Relevant bibliographies by topics / Stock market behavior

Academic literature on the topic 'Stock market behavior'

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Published: 18 May 2024

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Journal articles on the topic "Stock market behavior"

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Rahma Tri Benita, Siti Damayanti, and Irwan Adi Ekaputra. "Information Distribution and Informed Trading in Mixed and Islamic Capital Markets." International Journal of Business and Society 21, no. 3 (April 27, 2021): 1333–51. http://dx.doi.org/10.33736/ijbs.3353.2020.

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The correlation between volume and frequency with return volatility can explicate the information distribution process and informed traders' transaction behavior in a stock market. In this study, the Indonesian stock market represents the mixed market, while the Saudi Arabian stock market represents the Islamic market. We find that 94% and 96% of sharia-compliant stocks in Indonesia and Saudi Arabia follow the Mixture of Distribution Hypothesis (MDH). Consequently, we may conclude that sharia-compliant stocks in both markets are informationally efficient. However, we find that informed traders tend to behave differently in both markets. In the Indonesian market, informed traders exhibit competitive behavior in 95% of shariacompliant stocks and strategic transaction behavior in only 5% of the stocks. In contrast, in the Saudi Arabian market, we find that informed traders exhibit competitive behavior in only 38% of the stocks and strategic behavior in 62% of the stocks. The findings suggest that social and religious contexts may affect market participants' behavior.
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BenMabrouk, Houda. "Cross-herding behavior between the stock market and the crude oil market during financial distress." Managerial Finance 44, no. 4 (April 9, 2018): 439–58. http://dx.doi.org/10.1108/mf-09-2017-0363.

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Purpose The purpose of this paper is to investigate herding behavior around the crude oil market and the stock market and the possible cross-herding behavior between the two markets. The analysis examines also the herding behavior during financial turmoil and includes the investor sentiment and market volatility. Design/methodology/approach The authors use a modified version of the cross-sectional standard deviation and the cross-sectional absolute deviation to include investor sentiment, financial crisis and market volatility. Findings The authors find that the volatility of the stock market reduces the herding behavior around the oil market and boosts that around the stock market. However, the investors’ sentiment reduces the herding around the stock market and boosts that around the crude oil market. Consequently, the authors can conclude that the herding behavior around the two markets moves inversely and the herding in each market is enhanced by the lack of information in the other market. Research limitations/implications This paper is limited to the herding of stocks around the crude oil market and ignores the possible herding of commodities around the oil market. Originality/value The originality of the paper rests on the study of the possible cross-herding behavior between the oil market and the stock market especially during financial turmoil.
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Ruhani, Fatima, Md Aminul Islam, and Tunku Salha Tunku Ahmad. "Review of the Literatures on Stock Price Behavior of Malaysia." International Journal of Islamic Business & Management 2, no. 2 (December 19, 2018): 32–38. http://dx.doi.org/10.46281/ijibm.v2i2.219.

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Stock price behavior is one of the core concerns of researchers and finance scholars from more than a half-century of years. Most of the times, they have tried to identify unexplored anomalies that could be used to explain stock price movement in the different stock market. As a result, we have found different models and theories relating to stock price behavior as well as the efficiency of the stock market. Malaysian stock market is considered the second among the largest South East Asian stock markets according to its domestic market capitalization. A considerable number of researches have already been done on the stock price behavior of Malaysian stock market. This study reviews the existing literatures on the stock price behavior of Malaysian stock markets within two wings, literatures on efficient market hypothesis of Malaysian market and the effect of economic and financial variables on the stock price.
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Elshqirat, Mohammad K. "Investors’ Happiness and Stock Market." International Business Research 17, no. 2 (February 22, 2024): 23. http://dx.doi.org/10.5539/ibr.v17n2p23.

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Investor feelings can affect their investing behavior in the market which may impact the stocks prices and volatility. Investor’s happiness represents a very important feeling that can affect investing behavior. The main question here is whether the launching of a country wide happiness program can affect the investors’ behavior in the stock market and consequently the prices and volatility of stocks. The methodology followed to answer this question was a quantitative methodology using data from the stock market of United Arab Emirates for the years 2015 – 2017 and information about the country’s “national program for happiness and wellbeing” that was started in 2016. Data were analyzed using paired t-test and descriptive statistics. Results revealed that happiness can affect the volatility of stock prices but not the returns of stocks in the market.
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UPADHYAY, RITESH. "Factors affecting the Investment behavior of Stock Market Investors: A Quantitative Investigation." International Journal of Management, IT and Engineering 08, no. 04 (2018): 300–307. http://dx.doi.org/10.36893/ijmie.2018.v8i4.300-307.

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One of the world's most active and complicated financial markets is the stock market. There is a sizable quantity of money invested in various stocks and securities due to the market's participation by millions of investors. Several variables, including monetary conditions, political stability, corporate performance, and personal preferences, have an impact on how investors behave in the stock market. Investors must make sound financial decisions to maximize profits and reduce risks and stock market investment behavior is a critical component of that process. It's essential for investors, financial advisors, and legislators to comprehend the variables that influence investment behavior. The way Indian stock market investors invest is influenced by a number of factors. Individual investor preferences, risk tolerance, and investment goals all have a big impact on how they behave when it comes to investing. The ability to manage the complicated and dynamic financial market can be aided by having a thorough awareness of the numerous elements that influence investing behavior in the Indian stock market.
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Silitonga, Ririn Stefani, Isfenti Sadalia, and Amlys Syahputra Silalahi. "Analysis of Herding Behavior in Developing Countries." International Journal of Research and Review 8, no. 12 (December 24, 2021): 614–21. http://dx.doi.org/10.52403/ijrr.20211274.

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When faced with market uncertainty and high volatility in financial markets, the potential for herding behavior in the stock market is likely to increase. This will cause instability in the financial market and also the economy of a country. The purpose of this study is to analyze herding behavior in the stock markets of developing countries including China, the Philippines, India, Indonesia, Korea, Malaysia, Pakistan, Taiwan and Thailand. This type of research is quantitative research and the population in this study is stocks listed on the Stock Exchanges of all developing countries with a time period from January 2016 to December 2020. The sampling method used is purposive sampling. The data used are monthly stock index data, VIX, world oil prices and the fed funds rate. Data analysis was performed through panel data regression, which is a combination of cross section and time series using the Eviews program. The results showed that there was no herding behavior in developing countries. The result of this research is that the fed fund rate has a significant effect on herding behavior in developing countries, especially in Indonesia. Keywords: Herding, Market Volatility, Oil Price, Fed Fund Rate.
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Wei-Shan Hu, John, Yen-Hsien Lee, and Ying-Chuang Chen. "Mutual fund herding behavior and investment strategies in Chinese stock market." Investment Management and Financial Innovations 15, no. 2 (May 5, 2018): 87–95. http://dx.doi.org/10.21511/imfi.15(2).2018.08.

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This investigation studies the impact of mutual fund herding on the returns achieved by contrarian strategy from 1990 to 2015 in the Chinese stock market. The relationship between the profit gained by the contrarian strategy and the macroeconomic environment is also examined. First, the returns of the contrarian strategy in China’s stock market are found to be significant. Second, most loser stocks with a high degree of mutual fund herding outperform loser stocks with a low degree of mutual fund herding, revealing that the profitability of an investment portfolio depends on the degree of mutual fund herding. Third, investors should buy loser stocks with a high degree of herding and sell winner stocks with a low degree of herding during a two-year formation period, over which zero-cost contrarian strategies yield the significantly highest return. Finally, the payoff of contrarian strategies is positively related to the herding effect and negatively related to macroeconomic variables.
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Rizal, Nora Amelda, and Mirta Kartika Damayanti. "HERDING BEHAVIOR IN THE INDONESIAN ISLAMIC STOCK MARKET." Journal of Islamic Monetary Economics and Finance 5, no. 3 (November 1, 2019): 673–90. http://dx.doi.org/10.21098/jimf.v5i3.1079.

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Indonesia Stock Exchange provides Islamic stocks for Muslim investors who want toinvest, with the first Islamic stock index in Indonesia being Jakarta Islamic Index or JIIthat consists of thirty of the most liquid Islamic stocks. The market capitalization of JIItends to increase every year. This paper examines the presence of herding behavior inemerging Islamic stock market of Indonesia using daily return of Indonesia CompositeIndex and JII from October 6, 2000 to October 5, 2018. Herding behavior could generallytrigger shifting market prices from equilibrium values. Herding behavior may beidentified from the relation between stock return dispersion and market return. Stockreturn dispersion is measured using Cross Sectional Absolute Deviation or CSAD.Generalized Auto Regressive Conditional Heteroskedasticity or GARCH method isused to detect herding behavior. GARCH does not see heteroskedasticity as a problem,instead uses it to make a model. The result indicates that herding behavior exist inIslamic stock market of Indonesia. Asymmetric herding occurs in Indonesia Islamicstock market where herding behavior exists during falling market condition only.
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Aremu Akinde, Mukail, Eriki Peter, and Ochei Ailemen Ikpefan. "Portfolio selection strategies and cognitive psychology biases: a behavioral evidence from the Nigerian equity market." Investment Management and Financial Innovations 15, no. 3 (September 14, 2018): 267–82. http://dx.doi.org/10.21511/imfi.15(3).2018.22.

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The empirical evidence in the developed equity markets such as the United States, the United Kingdom, Germany, Japan and emerging markets had pronounced that there are institutional and individual investors’ cognitive psychology and mental biases in favor of the Growth Stocks, that is, the Growth Stocks are always preferred to the Value Stocks by the investors. The investors most times prefer the Growth Stocks to the Value Stocks irrespective of the stock fundamentals behavior in the equity market. The paper investigated whether Cognitive Psychology and Mental biases affect Portfolio Selection strategies using the Growth or the Value Stocks investment styles in the Nigerian Stock Market. In the study, the summary of the primary data was described and Multinomial Logistic Regression (MLR) models were adopted to make inferential decisions. The paper collected primary data through questionnaire administered to individual and institutional investors on the floor of Nigeria Stock Exchange (NSE). The findings from the analyses conducted confirmed a strong existence of Cognitive Psychology and mental biases in favor of the Growth Stocks in the Nigerian Equity Market. Investors had more belief in Growth Stocks than the Value Stocks notwithstanding the behavior of the market fundamentals. The study recommended that investors should seriously consider occurrences and performance fundamentals in Portfolio Selection in the Nigerian Equity Market.
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Hami, Mustapha El, and Ahmed Hefnaoui. "Analysis of Herding Behavior in Moroccan Stock Market." Journal of Economics and Behavioral Studies 11, no. 1(J) (March 10, 2019): 181–90. http://dx.doi.org/10.22610/jebs.v11i1(j).2758.

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Frontier markets, particularly the Moroccan financial market, are characterized by a narrowness of market, inability to absorb erratic price fluctuations and the low liquidity of securities that encourage investors to herd and imitate those who have all the information about the market. A quantitative research approach was used to analyze the existence of herding n Moroccan stock market. The daily data used in this study concerns the period from 04/01/2010 to 29/12/2017 and contains the daily returns of the MASI and a total of 43 traded stocks. Statistical and econometric methods such as multidimensional scaling and Cross-sectional absolute deviation were used. Subsequently, after the regression models were examined, findings indicated that the first stocks with the highest similarity to the index return are BMCE, BCP, IAM, ATW and CMSR, and the first stocks with the highest dissimilarity are PAP, IBC and SNP, This will have to allow investors to choose profitable alternatives and avoid those that present a possible risk. The results did also show the existence of herding in the Moroccan stock market both upward and downward. This finding was supported by the clear existence of a non-linearity between market performance and CSAD measurement, which confirms the prediction of a non-linear inversion relationship between CSAD and 𝑅𝑚. This could be due to the low level of transparency that prevails in frontier stock exchanges and reduces the quality of their information environment, which leads investors not to react rationally and to draw information from the transactions of their peers.
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Dissertations / Theses on the topic "Stock market behavior"

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Koh, Sung Soo. "The Korean stock market structure, behavior, and test of market efficiency /." Online version, 1989. http://ethos.bl.uk/OrderDetails.do?did=1&uin=uk.bl.ethos.352906.

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FILHO, HERALDO PIMENTA BORGES. "STOCK MARKET BEHAVIOR PREDICTION USING FINANCIAL NEWS IN PORTUGUESE." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=25123@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
Um conjunto de teorias financeiras, tais como a hipótese do mercado eficiente e a teoria do passeio aleatório, afirma ser impossível prever o futuro do mercado de ações baseado na informação atualmente disponível. Entretanto, pesquisas recentes têm provado o contrário ao constatar uma relação entre o conteúdo de uma notícia corrente e o comportamento de um ativo. Nosso objetivo é projetar e implementar um algoritmo de predição que utiliza notícias jornalísticas sobre empresas de capital aberto para prever o comportamento de ações na bolsa de valores. Utilizamos uma abordagem baseada em aprendizado de máquina para a tarefa de predição do comportamento de um ativo nas posições de alta, baixa ou neutra, utilizando informações quantitativas e qualitativas, como notícias sobre o mercado financeiro. Avaliamos o nosso sistema em um dataset com seis mil notícias e nossos experimentos apresentam uma acurácia de 68.57 porcento para a tarefa.
A set of financial theories, such as the eficient market hypothesis and the theory of random walk, says it is impossible to predict the future of the stock market based on currently available information. However, recent research has proven otherwise by finding a relationship between the content of a news and current behavior of an stock. Our goal is to develop and implement a prediction algorithm that uses financial news about joint-stock company to predict the stock s behavior on the stock exchange. We use an approach based on machine learning for the task of predicting the behavior of an stock in positions of up, down or neutral, using quantitative and qualitative information, such as financial. We evaluate our system on a dataset with six thousand news and our experiments indicate an accuracy of 68.57 percent for the task.
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Monte, Brent M. "Chaos and the stock market." CSUSB ScholarWorks, 1994. https://scholarworks.lib.csusb.edu/etd-project/860.

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Guo, Enyang. "An empirical examination of price behavior on the Hong Kong stock market." Diss., Virginia Tech, 1990. http://hdl.handle.net/10919/39803.

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This dissertation examines stock price behavior on the Hong Kong stock market in terms of normality of returns and the efficiency of that market. The results reveal that the Hong Kong stock market is efficient, although the degree of efficiency is somewhat different from what has been found for securities traded in the U.S. market. Moreover, it was found that as a small but active stock market, the Hong Kong market is sensitive and highly vulnerable to international events. The study also analyzes the relationship among different national equity markets, i.e., the U.S., the U.K., Japan, and Hong Kong. The results show that a substantial amount of multi-lateral interaction is present among national equity markets. In addition, some common seasonal patterns of stock price movements appear across the different national markets, and innovation transmissions from market to market are significant and efficient. The study provides added support to the hypothesis of an integrated world financial market.
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Nelson, Daniel B. "The time series behavior of stock market volatility and returns." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14363.

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Pietarinen, J. (Juhani). "Overconfidence and investor trading behavior in the Finnish stock market." Master's thesis, University of Oulu, 2014. http://urn.fi/URN:NBN:fi:oulu-201404241308.

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Empirical studies have analyzed how investors trade and perform in the financial markets. The studies show that rational trading needs do not explain the excessive manner of trading shown by the investors. Theoretical models offer overconfidence as one of the explanations for irrational trading behavior. Overconfidence is a psychological trait, argued to cause the investors to misinterpret useful information, which leads to an increase in trading activity and hurts their performance. In this study we analyze over 1.5 million Finnish trading records from the beginning of 1995 to the end of 2010. We evaluate the differences in trading behavior between males and females and with investors of diverse ages. We find that men trade securities more frequently and with higher turnover than females. Consistently with our reference studies we find that the level of turnover decreases as the investors age. We also analyze the profitability effects of trading by calculating raw returns and abnormal returns. The abnormal returns are adjusted with a passive benchmark portfolio. Earlier studies show that the more active trading of males reduces their abnormal returns. Our abnormal return ratios do not support this finding. However, we find consistently that the raw returns are higher for females than males. Females also hold portfolios with lower volatility than males. Finally, we find consistently with the models of overconfidence by Odean (1998b) and Gervais and Odean (2001) that the trading skill seems to get better with experience. Older investors receive higher raw returns and trade less, resulting in lower portfolio turnover. The transition in trading behavior may be an outcome of learning.
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Tan, Lin Chiang Thomas C. "Empirical analysis of Chinese stock market behavior : evidence from dynamic correlations, herding behavior, and speed of adjustment /." Philadelphia, Pa. : Drexel University, 2005. http://dspace.library.drexel.edu/handle/1860/514.

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Zhu, Jiang, and 朱江. "Stock market behavior in China: evidence fromrights issue and corporate restructuring." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B31246357.

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Choi, Hyung-Suk. "Three essays on stock market seasonality." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26597.

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Thesis (Ph.D)--Management, Georgia Institute of Technology, 2009.
Committee Chair: Eun, Cheol; Committee Member: Jayaraman, Narayanan; Committee Member: Kilic, Rehim; Committee Member: Lee, Suzanne; Committee Member: Wang, Qinghai. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Zhou, Ting Yu. "An examination of herd behavior in the Hong Kong stock market." Thesis, University of Macau, 2007. http://umaclib3.umac.mo/record=b1872933.

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Books on the topic "Stock market behavior"

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Ahmed, M. Farid. Stock market behavior in Bangladesh. [Dhaka]: Bureau of Business Research, University of Dhaka, 1992.

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Marsh, Terry A. Dividend behavior for the aggregate stock market. Cambridge, Mass: Massachusetts Institute of Technology, Alfred P. Sloan School of Management, 1985.

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Marsh, Terry A. Dividend behavior for the aggregate stock market. Cambridge, Mass: Massachusetts Institute of Technology, Sloan School of Management, 1986.

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Wooi, Hooy Chee, ed. Understanding the behavior of the Malaysian stock market. Serdang: Universiti Putra Malaysia Press, 2005.

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1967-, Alvarez Cesar, ed. How markets really work: A quantitative guide to stock market behavior. Hoboken, New Jersey: John Wiley & Sons, Inc., 2012.

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Lakonishok, Josef. Investor behavior and the option market. Cambridge, Mass: National Bureau of Economic Research, 2004.

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Understanding the stock market. Broomall, Pa: Mason Crest Publishers, 2011.

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Lehman, Richard. Far from random: Using investor behavior and trend analysis to forecast market movement. New York: Bloomberg Press, 2009.

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Far from random: Using investor behavior and trend analysis to forecast market movement. New York: Bloomberg Press, 2009.

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Lehman, Richard. Far from random: Using investor behavior and trend analysis to forecast market movement. New York: Bloomberg Press, 2009.

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Book chapters on the topic "Stock market behavior"

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Fernholz, E. Robert. "Stock Market Behavior and Diversity." In Stochastic Portfolio Theory, 25–42. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4757-3699-1_2.

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Gabbioneta, Claudia, Pietro Mazzola, and Davide Ravasi. "Corporate Reputation and Stock Market Behavior." In Reputation Management, 215–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19266-1_20.

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Raczynski, Stanislaw. "Stock Market: Uncertainty and Catastrophes." In Catastrophes and Unexpected Behavior Patterns in Complex Artificial Populations, 79–101. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2574-9_5.

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van Norden, Simon, and Huntley Schaller. "Speculative Behavior, Regime-Switching, and Stock Market Crashes." In Dynamic Modeling and Econometrics in Economics and Finance, 321–56. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5129-4_15.

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Edmonds, Bruce. "Exploring the Value of Prediction in an Artificial Stock Market." In Anticipatory Behavior in Adaptive Learning Systems, 262–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45002-3_15.

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Gurav, Uma, and Nandini Sidnal. "Predict Stock Market Behavior: Role of Machine Learning Algorithms." In Intelligent Computing and Information and Communication, 383–94. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7245-1_38.

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Franke, Markus, Bettina Hoser, and Jan Schröder. "On the Analysis of Irregular Stock Market Trading Behavior." In Data Analysis, Machine Learning and Applications, 355–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78246-9_42.

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Trifan, Ruxandra. "Insider Trading and Stock Market Behavior: Evidence from Romania." In Eurasian Studies in Business and Economics, 201–14. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77438-7_12.

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Gerke, Wolfgang, and Horst Bienert. "Market Design, Trading Behavior and Price Discovery — An Experimental Stock Market Model." In Contributions to Management Science, 3–25. Heidelberg: Physica-Verlag HD, 1999. http://dx.doi.org/10.1007/978-3-642-58664-4_1.

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Kodia, Zahra, and Lamjed Ben Said. "Multi-agent Simulation of Investor Cognitive Behavior in Stock Market." In Advances in Intelligent and Soft Computing, 90–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00487-2_10.

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Conference papers on the topic "Stock market behavior"

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Marine, FJ, JC Bribiesca, and A. Arrona-Palacios. "BEHAVIORAL APPROACH ON THE MEXICAN STOCK MARKET MODELED THROUGH PLSSEM." In The 7th International Conference on Education 2021. The International Institute of Knowledge Management, 2021. http://dx.doi.org/10.17501/24246700.2021.7121.

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This paper analyzes the Mexican Stock Market indicators and their relationships to study the ten most representative stocks in The Mexican Stock Market Index between 2011 to 2020, reflecting behavioral effects using the Mexican Volatility Index. A longitudinal research design of 119 observations sample size is modeled monthly; this sample was transformed into categorical variables to reflect emotional stages. The main objective was to analyze the stock market emotions applying a novel approach to create latent behavioral variables using current Mexican behavioral indicators as reflexive constructs. There is a lack of knowledge in using different techniques to model financial behavior in financial and economic modeling. The typical techniques employed to model market time series have been simple and multiple regression, broadly used in this science. Since behavioral science appliances, there is a need for evolution to modeling the complex nature of behavior. Partial Least Squares and Structural Equation Models (PLS-SEM) can manage different scales, complex relations, reflexive or formative models, non-normal data, and small samples. Possible because of the lack of knowledge al flexibility of PLSSEM models, there is an evident lack in the use of this methodology in modern research and financial teaching, so a new methodology for modeling financial data is exposed that can resolve problems in financial researching and teaching. It is relevant to show a way of modeling emotional financial markets; it is recommended the use of this modeling in different kind of data, different countries, characteristics, sectors, industries, or variables, or any possible application in different sciences with the same problems of assumptions like in economics sciences. Keywords: Investor behavior, risk, market efficiency, Structural Equations, and Partial Least Squares methods
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Nikulina, Victoria, and Maxim Bouev. "MEASURING HERDING BEHAVIOR IN THE RUSSIAN STOCK MARKET." In 35th International Academic Conference, Barcelona. International Institute of Social and Economic Sciences, 2018. http://dx.doi.org/10.20472/iac.2018.935.036.

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Sarangi, Prakash Kumar, Jayashree Mohanty, Srikanta Kumar Mohapatra, and Premananda Sahu. "Computing Stock Market Price Behavior Using Machine Learning Approach." In 2023 6th International Conference on Information Systems and Computer Networks (ISCON). IEEE, 2023. http://dx.doi.org/10.1109/iscon57294.2023.10112128.

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Alsedrah, Ibrahim. "Behavioral Finance And Speculative Behavior Of Investors: Evidence From Saudi Stock Market." In IEBMC 2017 – 8th International Economics and Business Management Conference. Cognitive-Crcs, 2018. http://dx.doi.org/10.15405/epsbs.2018.07.02.65.

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Bandaranayake, B. M. E. P., M. K. P. L. Perera, W. R. Lakmini, N. Nageswaran, S. D. Perera, A. Gunawardana, and N. A. Perera. "Detecting possible outliers in the Colombo stock exchange." In International Conference on Business Research. Business Research Unit (BRU), 2023. http://dx.doi.org/10.31705/icbr.2023.11.

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Insider trading poses a significant challenge for stock markets, including the Colombo Stock Exchange, as it undermines investor confidence. The purpose of this study is to develop an innovative methodology that can effectively identify and flag suspicious transactions and investors. The proposed approach considers a multitude of parameters that influence the behavior of insider traders, which have been overlooked in current detection methods. This method mainly focuses on assessing the change in the trading behavior of investors in relation to price-sensitive corporate events compared to their past behavior and the behavior of peer investors. As an initiation, we used trade data for the year 2016- 2021 and identified potential suspicious investors and transactions. By utilizing this approach, we seek to enhance the effectiveness of identifying insider trading and mitigate its adverse effects on the market.
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Candraningrat, Ica Rika. "Analysis of Herding Behavior in the Indonesian Capital Stock Market." In Proceedings of the 1st Aceh Global Conference (AGC 2018). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/agc-18.2019.59.

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Por-Shen Lai and Hsin-Chia Fu. "A polygon description based similarity measurement of stock market behavior." In 2007 IEEE Congress on Evolutionary Computation. IEEE, 2007. http://dx.doi.org/10.1109/cec.2007.4424553.

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Júnior, Manoel Marcondes de Oliveira Lima, Sofiani Labidi, and Pedro Brandão Neto. "A HYBRID MODEL FOR PREDICTING THE BEHAVIOR OF STOCK MARKET." In 10th CONTECSI International Conference on Information Systems and Technology Management. Sao Paulo: TECSI, 2013. http://dx.doi.org/10.5748/9788599693094-10contecsi/rf-477.

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Lei, Yuanzhi. "The Impact of Herd Behavior on the Chinese Stock Market." In 2021 International Conference on Public Art and Human Development ( ICPAHD 2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.220110.159.

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Bi, Tao, and Gong Cheng. "Trading volume, realized volatility and signed jump: Evidence form China's stock market." In 2014 International Conference on Behavior, Economic and Social Computing (BESC). IEEE, 2014. http://dx.doi.org/10.1109/besc.2014.7059520.

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Reports on the topic "Stock market behavior"

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Pindyck, Robert. Risk Aversion and Determinants of Stock Market Behavior. Cambridge, MA: National Bureau of Economic Research, May 1986. http://dx.doi.org/10.3386/w1921.

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Shiller, Robert. Investor Behavior in the October 1987 Stock Market Crash: Survey Evidence. Cambridge, MA: National Bureau of Economic Research, November 1987. http://dx.doi.org/10.3386/w2446.

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Campbell, John, and John Cochrane. By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior. Cambridge, MA: National Bureau of Economic Research, January 1995. http://dx.doi.org/10.3386/w4995.

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Shiller, Robert, Fumiko Konya, and Yoshiro Tsutsui. Investor Behavior in the October 1987 Stock Market Crash: The Case of Japan. Cambridge, MA: National Bureau of Economic Research, August 1988. http://dx.doi.org/10.3386/w2684.

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Soloviev, Vladimir, Andrii Bielinskyi, Oleksandr Serdyuk, Victoria Solovieva, and Serhiy Semerikov. Lyapunov Exponents as Indicators of the Stock Market Crashes. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4131.

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The frequent financial critical states that occur in our world, during many centuries have attracted scientists from different areas. The impact of similar fluctuations continues to have a huge impact on the world economy, causing instability in it concerning normal and natural disturbances [1]. The an- ticipation, prediction, and identification of such phenomena remain a huge chal- lenge. To be able to prevent such critical events, we focus our research on the chaotic properties of the stock market indices. During the discussion of the re- cent papers that have been devoted to the chaotic behavior and complexity in the financial system, we find that the Largest Lyapunov exponent and the spec- trum of Lyapunov exponents can be evaluated to determine whether the system is completely deterministic, or chaotic. Accordingly, we give a theoretical background on the method for Lyapunov exponents estimation, specifically, we followed the methods proposed by J. P. Eckmann and Sano-Sawada to compute the spectrum of Lyapunov exponents. With Rosenstein’s algorithm, we com- pute only the Largest (Maximal) Lyapunov exponents from an experimental time series, and we consider one of the measures from recurrence quantification analysis that in a similar way as the Largest Lyapunov exponent detects highly non-monotonic behavior. Along with the theoretical material, we present the empirical results which evidence that chaos theory and theory of complexity have a powerful toolkit for construction of indicators-precursors of crisis events in financial markets.
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Соловйов, В. М., and В. В. Соловйова. Моделювання мультиплексних мереж. Видавець Ткачук О.В., 2016. http://dx.doi.org/10.31812/0564/1253.

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From the standpoint of interdisciplinary self-organization theories and synergetics analyzes current approaches to modeling socio-economic systems. It is shown that the complex network paradigm is the foundation on which to build predictive models of complex systems. We consider two algorithms to transform time series or a set of time series to the network: recurrent and graph visibility. For the received network designed dynamic spectral, topological and multiplex measures of complexity. For example, the daily values the stock indices show that most of the complexity measures behaving in a characteristic way in time periods that characterize the different phases of the behavior and state of the stock market. This fact encouraged to use monitoring and prediction of critical and crisis states in socio-economic systems.
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Cavallo, Eduardo A., Ana Cepeda, and Ugo Panizza. Environmental Damage News and Stock Returns: Evidence from Latin America. Inter-American Development Bank, May 2024. http://dx.doi.org/10.18235/0012962.

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This paper studies the interplay between environmental performance and financial valuation of firms in Latin America and the Caribbean. We provide insights into how environmental considerations are integrated into financial decision-making and investor behavior by analyzing the stock market reaction to environmental news of firms with different levels of carbon emission intensity. We find that high emission intensity firms tend to underperform after the release of environmental damage news. Our baseline estimates indicate that, after the release of such news, firms at the 75th percentile of the distribution of emission intensity experience stock returns that are 17% lower than those of firms at the 25th percentile of the distribution of emission intensity. These results suggest that investors care about and price carbon risk, but only when this risk is salient.
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Muller, Leslie A., and John A. Turner. The Persistence of Employee 401(k) Contributions Over a Major Stock Market Cycle: Evidence on the Limited Power of Inertia on Savings Behavior. W.E. Upjohn Institute, April 2011. http://dx.doi.org/10.17848/wp11-174.

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Carrasco, Marine, and N'golo Koné. Test for Trading Costs Effect in a Portfolio Selection Problem with Recursive Utility. CIRANO, January 2023. http://dx.doi.org/10.54932/bjce8546.

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This paper addresses a portfolio selection problem with trading costs on stock market. More precisely, we develop a simple GMM-based test procedure to test the significance of rading costs effect in the economy with a áexible form of transaction costs. We also propose a two-step procedure to test overidentifying restrictions in our GMM estimation. In an empirical analysis, we apply our test procedures to the class of anomalies used in Novy-Marx and Velikov (2016). We show that transaction costs have a significant effect on investors behavior for many anomalies. In that case, investors significantly improve the out-of-sample performance of their portfolios by accounting for trading costs.
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López-Piñeros, Martha Rosalba, Norberto Rodríguez-Niño, and Miguel Sarmiento. Política monetaria y flujos de portafolio en una economía de mercado emergente. Banco de la República de Colombia, May 2022. http://dx.doi.org/10.32468/be.1200.

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Portfolio flows are an important source of funding for both private and public agents in emerging market economies. In this paper, we study the influence of changes in domestic and US monetary policy rates on portfolio inflows in an emerging market economy and discriminate among fixed income instruments (government securities and other corporate bonds) and variable income instruments (shares). We employ monthly data on portfolio inflows of non-residents in Colombia during the period 2011-2020 and identify the monetary policy shocks using a SVAR model with long-run restrictions. We find a positive and statistically significant response of portfolio inflows in government securities and corporate bonds to changes in both domestic and US monetary policy rates. Portfolio inflows in the stock market react more to changes in the inflation rate and do not react to changes in monetary policy rates. Our findings are consistent with the predictions of the interest rate channel and reestablish the predominant role of inflation rate in driving portfolio inflows. The results suggest that domestic and US monetary policy actions have an important effect on the behavior of portfolio inflows in emerging economies.
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