Stock Market Behavior Research Articles

RESPONSE OF STOCK MARKET DURING COVID-19 AND 2008 FINANCIAL CRISIS: A COMPARATIVE EVIDENCE FROM BRICS NATIONS

This study attempts to examine the response of stock markets amid the COVID-19 pandemic on prominent stock markets of the BRICS nation and compare it with the 2008 financial crisis by employing the GARCH and EGARCH model. First, average and variance of stock returns are tested for differences before and after the pandemic, t-test and F-test were applied. Further, OLS regression was applied to study the impact of COVID-19 on the standard deviation of returns using daily data of total cases, total deaths, and returns of the indices from the date on which the first case was reported till June 2020. Second, GARCH and EGARCH models are employed to compare the impact of COVID-19 and the 2008 financial crisis on the stock market volatility by using the data of respective stock indices for the period 2005–2020. The results suggest that the increasing number of COVID-19 cases and reported death cases hurt stock markets of the five countries except for South Africa in the latter case. The findings of the GARCH and EGARCH model indicate that for India and Russia, the financial crisis of 2008 has caused more stock volatility whereas stock markets of China, Brazil, and South Africa have been more volatile during the COVID-19 pandemic. The study has practical implications for investors, portfolio managers, institutional investors, regulatory institutions, and policymakers as it provides an understanding of stock market behavior in response to a major global crisis and helps them in taking decisions considering the risk of these events.

Elucidating the Impact of behavioral biases in Pakistan Stock Market: Moderating Impact of Financial Literacy

The current study focuses on some of the most commonly relied upon biases in decision making. The study aimed at understanding the influence of herding, overconfidence, anchoring, and loss aversion on the decision-making style of investor besides it also investigates the role of financial literacy, since the traditional paradigm of finance is of the view that the knowledge of finance is directly associated with the degree of irrational outcomes. To explore this linkage data from investors trading at Lahore, Karachi, and Islamabad is gathered. Structural equation modeling is used for establishing the proposed associations. The results revealed that behavioral biases significantly impact the decision-making of investors. The results of moderation analysis presented that financial literacy plays a major role in de-biasing decision making. These findings can be extremely useful for investors, policymakers, and investment professionals. Not only to make optimal decision-making but also by providing a deeper understanding of the daily life stock market behavior.

Herding Behavior in the Indian Stock Market : An Empirical Study

The herding behavior in financial markets indicates the process whereby the different participants of the market trade in a similar direction simultaneously. This kind of trading pattern seems like a consensus in the market. There are different reasons for herding to exist : to be part of a group, to avoid the feeling of being left out, reaction to some kind of new information, etc. In this paper, we tried to identify the existence of herding behavior in the Indian stock market. The markets were examined over a time frame of the last 15 years to determine the existence of herding behavior at various points of time. The three time periods selected for the study were 2003 – 2007 (pre - financial crisis), 2008 – 2012 (sub-prime crisis), and 2013 – 2017 (post) crisis. The study used security return dispersion as a substitute for herd behavior. In order to test the presence of herding behavior, linear regression model using dummy variables was used. The evidence supported the presence of herding in the Indian stock market during the financial crisis time period and the post-crisis period. In the pre - financial crisis period, there was no herding phenomenon observed.

Gambling-Like Day Trading During the COVID-19 Pandemic - Need for Research on a Pandemic-Related Risk of Indebtedness and Mental Health Impact.

Stock exchange trading increasingly has been highlighted as a possible cause of gambling disorder, typically in rapid and excessive “day trading” which may cause over-indebtedness and mental health problems. The COVID-19 pandemic has been suspected to increase online gambling and gambling problems. In a number of recent media reports, day trading has been reported to increase during COVID-19, possibly in relation to changes in everyday life, financial problems and job insecurity during the pandemic. Increasing day trading has thereby been suspected to cause addictive behavior, financial difficulties, and poor mental health. However, there is hitherto a lack of research in the area. The present paper addresses the potential for day trading to cause problem gambling, debts and mental health problems, and calls for research and clinical guidelines in problem gambling related to stock market behavior as a problematic gambling behavior. Screening tools, awareness among clinicians, and longitudinal research studies may be warranted, both during the COVID-19 pandemic and beyond.

Survival study on stock market prediction techniques using sentimental analysis

Sentiment analysis is the method to detect stock market behaviour. Various components are functioning their ups and downs because the stock market is unestimated. The trend of sequence gets influenced through factors and non-linear relationship. Both academic and real-life business, the Stock market prediction is an attractive topic. The prediction is carried out by gathering the customer reviews and classifying them as positive reviews or negative reviews. Various statistical and econometric techniques were introduced for stock market prediction using sentimental analysis. Stock market predictions are suffered from errorless through sentiment analysis techniques. Lesser classification accuracy has a direct cause for the reliability of stock market indicators. To improve prediction performance, the existing problems of stock market prediction were reviewed in this paper.

The nexus, downside risk and asset allocation between oil and Islamic stock markets: A cross-country analysis

This study performs empirical analyses on Islamic stock markets of 20 countries disaggregated into oil-importing, oil-exporting, and moderately oil-dependent countries. We investigate the asymmetric dynamic linkages between oil and Islamic stock prices for the period from May 2002 to February 2018 based on a nonlinear-Autoregressive Distributed Lag (ARDL) framework using both global and domestic oil prices. For comparison purposes, we also investigate conventional stock markets of the same countries and during the same sample period. Our results show five interesting findings. First, Islamic stock markets react to oil price shocks differently across time horizons and markets. Second, in the long run, our results support that a negative shock in oil prices significantly increases stock prices of all Islamic stock markets irrespective of the country's category (importing, exporting, or moderate oil dependency). Third, in the long run, a divergent reaction is established (regarding magnitude) across markets depending on their oil net position. Islamic stock markets in oil-exporting countries specifically exhibit a more aggressive reaction to negative oil price shocks (world and domestic) than their oil-importing and moderately oil-dependent counterparts. Finally, in the short run, we find that negative oil price changes have a more significant effect on Islamic indices than positive ones. For the conventional counterparts, findings indicate that the long-run effect of oil price changes is not significant for all countries. The short-run results show that, independently from the country's category, the effect of the negative oil price shocks seems to be more significant than oil price increases and that the reaction is similar between countries, in terms of influence. These findings are confirmed through an out-of-sample predictive accuracy test, highlighting that asymmetric specifications improve the predictability of the both Islamic and conventional stock prices of the studied markets. We also examine the implications for risk management in the presence of oil risk. We find evidence of diversification benefits and oil downside risk reduction in a two-assets, Oil-Islamic stocks, investment portfolio, being greater than for their conventional counterparts. The implications of this study will be of interest to Islamic portfolio managers and market regulators to better adopt proactive awareness regarding Islamic stock market behavior, as well as for international investors since it suggests Islamic stocks as an alternative to conventional stocks concerning Oil risk reduction.

Social sentiment segregation: Evidence from Twitter and Google Trends in Chile during the COVID-19 dynamic quarantine strategy.

The Chilean health authorities have implemented a sanitary strategy known as dynamic quarantine or strategic quarantine to cope with the COVID-19 pandemic. Under this system, lockdowns were established, lifted, or prolonged according to the weekly health authorities' assessment of municipalities' epidemiological situation. The public announcements about the confinement situation of municipalities country-wide are made typically on Tuesdays or Wednesdays before noon, have received extensive media coverage, and generated sharp stock market fluctuations. Municipalities are the smallest administrative division in Chile, with each city broken down typically into several municipalities. We analyze social media behavior in response to the confinement situation of the population at the municipal level. The dynamic quarantine scheme offers a unique opportunity for our analysis, given that municipalities display a high degree of heterogeneity, both in size and in the socioeconomic status of their population. We exploit the variability over time in municipalities' confinement situations, resulting from the dynamic quarantine strategy, and the cross-sectional variability in their socioeconomic characteristics to evaluate the impact of these characteristics on social sentiment. Using event study and panel data methods, we find that proxies for social sentiment based on Twitter queries are negatively related (more pessimistic) to increases in the number of confined people, but with a statistically significant effect concentrated on people from the wealthiest cohorts of the population. For indicators of social sentiment based on Google Trends, we found that search intensity during the periods surrounding government announcements is positively related to increases in the total number of confined people. Still, this effect does not seem to be dependent on the segments of the population affected by the quarantine. Furthermore, we show that the observed heterogeneity in sentiment mirrors heterogeneity in stock market reactions to government announcements. We provide evidence that the observed stock market behavior around quarantine announcements can be explained by the number of people from the wealthiest segments of the population entering or exiting lockdown.

Herding behavior in Hong Kong stock market during the COVID-19 period: a systematic detection approach

ABSTRACT The study intends to conduct a systematic mechanism for herding detection in the Hong Kong stock market. We take stocks from three market sectors as samples and investigate the existence of herding in the two periods: before and during the outbreak of COVID-19 in Hong Kong, from August 2019 to July 2020. We adopt CCK model-based OLS and quantile regression to examine herding in each observed period and employ HS model to measure the magnitude of herding during the time. The empirical results indicate the emergence of mild herding from August 2019 to January 2020, and the herding phenomenon is generally weakened between February and July 2020. Our study confirms the implication of the systematic herding detection mechanism that can improve the sensitivity of detection and capture the magnitude and variation of herding.

The role of investor behavior in emerging stock markets: Evidence from Vietnam

Exloring the role of different types of investors on stock market is crticial since different types of investors react and behave differently when making investment decision. The role of investor behavior is a very important issue in an immature stock market like Vietnam stock market because the market is characterized by a large number of individual investors and low reporting standard. Institutional and foreign investors however play an influential role due to their large exposure and strong investment expertise. Clearly, examining the role of investor behavior and its impact on the stock market in Vietnam is an important topic in finance. A significant body of empirical research has shown that investor behavior is an essential factor to explain stock price that the classical financial theory cannot explain. This research examines the role of investor behavior in stock market by examining the relationship between investor behavior and stock return using the Vietnamese stock exchange data. We create a sentiment index using the principal components analysis (PCA). Consistent with the sentiment and stock return literature, the research shows a negative contemporaneous relationship between investor sentiment and market return.

Oil price and stock market behaviour in GCC countries: Do asymmetries and structural breaks matter?

Although the relationship between the global oil and stock markets has been given extensive critical assessment in the literature, this study gives a re-examination of this nexus for the Gulf Cooperation Council countries with certain innovative contributions. We employ both the Symmetric ARDL by Pesaran et al. (2001) and Nonlinear ARDL by Shin et al. (2014) and we also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models. Using a weekly dataset from 1992-2016, we observe that most of the GCC stock markets respond asymmetrically to oil price. The need to account for structural breaks is also undeniably seen as the break dates are largely significant. We discovered some breaks which coincidentally correspond to the series of OPEC cuts of 1999, Asian demand soars of 2005 and global financial crisis of 2008, among others. Our robustness check suggests that global economic activity and geopolitical risks are very sensitive to oil price specification, however in a linear fashion which may change conclusions regarding the effect of oil price shocks on stock returns. In all, the findings of this study, especially the large asymmetric responses of the stock markets to oil price, have serious policy implications for the government of each country and potential investors because of their oil-dependent posture.

MONETARY POLICY AND HERDING BEHAVIOR DEVELOPED MARKET AND EMERGING MARKET COMPARISON

The research examines impact of monetary policy on herding behavior in the stock market. This study used OLS Regression, SUR, and Panel Regression Method. The results show that monetary policy affects herd behavior in stock market, specially in emerging market which have a specific characteristic such as low liquidity and low number of investor. Using SUR, this study show that common factors which affect the global herd behavior are not influential. Domestic stock market has its own variable that may initiate herd behavior.

Asymmetric Tsallis distributions for modeling financial market dynamics

Financial markets are highly non-linear and non-equilibrium systems. Earlier works have suggested that the behavior of market returns can be well described within the framework of non-extensive Tsallis statistics or superstatistics. For small time scales (delays), a good fit to the distributions of stock returns is obtained with q-Gaussian distributions, which can be derived either from Tsallis statistics or superstatistics. These distributions are symmetric. However, as the time lag increases, the distributions become increasingly non-symmetric. In this work, we address this problem by considering the data distribution as a linear combination of two independent normalized distributions — one for negative returns and one for positive returns. Each of these two independent distributions are half q-Gaussians with different non-extensivity parameter q and temperature parameter beta. Using this model, we investigate the behavior of stock market returns over time scales from 1 to 80 days. The data covers both the .com bubble and the 2008 crash periods. These investigations show that for all the time lags, the fits to the data distributions are better using asymmetric distributions than symmetric q-Gaussian distributions. The behaviors of the q parameter are quite different for positive and negative returns. For positive returns, q approaches a constant value of 1 after a certain lag, indicating the distributions have reached equilibrium. On the other hand, for negative returns, the q values do not reach a stationary value over the time scales studied. In the present model, the markets show a transition from normal to superdiffusive behavior (a possible phase transition) during the 2008 crash period. Such behavior is not observed with a symmetric q-Gaussian distribution model with q independent of time lag.

Assessing four decades of global research studies on stock market manipulations: a sceintometric analysis

PurposeThis study aims to diagnose the global key contributors in the stock market manipulation studies during the past four decades.Design/methodology/approachThe database search is based on the terms used in the existing body of knowledge. Using the bibliometric tools and techniques on the Scopus database, the study assessed and analysed the productivity of research studies, as well as the influence of the authors, publications, journals, affiliated institutions and countries.FindingsThis paper finds the USA as the leading country investigating this area, almost capturing 40% of the research studies in finance, moreover, a huge number of co-authors. Financial crises in the late 1990s and 2008 is observed as one of the main reasons for this intriguing research. The Journal of Finance is spotted as the most persuasive journal with the highest cite score and an unprecedented number of citations. The analysis of keywords engendered that most of the stock market manipulation studies are event-based studies. Seminally unique scientometric analysis revealed that the significance of stock market manipulation was mainly captured by event-based studies, insider trading and pump and dump schemes studies. However, much remained untapped to articulate the bridging scope of technology and media with stock market behaviour and manipulations.Research limitations/implicationsThe research only includes the Scopus database, however, incorporates 81% relevant study.Practical implicationsThis study reckons that technology-based manipulations are emerging themes in this research field which invites the applied research to have productive outcomes.Originality/valueThe intriguing study incorporates a maximum number of the relevant literature and used a comprehensive technique for the selection of dataset in Scopus.

An Examination of Herding Behavior in the Brazilian Equity Market

The aim of the present study is to investigate herding behavior in the Brazilian stock market. This bias is quite common in times of market downturns and can cause investors to suffer large losses. It is very difficult to effectively identify its real occurrence. Through the method of Chang et al. (2000), it is possible to show that the occurrence of herd behavior is associated with the following phenomena: high trading volume; high volatility, market downturn; and misbalancing of orders. The main contribution of the paper is to identify that herding behavior reacts asymmetrically to the sign of past shocks. The results suggest that an intense selling movement can generate uncertainty in agents, causing them to imitate others in imminent loss periods.

Política de Dividendos e Períodos de Recessão: Evidências no Mercado de Capitais Brasileiro

Objetivo: Observar o comportamento da distribuição de dividendos das empresas listadas na B3, comparando os períodos de expansão e de recessão na economia brasileira.Método: Foram realizados dois modelos de dados em painel, o qual contaram com o índice payout e com o índice dividend yield como variáveis dependentes e uma dummy classificada como 1, para os anos em que houve recessão econômica e 0 para os anos em que houve ascensão econômica, como variável independente. Além disso, foram acrescentadas ao modelo, as variáveis de controle alavancagem financeira, tamanho e o lucro por ação.Originalidade: O estudo abordou a distribuição de dividendos de acordo com o ciclo da economia brasileira, o que torna a pesquisa original, uma vez que não foram encontrados estudos semelhantes.Resultados: Independentemente da proxy de distribuição de dividendos utilizada, as empresas aumentam a distribuição de dividendos em períodos de recessão, quando há maior incerteza no mercado. No que tange às variáveis de controle, para o modelo estimado utilizando a proxy índice payout, apenas a alavancagem financeira não se mostrou significante, enquanto o tamanho e o lucro por ação foram positivamente significantes. No modelo que tem a proxy dividend yield como variável dependente, o lucro por ação não se mostrou significante, ao passo que a alavancagem financeira e o tamanho se mostraram negativamente correlacionadas ao dividend yield. Contribuições: Identificação do aspecto economômico na política de dividendos das empresas brasileiras e na criação de valor para os acionistas em períodos de recessão econômica.

Predicting Stock Market Investment Intention and Behavior among Malaysian Working Adults Using Partial Least Squares Structural Equation Modeling

The purpose of this study was to investigate the effects of risk tolerance, financial well-being, financial literacy, overconfidence bias, herding behavior, and social interaction on stock market investment intention and stock market participation among working adults in Malaysia. Adopting the cross-sectional design, this study collected quantitative data from a total of 349 respondents in an online survey via Google form link across various social media platforms. This study used the partial least squares structural equation modeling (PLS-SEM) approach to test the hypotheses. This study revealed the significant positive effects of risk tolerance, herding behavior, and social interaction on stock market investment intention. Stock market investment intention also had a significant effect on stock market participation. Stock market investment intention was also found to successfully mediate the relationships of risk tolerance and overconfidence bias with stock market participation. When it comes to stock market investment, the government and related authorities should focus on developing programs and policies that provide a financial safety net for investors and promote investment-related social platforms. This study linked risk tolerance, financial well-being, financial literacy, overconfidence bias, herding behavior, social interaction, stock market investment intention, and stock market participation. This is one of the few early attempts to address issues in light of the stock market investment participation among the working adults in a developing country.

Investigating the effect of political turmoil on the behavior of Tadawul stock market, KSA

The current paper will be addressing the investigation of the impact of the political incidents on the stock market return in Saudi Arabia. It was generated from previous inquiries that needed clarifications. Yet, from previous explorations, it became clear that an examination of this case should be conducted using a cause and effect research, relying on statistical analysis, was necessary. As a result, an experimental framework, using the positivist approach, sought to develop clarifications of the issue at hand. The tested data was collected between 2000 and 2014. They represented the closing figures on the last day of each month. Dummy variables were used to determine the effect of political turmoil on stock market behavior using regression analysis. The findings indicated that the Saudi Government attempted to control political unrest by giving subsidies, thus prevent inconsistency in political events. Finally, the study increases understanding of the stock market behavior of the decision makers in order for them to predict any changes, where preventive measures against the risk involved in stock market behavior can be taken by the authorities.

COVID-19 pandemic and stock market reaction: empirical insights from 15 Asian countries

Since 2020, the world has been passing through a difficult time due to the outbreak of COVID-19 Pandemic. This novel public health emergency has created both demand- and supply-side shocks affecting both real and financial sectors of economies globally. One of the noteworthy immediate consequences of it was sudden nosedive of stock markets across countries in the globe. In this pre-text, this study examined the stock market behaviour in 15 selected Asian markets amid the pandemic. The results infer about the surge in market return volatilities amid the rapid spread of the coronavirus which was primarily triggered through the impaired investors’ sentiments due to the announcement effects. During this period, the stock market performances in selected Asian countries have been observed to be influenced by the reporting of the number of COVID-19 confirmed cases and death cases, stock index returns, market volatility, oil prices, inflation rate, and interest rates.

Stock Market Behaviour in Response to Political Events: A Case of Pakistan Major Political Events

Stock Market Behaviour in Response to Political Events: A Case of Pakistan Major Political Events

Efficient Market Hypothesis to Behavioral Finance: A Review of Rationality to Irrationality

This paper focuses on a complete review of the evolution of Efficient Market Hypothesis and Behavioral Finance. The main purpose of the paper is to understand how the traditional finance theories (EMH) failed in understanding the market anomalies and the human behaviour involved in investment decision making process. Further, the study attempts to understand the evolution of a novel discipline Behavioral Finance. The review and discussion of literature is mainly divided into two sections – evolution of Efficient Market Hypothesis (EMH) and studies providing evidences on the failure of EMH; studies on the evolution of Behavioral Finance and studies of investor behaviour. The study found that EMH theory was one the dominant theory conceptualised by Eugene Fama during 1960′s. The EMH model became a prominent financial model explaining the stock market behaviour in 1970’s i.e. first decade of its conception and was widely considered as the best model by the investment community in large. The 1980s is a very significant decade, where several studies provoked to question the validity of EMH. The study also focused on highlighting the gaps in the concept of market efficiency and bridged the gap with a contemporary approach of Behavioral Finance.