comparing with other filtering methods, we find that the P-threshold approach extracts purely and significantly correlated stock pairs, which reflect the well-defined hierarchical structure of the market. In analyzing the dynamic stock networks with fixed-size moving windows, our results show that three global financial crises, covered by the long-range time series, can be distinguishingly indicated from the network topological and evolutionary perspectives. In addition, we find that the assortativity coefficient can manifest the financial crises and therefore can serve as a good indicator of the financial market development.

  3. Topological Characteristics of the Hong Kong Stock Market: A Test-based P-threshold Approach to Understanding Network Complexity

    PubMed Central

    Xu, Ronghua; Wong, Wing-Keung; Chen, Guanrong; Huang, Shuo

    2017-01-01

    In this paper, we analyze the relationship among stock networks by focusing on the statistically reliable connectivity between financial time series, which accurately reflects the underlying pure stock structure. To do so, we firstly filter out the effect of market index on the correlations between paired stocks, and then take a t-test based P-threshold approach to lessening the complexity of the stock network based on the P values. We demonstrate the superiority of its performance in understanding network complexity by examining the Hong Kong stock market. By comparing with other filtering methods, we find that the P-threshold approach extracts purely and significantly correlated stock pairs, which reflect the well-defined hierarchical structure of the market. In analyzing the dynamic stock networks with fixed-size moving windows, our results show that three global financial crises, covered by the long-range time series, can be distinguishingly indicated from the network topological and evolutionary perspectives. In addition, we find that the assortativity coefficient can manifest the financial crises and therefore can serve as a good indicator of the financial market development. PMID:28145494

  4. Topological Characteristics of the Hong Kong Stock Market: A Test-based P-threshold Approach to Understanding Network Complexity.

    PubMed

    Xu, Ronghua; Wong, Wing-Keung; Chen, Guanrong; Huang, Shuo

    2017-02-01

    In this paper, we analyze the relationship among stock networks by focusing on the statistically reliable connectivity between financial time series, which accurately reflects the underlying pure stock structure. To do so, we firstly filter out the effect of market index on the correlations between paired stocks, and then take a t-test based P-threshold approach to lessening the complexity of the stock network based on the P values. We demonstrate the superiority of its performance in understanding network complexity by examining the Hong Kong stock market. By comparing with other filtering methods, we find that the P-threshold approach extracts purely and significantly correlated stock pairs, which reflect the well-defined hierarchical structure of the market. In analyzing the dynamic stock networks with fixed-size moving windows, our results show that three global financial crises, covered by the long-range time series, can be distinguishingly indicated from the network topological and evolutionary perspectives. In addition, we find that the assortativity coefficient can manifest the financial crises and therefore can serve as a good indicator of the financial market development.

  5. 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.

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  9. Multifractal diffusion entropy analysis on stock volatility in financial markets

    NASA Astrophysics Data System (ADS)

    Huang, Jingjing; Shang, Pengjian; Zhao, Xiaojun

    2012-11-01

    This paper introduces a generalized diffusion entropy analysis method to analyze long-range correlation then applies this method to stock volatility series. The method uses the techniques of the diffusion process and Rényi entropy to focus on the scaling behaviors of regular volatility and extreme volatility respectively in developed and emerging markets. It successfully distinguishes their differences where regular volatility exhibits long-range persistence while extreme volatility reveals anti-persistence.

  10. Stock market networks: The dynamic conditional correlation approach

    NASA Astrophysics Data System (ADS)

    Lyócsa, Štefan; Výrost, Tomáš; Baumöhl, Eduard

    2012-08-01

    We demonstrate the economic relevance of minimum spanning trees (MSTs) constructed from dynamic conditional correlations (DCC) for a sample of S&P 100 constituents. An empirical comparison of MST properties shows that using the standard approach of rolling (or sliding-window) correlations yields trees that are more robust, have higher densities and exhibit higher industry clustering than MSTs based on DCC. Our results suggest that these properties are achieved at the expense of the smoothing of market dynamics, which is better preserved by DCC. The DCC approach offers a new perspective for the analysis of complex systems such as stock markets.

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

    NASA Astrophysics Data System (ADS)

    Bentes, Sónia R.

    2015-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Ying, Shangjun; Li, Xiaojun; Zhong, Xiuqin

    2015-04-01

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

  13. What stock market returns to expect for the future?

    PubMed

    Diamond, P A

    2000-01-01

    In evaluating proposals for reforming Social Security that involve stock investments, the Office of the Chief Actuary (OCACT) has generally used a 7.0 percent real return for stocks. The 1994-96 Advisory Council specified that OCACT should use that return in making its 75-year projections of investment-based reform proposals. The assumed ultimate real return on Treasury bonds of 3.0 percent implies a long-run equity premium of 4.0 percent. There are two equity-premium concepts: the realized equity premium, which is measured by the actual rates of return; and the required equity premium, which investors expect to receive for being willing to hold available stocks and bonds. Over the past two centuries, the realized premium was 3.5 percent on average, but 5.2 percent for 1926 to 1998. Some critics argue that the 7.0 percent projected stock returns are too high. They base their arguments on recent developments in the capital market, the current high value of the stock market, and the expectation of slower economic growth. Increased use of mutual funds and the decline in their costs suggest a lower required premium, as does the rising fraction of the American public investing in stocks. The size of the decrease is limited, however, because the largest cost savings do not apply to the very wealthy and to large institutional investors, who hold a much larger share of the stock market's total value than do new investors. These trends suggest a lower equity premium for projections than the 5.2 percent of the past 75 years. Also, a declining required premium is likely to imply a temporary increase in the realized premium because a rising willingness to hold stocks tends to increase their price. Therefore, it would be a mistake during a transition period to extrapolate what may be a temporarily high realized return. In the standard (Solow) economic growth model, an assumption of slower long-run growth lowers the marginal product of capital if the savings rate is constant

  14. 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.

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

    PubMed

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

    2013-06-06

    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.

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

    NASA Astrophysics Data System (ADS)

    Roehner, Bertrand M.

    2005-03-01

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

  17. 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.

  18. 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.

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

    PubMed

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

    2009-12-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim

    2016-08-01

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

  3. Analytical study of index-coupled herd behavior in financial markets

    NASA Astrophysics Data System (ADS)

    Berman, Yonatan; Shapira, Yoash; Schwartz, Moshe

    2016-12-01

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

  4. Structural Evolutions of STOCK Markets Controlled by Generalized Entropy Principles of Complex Systems

    NASA Astrophysics Data System (ADS)

    Wang, Yi Jiao; Feng, Qing Yi; Chai, Li He

    As one of the most important financial markets and one of the main parts of economic system, the stock market has become the research focus in economics. The stock market is a typical complex open system far from equilibrium. Many available models that make huge contribution to researches on market are strong in describing the market however, ignoring strong nonlinear interactions among active agents and weak in reveal underlying dynamic mechanisms of structural evolutions of market. From econophysical perspectives, this paper analyzes the complex interactions among agents and defines the generalized entropy in stock markets. Nonlinear evolutionary dynamic equation for the stock markets is then derived from Maximum Generalized Entropy Principle. Simulations are accordingly conducted for a typical case with the given data, by which the structural evolution of the stock market system is demonstrated. Some discussions and implications are finally provided.

  5. 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.

  6. 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?

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-12-20

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

  9. Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study.

    PubMed

    Bhattacharjee, Biplab; Shafi, Muhammad; Acharjee, Animesh

    2016-01-01

    The socio-economic systems today possess high levels of both interconnectedness and interdependencies, and such system-level relationships behave very dynamically. In such situations, it is all around perceived that influence is a perplexing power that has an overseeing part in affecting the dynamics and behaviours of involved ones. As a result of the force & direction of influence, the transformative change of one entity has a cogent aftereffect on the other entities in the system. The current study employs directed weighted networks for investigating the influential relationship patterns existent in a typical equity market as an outcome of inter-stock interactions happening at the market level, the sectorial level and the industrial level. The study dataset is derived from 335 constituent stocks of 'Standard & Poor Bombay Stock Exchange 500 index' and study period is 1st June 2005 to 30th June 2015. The study identifies the set of most dynamically influential stocks & their respective temporal pattern at three hierarchical levels: the complete equity market, different sectors, and constituting industry segments of those sectors. A detailed influence relationship analysis is performed for the sectorial level network of the construction sector, and it was found that stocks belonging to the cement industry possessed high influence within this sector. Also, the detailed network analysis of construction sector revealed that it follows scale-free characteristics and power law distribution. In the industry specific influence relationship analysis for cement industry, methods based on threshold filtering and minimum spanning tree were employed to derive a set of sub-graphs having temporally stable high-correlation structure over this ten years period.

  10. 17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 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 Exchanges SECURITIES AND EXCHANGE COMMISSION (CONTINUED) GENERAL RULES AND REGULATIONS, SECURITIES EXCHANGE ACT OF...

  11. How the 2008 stock market crash and seasons affect total and cardiac deaths in Los Angeles County.

    PubMed

    Schwartz, Bryan Glen; Pezzullo, John Christopher; McDonald, Scott Andrew; Poole, William Kenneth; Kloner, Robert Alan

    2012-05-15

    Various stressors trigger cardiac death. The objective was to investigate a possible relation between a stock market crash and cardiac death in a large population within the United States. We obtained daily stock market data (Dow Jones Industrial Average Index), death certificate data for daily deaths in Los Angeles County (LA), and annual LA population estimates for 2005 through 2008. The 4 years death rate curves (2005 through 2008) were averaged into a single curve to illustrate annual trends. Data were "deseasonalized" by subtracting from the daily observed value the average value for that day of year. There was marked seasonal variation in total and cardiac death rates. Even in the mild LA climate, death rates were higher in winter versus summer including total death (+17%), circulatory death (+24%), coronary heart disease death (+28%), and myocardial infarction death (+38%) rates (p <0.0001 for each). Absolute coronary heart disease death rates have decreased since 1985. After accounting for seasonal variation, the large stock market crash in October 2008 did not affect death rates in LA. Death rates remained at or below seasonal averages during the stock market crash. In conclusion, after correcting for seasonal variation, the stock market crash in October 2008 was not associated with an increase in total or cardiac death in LA. Annual coronary heart disease death rates continue to decrease. However, seasonal variation (specifically winter) remains a trigger for death and coronary heart disease death even in LA where winters are mild.

  12. 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.

  13. 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.

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

    PubMed

    Berument, M Hakan; Ceylan, Nildag Basak

    2013-06-01

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

  15. Log-periodic view on critical dates of the Chinese stock market bubbles

    NASA Astrophysics Data System (ADS)

    Li, Chong

    2017-01-01

    We present an analysis of critical dates of three historical Chinese stock market bubbles (July 2006-Oct. 2007, Dec. 2007-Oct. 2008, Oct. 2014-June 2015) based on the Shanghai Shenzhen CSI 300 index (CSI300). This supports that the log-periodic power law singularity (LPPLS) model can describe well the behavior of super-exponential (power law with finite-time singularity) increase or decrease of the CSI300 index, suggesting that the LPPLS is available to predict the critical date. We also attempt to analyze the fitting parameter α of the LPPLS and the forecast gap which is between the last observed date and the expected critical date, proposing that the forecast gap is an alternative way for advanced warning of the market conversion.

  16. Metaphors and the Market: Consequences and Preconditions of Agent and Object Metaphors in Stock Market Commentary

    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…

  17. Effects of daylight-saving time changes on stock market returns and stock market volatility: rebuttal.

    PubMed

    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.

  18. Microscopic analysis of currency and stock exchange markets

    NASA Astrophysics Data System (ADS)

    Kador, L.

    1999-08-01

    Recently it was shown that distributions of short-term price fluctuations in foreign-currency exchange exhibit striking similarities to those of velocity differences in turbulent flows. Similar profiles represent the spectral-diffusion behavior of impurity molecules in disordered solids at low temperatures. It is demonstrated that a microscopic statistical theory of the spectroscopic line shapes can be applied to the other two phenomena. The theory interprets the financial data in terms of information which becomes available to the traders and their reactions as a function of time. The analysis shows that there is no characteristic time scale in financial markets, but that instead stretched-exponential or algebraic memory functions yield good agreement with the price data. For an algebraic function, the theory yields truncated Lévy distributions which are often observed in stock exchange markets.

  19. Microscopic analysis of currency and stock exchange markets.

    PubMed

    Kador, L

    1999-08-01

    Recently it was shown that distributions of short-term price fluctuations in foreign-currency exchange exhibit striking similarities to those of velocity differences in turbulent flows. Similar profiles represent the spectral-diffusion behavior of impurity molecules in disordered solids at low temperatures. It is demonstrated that a microscopic statistical theory of the spectroscopic line shapes can be applied to the other two phenomena. The theory interprets the financial data in terms of information which becomes available to the traders and their reactions as a function of time. The analysis shows that there is no characteristic time scale in financial markets, but that instead stretched-exponential or algebraic memory functions yield good agreement with the price data. For an algebraic function, the theory yields truncated Lévy distributions which are often observed in stock exchange markets.

  20. Dissecting cross-impact on stock markets: an empirical analysis

    NASA Astrophysics Data System (ADS)

    Benzaquen, M.; Mastromatteo, I.; Eisler, Z.; Bouchaud, J.-P.

    2017-02-01

    The vast majority of market impact studies assess each product individually, and the interactions between the different order flows are disregarded. This strong approximation may lead to an underestimation of trading costs and possible contagion effects. Transactions in fact mediate a significant part of the correlation between different instruments. In turn, liquidity shares the sectorial structure of market correlations, which can be encoded as a set of eigenvalues and eigenvectors. We introduce a multivariate linear propagator model that successfully describes such a structure, and accounts for a significant fraction of the covariance of stock returns. We dissect the various dynamical mechanisms that contribute to the joint dynamics of assets. We also define two simplified models with substantially less parameters in order to reduce overfitting, and show that they have superior out-of-sample performance.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  2. Long-range correlations and nonstationarity in the Brazilian stock market

    NASA Astrophysics Data System (ADS)

    Costa, Rogério L.; Vasconcelos, G. L.

    2003-11-01

    We report an empirical study of the Ibovespa index of the São Paulo Stock Exchange in which we detect the existence of long-range correlations. To analyze our data, we introduce a rescaled variant of the usual detrended fluctuation analysis that allows us to obtain the Hurst exponent through a one-parameter fitting. We also compute a time-dependent Hurst exponent H( t) using 3-year moving time windows. In particular, we find that before the launch of the Collor Plan in 1990 the curve H( t) remains, in general, well above {1}/{2}, while afterwards it stays close to {1}/{2}. We thus argue that the structural reforms set off by the Collor Plan has lead to a more efficient stock market in Brazil. We also suggest that the time dependence of the Ibovespa Hurst exponent could be described in terms of a multifractional Brownian motion.

  3. 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.

  4. Web Search Queries Can Predict Stock Market Volumes

    PubMed Central

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

    2012-01-01

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

  5. Web search queries can predict stock market volumes.

    PubMed

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

    2012-01-01

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

  6. 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.

  7. Bond-market skepticism and stock-market exuberance in the hospital industry.

    PubMed

    Robinson, James C

    2002-01-01

    The hospital industry needs funds to refurbish physical facilities, upgrade clinical and information technologies, and rebuild financial positions weakened by past external challenges and unwise organizational strategies. The financial markets offer a marked contrast in capital access, as bond creditors remain skeptical while stock investors plunge back into the once-shunned industry. Ironically, high stock prices may drive the for-profit chains to repeat past cycles of overexpansion, while weak bond ratings may save non-profit systems from a comparable loss of focus on the core business of operating and improving inpatient facilities. This turbulence has implications for public payment, antitrust, and financial disclosure policies.

  8. 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.

  9. 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.

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

    ERIC Educational Resources Information Center

    Keller, Heath; Cox, James R.

    2004-01-01

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

  11. Analysis of the efficiency-integration nexus of Japanese stock market

    NASA Astrophysics Data System (ADS)

    Rizvi, Syed Aun R.; Arshad, Shaista

    2017-03-01

    This paper attempts a novel approach in analysing the Japanese economy through a dual-dimension analysis of its stock market, examining the efficiency and market integration. Taking a period of 24 years, this study employs MFDFA and MGARCH to understand how the efficiency and integration of the stock market faired during different business cycle phases of the Japanese economy. The results showed improving efficiency over the time period. For the case of market integration, our findings conform to recent literature on business cycles and stock market integration that every succeeding recession creates a break into integration levels resulting in a decrease.

  12. 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.

  13. The scaling properties of stock markets based on modified multiscale multifractal detrended fluctuation analysis

    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.

  14. 77 FR 8312 - Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-14

    ... Change The NASDAQ Stock Market LLC proposes to modify Chapter XV, entitled ``Option Fees,'' at Sec. 2... COMMISSION Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change Relating to Options Fees February 8, 2012. Pursuant to Section 19(b)(1)...

  15. 76 FR 78325 - Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-16

    ... COMMISSION Self-Regulatory Organizations; NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of a Proposed Rule Change Relating to Option Fee Disputes December 9, 2011. Pursuant to Section 19... hereby given that on November 30, 2011. The NASDAQ Stock Market LLC (``NASDAQ'' or ``Exchange'')...

  16. Detecting Subtle Effects of Persistence in the Stock Market Dynamics

    NASA Astrophysics Data System (ADS)

    Rak, R.; Drożdż, S.; Kwapień, J.; Oświecimka, P.

    2005-08-01

    The conventional formal tool to detect effects of the financial persistence is in terms of the Hurst exponent. A typical corresponding result is that its value comes out close to 0.5, as characteristic for geometric Brownian motion, with at most small departures from this value in either direction depending on the market and on the time scales involved. We study the high frequency price changes on the American and on the German stock markets. For both corresponding indices, the Dow Jones and the DAX respectively, the Hurst exponent analysis results in values close to 0.5. However, by decomposing the market dynamics into pairs of steps such that an elementary move up (down) is followed by another move up (down) and explicitly counting the resulting conditional probabilities we find values typically close to 60%. This effect of persistence is particularly visible on the short time scales ranging from 1 up to 3 minutes, decreasing gradually to 50% and even significantly below this value on the larger time scales. We also detect some asymmetry in persistence related to the moves up and down, respectively. This indicates a subtle nature of the financial persistence whose characteristics escape detection within the conventional Hurst exponent formalism.

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

    NASA Astrophysics Data System (ADS)

    Bentes, Sónia R.

    2014-08-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  20. Evidence of multifractality from emerging European stock markets.

    PubMed

    Caraiani, Petre

    2012-01-01

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

  1. Evidence of Multifractality from Emerging European Stock Markets

    PubMed Central

    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

  2. Time-varying Hurst exponent for US stock markets

    NASA Astrophysics Data System (ADS)

    Alvarez-Ramirez, Jose; Alvarez, Jesus; Rodriguez, Eduardo; Fernandez-Anaya, Guillermo

    2008-10-01

    In this work, the dynamical behavior of the US stock markets is characterized on the basis of the temporal variations of the Hurst exponent estimated with detrended fluctuation analysis (DFA) over moving windows for the historical Dow Jones (1928-2007) and the S&P-500 (1950-2007) daily indices. According to the results drawn: (i) the Hurst exponent displays an erratic dynamics with some episodes alternating low and high persistent behavior, (ii) the major breakthrough of the long-term trend of the scaling behavior occurred in 1972, at the end of the Bretton Woods system, when the Hurst exponent shifted form a positive to a negative long-term trend. Other effects, such as the 1987 crisis and the emergence of anti-correlated behavior in the recent two years, are also discussed.

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

    PubMed

    Righi, Marcelo Brutti; Vieira, Kelmara Mendes

    2014-01-01

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

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

    PubMed Central

    Righi, Marcelo Brutti; Vieira, Kelmara Mendes

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhuang, Xiaoyang; Wei, Yu; Ma, Feng

    2015-07-01

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

  6. Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market

    PubMed Central

    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

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

    PubMed

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

    2010-12-20

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

  8. Examining the efficiency and interdependence of US credit and stock markets through MF-DFA and MF-DXA approaches

    NASA Astrophysics Data System (ADS)

    Shahzad, Syed Jawad Hussain; Nor, Safwan Mohd; Mensi, Walid; Kumar, Ronald Ravinesh

    2017-04-01

    This study examines the power law properties of 11 US credit and stock markets at the industry level. We use multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DXA) to first investigate the relative efficiency of credit and stock markets and then evaluate the mutual interdependence between CDS-equity market pairs. The scaling exponents of the MF-DFA approach suggest that CDS markets are relatively more inefficient than their equity counterparts. However, Banks and Financial credit markets are relatively more efficient. Basic Materials (both CDS and equity indices) is the most inefficient sector of the US economy. The cross-correlation exponents obtained through MF-DXA also suggest that the relationship of the CDS and equity sectors within and across markets is multifractal for all pairs. Within the CDS market, Basic Materials is the most dependent sector, whereas equity market sectors can be divided into two distinct groups based on interdependence. The pair-wise dependence between Basic Materials sector CDSs and the equity index is also the highest. The degree of cross-correlation shows that the sectoral pairs of CDS and equity markets belong to a persistent cross-correlated series within selected time intervals.

  9. Statistical properties of trading activity in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Sun, Xiaoqian; Cheng, Xueqi; Shen, Huawei; Wang, Zhaoyang

    2010-08-01

    We investigate the statistical properties of traders' trading behavior using cumulative distribution function(CDF). We analyze exchange data of 52 stocks for one-year period which contains non-manipulated stocks and manipulated stocks published by China Securities Regulatory Commission(CSRC). By analyzing the total number of transactions and the trading volume of each trader over a year, we find the cumulative distributions have power-law tails and the distributions between non-manipulated stocks and manipulated stocks are different. These findings can help us to detect the manipulated stocks.

  10. 76 FR 44076 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-22

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Amend NASDAQ Stock Market Equities Trading Rules 4757 and 4758 and... 13, 2011, The NASDAQ Stock Market LLC (the ``Exchange'' or ``NASDAQ'') filed with the Securities...

  11. 77 FR 75232 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-19

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...\\ thereunder, notice is hereby given that on November 30, 2012, The NASDAQ Stock Market LLC (``NASDAQ'' or... Terms of the Substance of the Proposed Rule Change The NASDAQ Stock Market LLC proposes changes...

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

    PubMed

    Mu, Guo-Hua; Zhou, Wei-Xing

    2010-12-01

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

  13. 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

  14. 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.

  15. Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA

    NASA Astrophysics Data System (ADS)

    Cao, Guangxi; Cao, Jie; Xu, Longbing

    2013-02-01

    We utilized asymmetric multifractal detrended fluctuation analysis in this study to examine the asymmetric multifractal scaling behavior of Chinese stock markets with uptrends or downtrends. Results show that the multifractality degree of Chinese stock markets with uptrends is stronger than that of Chinese stock markets with downtrends. Correlation asymmetries are more evident in large fluctuations than in small fluctuations. By discussing the source of asymmetric multifractality, we find that multifractality is related to long-range correlations when the market is going up, whereas it is related to fat-tailed distribution when the market is going down. The main source of asymmetric scaling behavior in the Shanghai stock market are long-range correlations, whereas that in the Shenzhen stock market is fat-tailed distribution. An analysis of the time-varying feature of scaling asymmetries shows that the evolution trends of these scaling asymmetries are similar in the two Chinese stock markets. Major financial and economical events may enhance scaling asymmetries.

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  18. Impact of Stock Market Structure on Intertrade Time and Price Dynamics

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  20. Characteristics of the volatility in the Korea composite stock price index

    NASA Astrophysics Data System (ADS)

    Lee, Chang-Yong

    2009-09-01

    We empirically analyze the time series of the Korea Composite Stock Price Index (KOSPI) from March of 1992 to February of 2007 using methods from the hydrodynamic turbulence. To this end, we focus on characteristics of the return and volatility, which are respectively the price change and a measure of the financial market fluctuation over a time interval. With these, we show that the non-Gaussian probability distribution of the return can be modeled by the convolution of the conditional probability distribution of the return given the volatility and the distribution of the volatility per se. From this model, we suggest that the non-Gaussian characteristic of the return results from the fluctuation of the volatility. That is, a large return is partly, if not entirely, due to the market fluctuation in a long time scale influencing the fluctuation in a short time scale via net information flow. We further show that the volatility has a multi-fractal property, which resembles the multifractality of the energy dissipation in the turbulence.

  1. 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.

  2. 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.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  5. Effect of market factors on the short-time pricing of stock-exchange metals

    NASA Astrophysics Data System (ADS)

    Bogdanov, S. V.; Shevelev, I. M.; Chernyi, S. A.

    2016-12-01

    The open trade on the world market is estimated using information of one-day exchange prices of nonferrous and precious metals, oil, reduced crude, and gasoline and the main world stock indices in the time period from January 1, 2009 to December 31, 2015. It is found that the short-term changes in the prices of nonferrous metals are determined by the prices on the metal market. The changes in the prices of energy carriers and the stock trade on the stock market weakly influence the pricing of nonferrous and precious metals. The prices of metals depend on the situation during trade on commodity exchanges, and the stock market indirectly influences the exchange prices of metals through changes in the share prices of the companies that produce copper, aluminum, and zinc.

  6. 78 FR 50123 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-16

    ... free and open market and a national market system, and, in general, to protect investors and the public... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule... that on July 31, 2013, The NASDAQ Stock Market LLC (``NASDAQ'' or the ``Exchange'') filed with...

  7. 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.

  8. Long-time fluctuations in a dynamical model of stock market indices.

    PubMed

    Biham, O; Huang, Z F; Malcai, O; Solomon, S

    2001-08-01

    Financial time series typically exhibit strong fluctuations that cannot be described by a Gaussian distribution. Recent empirical studies of stock market indices examined whether the distribution P(r) of returns r(tau) after some time tau can be described by a (truncated) Lévy-stable distribution L(alpha)(r) with some index 0index is consistent with the Lévy distribution with alpha=1.4. In a more recent study [P. Gopikrishnan et al., Phys. Rev. E 60, 5305 (1999)] it was found that the tails of P(r) exhibit a power-law decay, with an exponent alpha congruent with 3, thus deviating from the Lévy distribution. In this paper we study the distribution of returns in a generic model that describes the dynamics of stock market indices. For the distributions P(r) generated by this model, we observe that the scaling of the central peak is consistent with a Lévy distribution while the tails exhibit a power-law distribution with an exponent alpha>2, namely, beyond the range of Lévy-stable distributions. Our results are in agreement with both empirical studies and reconcile the apparent disagreement between their results.

  9. 77 FR 24549 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Amendment No. 1...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-24

    ... competitive advantage over Nasdaq'' because issuers listing on Nasdaq would risk being deemed a ``penny stock... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Amendment No. 1... Requirements are Met April 18, 2012. I. Introduction On January 3, 2012, The NASDAQ Stock Market...

  10. 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.

  11. Dynamic spanning trees in stock market networks: The case of Asia-Pacific

    NASA Astrophysics Data System (ADS)

    Sensoy, Ahmet; Tabak, Benjamin M.

    2014-11-01

    This article proposes a new procedure to evaluate Asia Pacific stock market interconnections using a dynamic setting. Dynamic spanning trees (DST) are constructed using an ARMA-FIEGARCH-cDCC process. The main results show that: 1. the DST significantly shrinks over time; 2. Hong Kong is found to be the key financial market; 3. the DST has a significantly increased stability in the last few years; 4. the removal of the key player has two effects: there is no clear key market any longer and the stability of the DST significantly decreases. These results are important for the design of policies that help develop stock markets and for academics and practitioners.

  12. 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.

  13. 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

  14. 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.

  15. 26 CFR 1.1296-2 - Definition of marketable stock.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... means— (1) Passive foreign investment company (PFIC) stock that is regularly traded, as defined in... section; (2) Stock in certain PFICs, as described in paragraph (d) of this section; and (3) Options on... the quarter in which the offering occurs, or 5 days. (3) Anti-abuse rule. Trades that have as one...

  16. 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.

  17. A dynamical model describing stock market price distributions

    NASA Astrophysics Data System (ADS)

    Masoliver, Jaume; Montero, Miquel; Porrà, Josep M.

    2000-08-01

    High-frequency data in finance have led to a deeper understanding on probability distributions of market prices. Several facts seem to be well established by empirical evidence. Specifically, probability distributions have the following properties: (i) They are not Gaussian and their center is well adjusted by Lévy distributions. (ii) They are long-tailed but have finite moments of any order. (iii) They are self-similar on many time scales. Finally, (iv) at small time scales, price volatility follows a non-diffusive behavior. We extend Merton's ideas on speculative price formation and present a dynamical model resulting in a characteristic function that explains in a natural way all of the above features. The knowledge of such a distribution opens a new and useful way of quantifying financial risk. The results of the model agree - with high degree of accuracy - with empirical data taken from historical records of the Standard & Poor's 500 cash index.

  18. 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

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

    PubMed

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

    2001-01-01

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

  20. An econophysics approach to the Portuguese Stock Index-PSI-20

    NASA Astrophysics Data System (ADS)

    Matos, José A. O.; Gama, Sílvio M. A.; Ruskin, Heather J.; Duarte, José A. M. S.

    2004-11-01

    We analyse the PSI-20 (Portuguese Stock Index) data series from 1993 to 2001, with a view to examining the structure of the series, the appropriateness of the standard model forms for these data and evidence for market maturation. The data demonstrate several distinct behavioural periods, with characteristic dependence on different time-scales, and increased volatility during 1998-2000. The distribution of the daily logarithmic variation reveals an exponential decay in the central region, with typically fatter tails than expected from the Normal distribution. In particular, the characterisation of the time series profile of the daily variation with respect to the index value shows a power-law with exponent 1.58 different from those predicted by the additive and multiplicative models. In addition, we model the index series using a fractional Brownian motion formulation to obtain the Hurst exponents evaluating these through detrended fluctuation analysis, with different window sizes. It seems clear that persistence is a feature of the initial period, but is not evident (as might be expected) for periods of high volatility. However, some indication of recent improvements in stability is observed even for coarse-graining. This transition from persistent to anti-persistent behaviour is clearly reflected in the Hurst exponent values and supports to some extent the notion of volatility clustering. Furthermore, the grouping of similar exponent values as the series data evolve suggests that short-term memory is exhibited by the original series, even when volatility is relatively high. These findings are broadly supported by a further analysis of persistence in trends for the returns series, with the autocorrelation function for the returns, ηt= δXt/ Xt, of the PSI-20 indicative of stronger short-term memory effects, although the modulus of return is not autocorrelated.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    PubMed

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

    2015-07-01

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

  3. The relationships between Shanghai stock market and CNY/USD exchange rate: New evidence based on cross-correlation analysis, structural cointegration and nonlinear causality test

    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.

  4. Evolutions of fluctuation modes and inner structures of global stock markets

    NASA Astrophysics Data System (ADS)

    Yan, Yan; Wang, Lei; Liu, Maoxin; Chen, Xiaosong

    2016-09-01

    The paper uses empirical data, including 42 globally main stock indices in the period 1996-2014, to systematically study the evolution of fluctuation modes and inner structures of global stock markets. The data are large in scale considering both time and space. A covariance matrix-based principle fluctuation mode analysis (PFMA) is used to explore the properties of the global stock markets. It has been ignored by previous studies that covariance matrix is more suitable than the correlation matrix to be the basis of PFMA. It is found that the principle fluctuation modes of global stock markets are in the same directions, and global stock markets are divided into three clusters, which are found to be closely related to the countries’ locations with exceptions of China, Russia and Czech Republic. A time-stable correlation network constructing method is proposed to solve the problem of high-level statistical uncertainty when the estimated periods are very short, and the complex dynamic network (CDN) is constructed to investigate the evolution of inner structures. The results show when the clusters emerge and how long the clusters exist. When the 2008 financial crisis broke out, the indices form one cluster. After these crises, only the European cluster still exists. These findings complement the previous studies, and can help investors and regulators to understand the global stock markets.

  5. Dynamic Evolution of Cross-Correlations in the Chinese Stock Market

    PubMed Central

    Ren, Fei; Zhou, Wei-Xing

    2014-01-01

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

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

    PubMed

    Ren, Fei; Zhou, Wei-Xing

    2014-01-01

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

  7. Association between Stock Market Gains and Losses and Google Searches

    PubMed Central

    Arditi, Eli; Yechiam, Eldad; Zahavi, Gal

    2015-01-01

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

  8. Association between Stock Market Gains and Losses and Google Searches.

    PubMed

    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.

  9. 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.

  10. 75 FR 64384 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Instituting Proceedings To...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-19

    ..., particularly in times of market stress, and exacerbate market volatility.\\8\\ \\7\\ See BATS Letter at 2; Deutsche... Volatility Guard to work within the parameters of the recently adopted single-stock circuit breakers, and to... the increasing number of LRPs on May 6 played into their decisions to reduce liquidity, pause...

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

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim

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

  12. Comparison between the probability distribution of returns in the Heston model and empirical data for stock indexes

    NASA Astrophysics Data System (ADS)

    Silva, A. Christian; Yakovenko, Victor M.

    2003-06-01

    We compare the probability distribution of returns for the three major stock-market indexes (Nasdaq, S&P500, and Dow-Jones) with an analytical formula recently derived by Drăgulescu and Yakovenko for the Heston model with stochastic variance. For the period of 1982-1999, we find a very good agreement between the theory and the data for a wide range of time lags from 1 to 250 days. On the other hand, deviations start to appear when the data for 2000-2002 are included. We interpret this as a statistical evidence of the major change in the market from a positive growth rate in 1980s and 1990s to a negative rate in 2000s.

  13. 78 FR 35656 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Approval to Proposed...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-13

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Approval to Proposed... as ``Retail Orders'' June 7, 2013. I. Introduction On February 19, 2013, The NASDAQ Stock Market LLC..., Managing Director and Associate General Counsel, Securities Industry and Financial Markets...

  14. 77 FR 1537 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-10

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...\\ notice is hereby given that on December 22, 2011, The NASDAQ Stock Market LLC (``NASDAQ'') filed with the... the NASDAQ Last Sale (``NLS'') market data products. NLS allows data distributors to have access...

  15. 78 FR 19791 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-02

    ... route orders in options listed and open for trading to destination markets. Each time NOS routes to away... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate... that on March 19, 2013, The NASDAQ Stock Market LLC (``NASDAQ'' or ``Exchange'') filed with...

  16. 77 FR 57171 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Designation of a Longer...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-17

    ... Financial Markets Association, dated August 22, 2012; Mark Shelton, Group Managing Director and General... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Designation of a Longer... September 12, 2012. On July 23, 2012, The NASDAQ Stock Market LLC (``NASDAQ'' or ``Exchange'') filed...

  17. 78 FR 24282 - Self-Regulatory Organizations; the NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-24

    ... proposal creates a burden on intra-market competition because the Exchange is applying the same Routing... COMMISSION Self-Regulatory Organizations; the NASDAQ Stock Market LLC; Notice of Filing and Immediate... given that on April 9, 2013, The NASDAQ Stock Market LLC (``NASDAQ'' or ``Exchange'') filed with...

  18. 78 FR 26820 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-05-08

    ... raise any issues of intra-market competition because it involves inbound routing from an affiliated... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule... NASDAQ Stock Market LLC (the ``Exchange'' or ``Nasdaq'') filed with the Securities and...

  19. 76 FR 57778 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-09-16

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify Fees for Members Using the NASDAQ Options Market September 12... thereunder,\\2\\ notice is hereby given that on September 1, 2011, The NASDAQ Stock Market LLC (``NASDAQ''...

  20. 76 FR 57776 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-09-16

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify Fees for Members Using the NASDAQ Options Market September 12... thereunder,\\2\\ notice is hereby given that on September 6, 2011, The NASDAQ Stock Market LLC (``NASDAQ''...

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

    NASA Astrophysics Data System (ADS)

    Yang, Miao; Jiang, Zhi-Qiang

    2016-11-01

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

  2. Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix

    NASA Astrophysics Data System (ADS)

    Takaishi, Tetsuya

    2016-08-01

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

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

    PubMed Central

    Zhu, Tao; Li, Yuelei; Xiong, Xiong

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Cui, Ling-xiao; Long, Wen

    2016-11-01

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

  6. 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.

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

    PubMed

    Cavapozzi, Danilo; Trevisan, Elisabetta; Weber, Guglielmo

    2013-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Jaber, Abobaker M.

    2014-12-01

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

  9. 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).

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

    PubMed Central

    Cano, Carlos; Jareño, Francisco; Tolentino, Marta

    2016-01-01

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

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

    PubMed

    Cano, Carlos; Jareño, Francisco; Tolentino, Marta

    2016-01-01

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

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

  15. 78 FR 41489 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-10

    ... the definition of Derivative Securities Products, weight of component stocks of an index or portfolio... Securities Products, weight of component stocks of an index or portfolio,\\3\\ averaging minimum notional value... ``Derivative Securities Products'' from Rule 5705(b)(3)(A)(i) a., b., and c. for U.S. Indexes or...

  16. 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…

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

    SciTech Connect

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

    2010-11-15

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

  18. Dataset for petroleum based stock markets and GAUSS codes for SAMEM.

    PubMed

    Khalifa, Ahmed A A; Bertuccelli, Pietro; Otranto, Edoardo

    2017-02-01

    This article includes a unique data set of a balanced daily (Monday, Tuesday and Wednesday) for oil and natural gas volatility and the oil rich economies' stock markets for Saudi Arabia, Qatar, Kuwait, Abu Dhabi, Dubai, Bahrain and Oman, using daily data over the period spanning Oct. 18, 2006-July 30, 2015. Additionally, we have included unique GAUSS codes for estimating the spillover asymmetric multiplicative error model (SAMEM) with application to Petroleum-Based Stock Market. The data, the model and the codes have many applications in business and social science.

  19. Effects of Daylight Saving Time changes on stock market volatility: a reply.

    PubMed

    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.

  20. 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.

  1. 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.

  2. 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.

  3. 75 FR 78302 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-15

    ... Contained in the Standard & Poor's 500 Index, Russell 1000 Index, and Specified Exchange Traded Products... individual stocks contained in the Standard & Poor's 500 Index, Russell 1000 Index, and specified Exchange... securities in the Standard & Poor's 500 Index, the Russell 1000 Index, as well as a pilot list of...

  4. Can Big Data Machines Analyze Stock Market Sentiment?

    PubMed

    Dhar, Vasant

    2014-12-01

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

  5. 75 FR 64375 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-19

    ... maintain username/password entitlement systems and/or quote counting mechanisms also have multiple options... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...,\\2\\ notice is hereby given that on October 1, 2010, The NASDAQ Stock Market LLC (``NASDAQ'')...

  6. 78 FR 6382 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-30

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...\\ notice is hereby given that on January 16, 2013, The NASDAQ Stock Market LLC (``NASDAQ'' or ``Exchange... of the Proposed Rule Change NASDAQ proposes to list and trade option contracts overlying 10 shares...

  7. 77 FR 74538 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-14

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

  8. 75 FR 5822 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-02-04

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

  9. 76 FR 20407 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-12

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Amend NASDAQ Rule 3011 To Reflect Changes to a Corresponding Financial..., 2011, The NASDAQ Stock Market LLC (the ``Exchange'' or ``NASDAQ'') filed with the Securities...

  10. 76 FR 9397 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-17

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Offer Additional Routing Option February 14, 2011. Pursuant to Section... hereby given that on February 10, 2011, The NASDAQ Stock Market LLC (``NASDAQ'' or the...

  11. 78 FR 64556 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-29

    ... market conditions, additional series of individual stock options may be added in the discretion of the... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Implement Transition to Friday Expiration for Most Options...

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

    SciTech Connect

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

    2015-12-07

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

  13. 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.

  14. 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Gu, Gao-Feng; Zhou, Wei-Xing

    2007-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Gao, Yan; Gao, Yao

    2015-11-01

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

  19. 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

  20. Modeling Stock Order Flows and Learning Market-Making from Data

    DTIC Science & Technology

    2002-06-01

    and demand. In this paper, we demonstrate a novel method for modeling the market as a dynamic system and a reinforcement learning algorithm that learns...difficult dynamic system. Our reinforcement learning algorithm, based on likelihood ratios, is run on this partially-observable environment. We demonstrate learning results for two separate real stocks.

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

    PubMed

    Araújo, Ricardo de A

    2012-04-01

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

  2. 75 FR 21688 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Accelerated Approval...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-26

    ... Securities April 20, 2010. I. Introduction On March 11, 2010, The NASDAQ Stock Market LLC (``Nasdaq'' or... predictability for investors who may view these products as serving similar investment functions in the... and predictability for investors who may view these products as serving similar investment...

  3. 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.

  4. 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.

  5. 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.…

  6. 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…

  7. The predictive power of Japanese candlestick charting in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Chen, Shi; Bao, Si; Zhou, Yu

    2016-09-01

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

  8. Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis

    NASA Astrophysics Data System (ADS)

    Mensi, Walid; Tiwari, Aviral Kumar; Yoon, Seong-Min

    2017-04-01

    This paper estimates the weak-form efficiency of Islamic stock markets using 10 sectoral stock indices (basic materials, consumer services, consumer goods, energy, financials, health care, industrials, technology, telecommunication, and utilities). The results based on the multifractal detrended fluctuation analysis (MF-DFA) approach show time-varying efficiency for the sectoral stock markets. Moreover, we find that they tend to show high efficiency in the long term but moderate efficiency in the short term, and that these markets become less efficient after the onset of the global financial crisis. These results have several significant implications in terms of asset allocation for investors dealing with Islamic markets.

  9. 77 FR 47472 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving Proposed Rule Change...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-08

    ..., to remove impediments to and perfect the mechanism of a free and open market and a national market... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving Proposed Rule Change, as Modified by Amendment No. 1, To Adopt a New Market Maker Peg Order Available to Exchange...

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

    NASA Astrophysics Data System (ADS)

    Jiang, Jiaqi; Gu, Rongbao

    2016-04-01

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

  11. 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.

  12. 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.

  13. Dream characteristics of stock brokers after a major market downturn.

    PubMed

    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.

  14. A refined fuzzy time series model for stock market forecasting

    NASA Astrophysics Data System (ADS)

    Jilani, Tahseen Ahmed; Burney, Syed Muhammad Aqil

    2008-05-01

    Time series models have been used to make predictions of stock prices, academic enrollments, weather, road accident casualties, etc. In this paper we present a simple time-variant fuzzy time series forecasting method. The proposed method uses heuristic approach to define frequency-density-based partitions of the universe of discourse. We have proposed a fuzzy metric to use the frequency-density-based partitioning. The proposed fuzzy metric also uses a trend predictor to calculate the forecast. The new method is applied for forecasting TAIEX and enrollments’ forecasting of the University of Alabama. It is shown that the proposed method work with higher accuracy as compared to other fuzzy time series methods developed for forecasting TAIEX and enrollments of the University of Alabama.

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

    NASA Astrophysics Data System (ADS)

    Nguyen, Quang

    2013-07-01

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

  16. The influence of liquidity on informational efficiency: The case of the Thai Stock Market

    NASA Astrophysics Data System (ADS)

    Bariviera, Aurelio Fernández

    2011-11-01

    The presence of long-range memory in financial time series is a puzzling fact that challenges the established financial theory. We study the effect of liquidity on the efficiency (measured by the Hurst’s exponent) of the Thai Stock Market. According to our study, we find that: (i) the R/S method could generate spurious long-range dependence, giving the DFA method more reliable estimates of the Hurst’s exponent and (ii) there is a weak relationship between market capitalization and the efficiency of the market, and that the latter is not significantly affected by the presence of foreign investors.

  17. 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…

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

    NASA Astrophysics Data System (ADS)

    Rounaghi, Mohammad Mahdi; Nassir Zadeh, Farzaneh

    2016-08-01

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

  19. 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.

  20. Canonical Sectors and Evolution of Firms in the US Stock Markets

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-01-01

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

  3. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  6. Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study

    PubMed Central

    Acharjee, Animesh

    2016-01-01

    The socio-economic systems today possess high levels of both interconnectedness and interdependencies, and such system-level relationships behave very dynamically. In such situations, it is all around perceived that influence is a perplexing power that has an overseeing part in affecting the dynamics and behaviours of involved ones. As a result of the force & direction of influence, the transformative change of one entity has a cogent aftereffect on the other entities in the system. The current study employs directed weighted networks for investigating the influential relationship patterns existent in a typical equity market as an outcome of inter-stock interactions happening at the market level, the sectorial level and the industrial level. The study dataset is derived from 335 constituent stocks of ‘Standard & Poor Bombay Stock Exchange 500 index’ and study period is 1st June 2005 to 30th June 2015. The study identifies the set of most dynamically influential stocks & their respective temporal pattern at three hierarchical levels: the complete equity market, different sectors, and constituting industry segments of those sectors. A detailed influence relationship analysis is performed for the sectorial level network of the construction sector, and it was found that stocks belonging to the cement industry possessed high influence within this sector. Also, the detailed network analysis of construction sector revealed that it follows scale-free characteristics and power law distribution. In the industry specific influence relationship analysis for cement industry, methods based on threshold filtering and minimum spanning tree were employed to derive a set of sub-graphs having temporally stable high-correlation structure over this ten years period. PMID:27846251

  7. 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.

  8. 76 FR 79262 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Granting Approval of Proposed...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-21

    ... Global and Global Select Markets December 15, 2011. I. Introduction On August 30, 2011, The NASDAQ Stock... on NASDAQ's Global and Global Select Markets. The proposed rule change was published in the Federal... listing on NASDAQ's Global and Global Select Markets in connection with an initial public offering,...

  9. 76 FR 57781 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-09-16

    ... Global Select Markets September 12, 2011. Pursuant to Section 19(b)(1) of the Securities Exchange Act of... listing on the Global and Global Select Markets in connection with an initial public offering, upon... from the New York Stock Exchange (NYSE) to the Global or Global Select Markets (``Eligible...

  10. 76 FR 74084 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-30

    ... open market and a national market system. The proposed rule change also is designed to support the... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change to Exclude All Rights and Warrants from the Pilot Rule for Trading...

  11. 76 FR 13007 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-09

    ... impediments to and perfect the mechanism of a free and open market and a national market system. The proposed... exchange, by expulsion, suspension, limitation of activities, functions, and operations, fine, censure... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and...

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

    PubMed Central

    Shao, Xigao; Wu, Kun; Liao, Bifeng

    2012-01-01

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

  13. ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    Lin, Aijing; Shang, Pengjian

    2016-04-01

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

  15. 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.

  16. Time spans between price maxima and price minima in stock markets

    NASA Astrophysics Data System (ADS)

    Zou, Yongjie; Li, Honggang

    2014-02-01

    We empirically investigate the distribution of time spans between price maxima and price minima in international stock markets, where a time span is defined as the time interval between a local price minimum and a local price maximum, and local price extrema are identified by a method introduced by Preis and Stanley (Preis et al. (2011), Preis (2011), Preis and Stanley (2011, 2010), Preis (2010), Preis and Stanley (2010), Stanley et al. (2010), Preis and Stanley (2009)). The empirical results show that both the tail distributions of time spans from local price maxima to local price minima and the tail distributions of time spans from local price minima to local price maxima yield an exponential distribution. In addition, price rise/fall asymmetry is observed by comparing the values of the exponents of the distribution curves. These results are robust across eight representative stock markets.

  17. Statistical physics in foreign exchange currency and stock markets

    NASA Astrophysics Data System (ADS)

    Ausloos, M.

    2000-09-01

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

  18. Characterizing emerging European stock markets through complex networks: From local properties to self-similar characteristics

    NASA Astrophysics Data System (ADS)

    Caraiani, Petre

    2012-07-01

    We investigate the properties of the returns of the main emerging stock markets from Europe by means of complex networks. We transform the series of daily returns into complex networks, and analyze the local properties of these networks with respect to degree distributions, clustering, or average line length. We further use the clustering coefficients as quantities describing the local structure of the network, and approach them by using multifractal analysis. We find evidence of scale-free networks and multifractality of clustering coefficients.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  20. 76 FR 52724 - Self-Regulatory Organizations; the NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-23

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

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

    ERIC Educational Resources Information Center

    1998

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

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

    NASA Astrophysics Data System (ADS)

    Zeng, Yayun; Wang, Jun; Xu, Kaixuan

    2017-04-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim; Boukadoum, Mounir

    2015-08-01

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

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

    PubMed

    Araújo, Ricardo de A

    2010-12-01

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

  6. Stock-Market Crash Will Not Lead to Severe Reduction in Giving to Colleges, Harvard Economist Predicts.

    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)

  7. 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.

  8. 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.

  9. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... paragraph (h)(3) of this section. (ii) Cessation of a foreign corporation as a PFIC. A United States person... passive foreign investment company (PFIC), including any PFIC stock owned directly or indirectly by an... of a foreign corporation that previously had been a PFIC, and for which a section 1296...

  10. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... paragraph (h)(3) of this section. (ii) Cessation of a foreign corporation as a PFIC. A United States person... passive foreign investment company (PFIC), including any PFIC stock owned directly or indirectly by an... of a foreign corporation that previously had been a PFIC, and for which a section 1296...

  11. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... paragraph (h)(3) of this section. (ii) Cessation of a foreign corporation as a PFIC. A United States person... passive foreign investment company (PFIC), including any PFIC stock owned directly or indirectly by an... of a foreign corporation that previously had been a PFIC, and for which a section 1296...

  12. 26 CFR 1.1296-1 - Mark to market election for marketable stock.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... paragraph (h)(3) of this section. (ii) Cessation of a foreign corporation as a PFIC. A United States person... passive foreign investment company (PFIC), including any PFIC stock owned directly or indirectly by an... of a foreign corporation that previously had been a PFIC, and for which a section 1296...

  13. Comparison of Monetary Policy Actions and Central Bank Communication on Tackling Asset Price Bubbles-Evidence from China's Stock Market.

    PubMed

    Sun, Ou; Liu, Zhixin

    2016-01-01

    We examine the different effects of monetary policy actions and central bank communication on China's stock market bubbles with a Time-varying Parameter SVAR model. We find that with negative responses of fundamental component and positive responses of bubble component of asset prices, contractionary monetary policy induces the observed stock prices to rise during periods of large bubbles. By contrast, central bank communication acts on the market through expectation guidance and has more significant effects on stock prices in the long run, which implies that central bank communication be used as an effective long-term instrument for the central bank's policymaking.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

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

    DOE PAGES

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

    2015-12-07

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  19. 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.

  20. 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.

  1. 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.

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

    PubMed Central

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

    2013-01-01

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

  3. Recession depression: mental health effects of the 2008 stock market crash.

    PubMed

    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.

  4. 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.

  5. 78 FR 4536 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-22

    ... equitable principles of trade, to remove impediments to and perfect the mechanism of a free and open market... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Extend the Operative Date of Recent Changes Made to Rules...

  6. 75 FR 72855 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-26

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify Two Aspects of the Rules and Operation of The NASDAQ Options... transactions in securities, to remove impediments to and perfect the mechanism of a free and open market and...

  7. 75 FR 21069 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-22

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify Fees for Members Using the NASDAQ Market Center April 16, 2010. Pursuant to Section 19(b)(1) of...

  8. 75 FR 16877 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-02

    ... transactions in securities, and to remove impediments to and perfect the mechanism of a free and open market... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify Nasdaq's Rules To Eliminate an Outdated Reference March 26,...

  9. 77 FR 34453 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-11

    ... 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 a Proposed Rule Change To Update the NASDAQ Options Market Message Traffic Mitigation Rule June 5, 2012. Pursuant to Section...

  10. 76 FR 12178 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-04

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Offer Market Data to the Public at No Charge February 25, 2011. Pursuant to Section 19(b)(1) of the...

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

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  12. 78 FR 36800 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-19

    ... COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule Change for the Permanent Approval of a Pilot Program To Permit NASDAQ Options Market To Accept Inbound Options Orders From NASDAQ OMX BX, Inc. June 13, 2013. I. Introduction On April 24, 2013, The NASDAQ...

  13. 76 FR 61129 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-03

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify Fees for Members Using the NASDAQ Options Market September...

  14. Scaling and memory effect in volatility return interval of the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Qiu, T.; Guo, L.; Chen, G.

    2008-12-01

    We investigate the probability distribution of the volatility return intervals τ for the Chinese stock market. We rescale both the probability distribution Pq(τ) and the volatility return intervals τ as Pq(τ)=1/τbar f(τ/τbar ) to obtain a uniform scaling curve for different threshold value q. The scaling curve can be well fitted by the stretched exponential function f(x)∼e, which suggests memory exists in τ. To demonstrate the memory effect, we investigate the conditional probability distribution Pq(τ|τ0), the mean conditional interval <τ|τ0> and the cumulative probability distribution of the cluster size of τ. The results show clear clustering effect. We further investigate the persistence probability distribution P±(t) and find that P-(t) decays by a power law with the exponent far different from the value 0.5 for the random walk, which further confirms long memory exists in τ. The scaling and long memory effect of τ for the Chinese stock market are similar to those obtained from the United States and the Japanese financial markets.

  15. Store Impulse Marketing Strategies and Body Mass Index

    PubMed Central

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

    2015-01-01

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

  16. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

    Roman, H. E.; Porto, M.

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

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

    PubMed

    Sperling, Wolfgang; Bleich, Stefan; Reulbach, Udo

    2008-12-01

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

  20. 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.

  1. 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.

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

    SciTech Connect

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

    2004-05-01

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

  3. Effects of daylight-saving time changes on stock market volatility: a comment.

    PubMed

    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.

  4. Prediction of stock markets by the evolutionary mix-game model

    NASA Astrophysics Data System (ADS)

    Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

    2008-06-01

    This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

  5. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    PubMed Central

    Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

  6. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend.

    PubMed

    Inthachot, Montri; Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

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

    PubMed

    Challet, Damien; Marsili, Matteo

    2003-09-01

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

  8. Forecasting the portuguese stock market time series by using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Isfan, Monica; Menezes, Rui; Mendes, Diana A.

    2010-04-01

    In this paper, we show that neural networks can be used to uncover the non-linearity that exists in the financial data. First, we follow a traditional approach by analysing the deterministic/stochastic characteristics of the Portuguese stock market data and some typical features are studied, like the Hurst exponents, among others. We also simulate a BDS test to investigate nonlinearities and the results are as expected: the financial time series do not exhibit linear dependence. Secondly, we trained four types of neural networks for the stock markets and used the models to make forecasts. The artificial neural networks were obtained using a three-layer feed-forward topology and the back-propagation learning algorithm. The quite large number of parameters that must be selected to develop a neural network forecasting model involves some trial and as a consequence the error is not small enough. In order to improve this we use a nonlinear optimization algorithm to minimize the error. Finally, the output of the 4 models is quite similar, leading to a qualitative forecast that we compare with the results of the application of k-nearest-neighbor for the same time series.

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

    NASA Astrophysics Data System (ADS)

    Manahov, Viktor; Hudson, Robert

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Suzuki, Tomoya; Ohkura, Yuushi

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Keller, Heath; Cox, James R.

    2004-04-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-01-01

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

  19. 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.

  20. 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.

  1. 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.

  2. Relationship between suicide rate and economic growth and stock market in the People’s Republic of China: 2004–2013

    PubMed Central

    Yin, Honglei; Xu, Lin; Shao, Yechang; Li, Liping; Wan, Chengsong

    2016-01-01

    Objectives The objective of this study was to estimate the features of suicide rate and its association with economic development and stock market during the past decade in the People’s Republic of China. Methods Official data were gathered and analyzed in the People’s Republic of China during the period 2004–2013. Nationwide suicide rate was stratified by four year age-groups, sex, urban/rural areas, and regions (East, Central, and West). Annual economic indexes including gross domestic product (GDP) per capita and rural and urban income per capita were all adjusted for inflation. Variation coefficient of market index (VCMI) was also included as an economic index to measure the fluctuation of the stock market. Negative binomial regression was performed to examine the time trend of region-level suicide rates and effects of sex, age, urban/rural area, region, and economic index on the suicide rates. Results Suicide rates of each age-group, sex, urban/rural area, and region were generally decreased from 2004 to 2013, while annual GDP per capita and rural and urban income per capita were generally increased by year. VCMI fluctuated largely, which peaked around 2009 and decreased after that time. Negative binomial regression showed that the decreased suicide rate in East and Central rural areas was the main cause of the decrease in suicide rate in the People’s Republic of China. Suicide rate in the People’s Republic of China for the study period increased with age and was higher in rural than in urban area, higher in males than in females, and the highest in the Central region. When GDP per capita increased by 2,787 RMB, the suicide rate decreased by 0.498 times. VCMI showed no significant relationship with suicide rate in the negative binomial regression. Conclusion Suicide rate decreased in 2004–2013; varied among different age-groups, sex, urban/rural areas, and regions; and was negatively associated with the economic growth in the People’s Republic of

  3. 77 FR 75229 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Designation of a Longer...

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    ... Connectivity for Co-Located Clients December 12, 2012. On October 10, 2012, The NASDAQ Stock Market LLC... proposed rule change to establish fees for new optional wireless connectivity for co-located clients. The... connectivity for co-located clients. ] Accordingly, the Commission, pursuant to Section 19(b)(2) of the...

  4. Stocking density effects on production characteristics and body composition of market size cobia, Rachycentron canadum, reared in recirculating aquaculture systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Production density in excess of a critical threshold can result in a negative relationship between stocking density and fish production. This study was conducted to evaluate production characteristics of juvenile cobia Rachycentron canadum, reared to market size in production-scale recirculating aq...

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    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE... Rights and Warrants January 23, 2012. Pursuant to Section 19(b)(1) of the Securities Exchange Act of 1934... NASDAQ Stock Market LLC (``Exchange'') filed with the Securities and Exchange Commission...

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    ... 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 Its Corporate Governance Rules July 19, 2012. I. Introduction On May 17, 2012, The...

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    2011-10-18

    ... From the Federal Register Online via the Government Publishing Office ] SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change Relating to Customer Rebates To Add Liquidity September 22, 2011. Correction In notice document...

  16. 77 FR 40926 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-11

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

  17. 77 FR 58199 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-19

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Delete NASDAQ Rule 7032 September 13, 2012. Pursuant to Section 19(b)(1) of the Securities Exchange Act of...

  18. 76 FR 11548 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-02

    ... 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 Regarding the NASDAQ Order Imbalance Snapshot February 24, 2011. Pursuant to Section 19(b)(1) of the...

  19. 76 FR 64411 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

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    2011-10-18

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Modify the Minimum Quantity Order October 12, 2011. Pursuant to Section 19(b)(1) of the Securities Exchange...

  20. 76 FR 12171 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-04

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate Effectiveness of Proposed Rule Change To Make Clarifying Changes to Rule 7002 Concerning the Application and Collection of the Sales Fee February...