scholarly journals Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jing Zhang ◽  
Ya-ming Zhuang
Keyword(s):  
Stock Market ◽  
Bayesian Network ◽  
Stochastic Volatility ◽  
Strong Correlation ◽  
Stock Markets ◽  
Computational Analysis ◽  
Herd Behavior ◽  
Herding Behavior ◽  
Volatility Spillovers ◽  
Multivariate Stochastic Volatility

This paper is concerned with the multivariate stochastic volatility modeling of the stock market. We investigate a DGC-t-MSV model to find the historical volatility spillovers between nine markets, including S&P, Nasdaq, SSE, SZSE, HSI, FTSE, CAC, DAX, and Nikkei indices. We use the Bayesian network to analyze the spreading of herd behavior between nine markets. The main results are as follows: (1) the DGC-t-MSV model we considered is a useful way to estimate the parameter and fit the data well in the stock market; (2) our computational analysis shows that the S&P and Nasdaq have higher volatility spillovers to the Shanghai and Shenzhen stock markets; (3) the results also show that there is a strong correlation between stock markets in the same region.

Islamic finance and herding behavior: an application to Gulf Islamic stock markets

2018 ◽  
Vol 10 (2) ◽  
pp. 192-206 ◽  
Author(s):  
Imed Medhioub ◽  
Mustapha Chaffai
Keyword(s):  
Saudi Arabia ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Future Research ◽  
Herd Behavior ◽  
Herding Behavior ◽  
Cross Sectional ◽  
Monthly Data ◽  
Content Type

Purpose The purpose of this paper is to examine the herding behavior in GCC Islamic stock markets. Design/methodology/approach The authors followed the methodology developed by Chiang and Zheng (2010) to test herding behavior. Cross-sectional tests have been considered in this paper. The authors use both OLS and GARCH estimations to examine herding behavior by using a sample of GCC Islamic stock markets. Findings By applying monthly data for the period between January 2006 and February 2016 for five Islamic GCC stock returns (Bahrain, Kuwait, Qatar, Saudi Arabia and UAE), results suggest a significant evidence of herd behavior in Saudi and Qatari Islamic stock markets only. When the authors take into account the existence of asymmetry in herd behavior between down- and up-market periods, evidence of herding behavior during down market periods in the case of Qatar and Saudi Arabia was found. In addition, the authors found that Kuwaiti and Emirates Islamic stock markets herd with the local conventional stock market, showing the interdependencies between Islamic and conventional markets. Research limitations/implications In this paper, the authors found an absence of herding behavior in some Islamic stock markets (Bahrain, Kuwait and Emirates). This is not the result of Shariah guidelines in these Islamic markets, but this is mainly due to the weak oscillations of returns which are very close to zero. In our future research, the authors could apply daily data and compare the results to those obtained in this paper by using monthly data. Originality/value This paper provides a practical framework in order to analyze the herding behavior concept for GCC Islamic stock markets. Its originality consists of linking the herding behavior to ethics and morality to verify whether the properties and guidelines of Islam are respected in Islamic stock markets. To the best of the authors’ knowledge, no other paper has treated the case of herding behavior in Islamic stock markets and taking into account the possible influence of the conventional market on the Islamic stock market that may impact herding behavior.

scholarly journals Spillovers of Stock Markets among the BRICS: New Evidence in Time and Frequency Domains before the Outbreak of COVID-19 Pandemic

2021 ◽  
Vol 14 (3) ◽  
pp. 112
Author(s):  
Kai Shi
Keyword(s):  
Stock Market ◽  
Frequency Band ◽  
Stock Markets ◽  
Emerging Market ◽  
Low Frequency ◽  
Systematic Risk ◽  
Error Variance ◽  
Frequency Bands ◽  
Volatility Spillovers ◽  
Risk Sources

We attempted to comprehensively decode the connectedness among the abbreviation of five emerging market countries (BRICS) stock markets between 1 August 2002 and 31 December 2019 not only in time domain but also in frequency domain. A continuously varying spillover index based on forecasting error variance decomposition within a generalized abbreviation of vector-autoregression (VAR) framework was computed. With the help of spectral representation, heterogeneous frequency responses to shocks were separated into frequency-specific spillovers in five different frequency bands to reveal differentiated linkages among BRICS markets. Rolling sample analyses were introduced to allow for multiple changes during the sample period. It is found that return spillovers dominated by the high frequency band (within 1 week) part declined with the drop of frequencies, while volatility spillovers dominated by the low frequency band (above 1 quarter) part grew with the decline in frequencies; the dynamics of spillovers were influenced by crucial systematic risk events, and some similarities implied in the spillover dynamics in different frequency bands were found. From the perspective of identifying systematic risk sources, China’s stock market and Russia’s stock market, respectively, played an influential role for return spillover and volatility spillover across BRICS markets.

scholarly journals Linkages between gold and emerging Asian stock markets: New evidence from the Chinese stock market crash

2021 ◽  
Vol 39 (2) ◽  
Author(s):  
Imran Yousaf ◽  
Shoaib Ali
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Chinese Stock Market ◽  
Stock Market Crash ◽  
Volatility Spillovers ◽  
Hedge Ratios ◽  
The Global Financial Crisis ◽  
New Evidence

This study examines the return and volatility transmission between gold and nine emerging Asian Stock Markets during the global financial crisis and the Chinese stock market crash. We use the VAR-AGARCH model to estimate return and volatility spillovers over the period from January 2000 through June 30, 2018. The results reveal the substantial return and volatility spillovers between the gold and emerging Asian stock markets during the global financial crisis and the Chinese stock market crash. However, these return and volatility transmissions vary across the pairs of stock markets and the financial crises. Besides, we analyze the optimal portfolios and hedge ratios between gold and emerging Asian stock markets during all sample periods. Our findings have important implications for effective hedging and diversification strategies, asset pricing and risk management.

scholarly journals Investor Sentiment and Herding Behavior in the Korean Stock Market

2020 ◽  
Vol 8 (2) ◽  
pp. 34
Author(s):  
Ki-Hong Choi ◽  
Seong-Min Yoon
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Markets ◽  
Trading Volume ◽  
Investor Sentiment ◽  
Herding Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Korean Stock Market ◽  
Quantile Regression Method

This paper investigates herding behavior and the connection between herding behavior and investor sentiment. We apply a Cross-Sectional Absolute Deviation (CSAD) approach and the quantile regression method to capture herding behavior in the KOSPI and KOSDAQ stock markets. The analysis results are outlined as follows. First, we find that herding behavior is exhibited during down-market periods in the KOSPI and KOSDAQ stock markets. However, we show that adverse herding behavior occurs in low-trading volume and low-volatility periods. Second, according to the results of the quantile regression, herding behavior is found in the low and high quantiles of the KOSPI and KOSDAQ stock markets. However, adverse herding behavior is also found, which means that investors herd in extreme market conditions. Third, the relationship between investor sentiment and herding behavior is analyzed through regression and quantile regression, and investor sentiment is confirmed to be one of the important factors that can cause herding behavior in the Korean stock market.

scholarly journals Intraday Volatility Spillovers among European Financial Markets during COVID-19

2021 ◽  
Vol 9 (1) ◽  
pp. 5
Author(s):  
Faheem Aslam ◽  
Paulo Ferreira ◽  
Khurrum Shahzad Mughal ◽  
Beenish Bashir
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Forecast Error ◽  
Error Variance ◽  
Stock Market Volatility ◽  
Volatility Spillovers ◽  
Forecast Error Variance ◽  
Intraday Volatility ◽  
Market Interdependence ◽  
Rolling Windows

During crises, stock market volatility generally rises sharply, and as consequence, spillovers are identified across markets. This study estimates the volatility spillover among twelve European stock markets representing all four regions of Europe. The data consists of 10,990 intraday observations from 2 December 2019 to 29 May 2020. Using the methodology of Diebold and Yilmaz, we use static and rolling windows to characterize five-minute volatility spillovers. Our results show that 77.80% of intraday volatility forecast error variance in twelve European markets comes from spillovers. Furthermore, the highest gross directional volatility spillovers are found in Sweden and the Netherlands, while the minimum spillovers to other stock markets are observed in the stock markets of Poland and Ireland. However, German and Dutch markets transmit the highest net directional volatility spillovers. Splitting the whole sample in pre- and post-pandemic declaration (11 March 2020) we find more stable spillovers in the latter. The findings reveal important information about European stock market interdependence during COVID-19, which will be beneficial to both policy-makers and practitioners.

What make investors herd while investing in the Indian stock market? A hybrid approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muskan Sachdeva ◽  
Ritu Lehal ◽  
Sanjay Gupta ◽  
Aashish Garg
Keyword(s):  
Stock Market ◽  
Fuzzy Ahp ◽  
Hybrid Approach ◽  
North India ◽  
Second Phase ◽  
Herd Behavior ◽  
Herding Behavior ◽  
Two Phase ◽  
Content Type ◽  
Indian Stock Market

PurposeIn recent years, significant research has focused on the question of whether severe market periods are accompanied by herding behavior. As herding behavior is a considerable cause of the speculative bubble and leads to stock market deviations from their basic values it is necessary to examine the motivators which led to herding behavior among investors. The paper aims to discuss this issue.Design/methodology/approachIn this study, the authors performed a two-phase analysis to address the research questions of the study. In the first phase, for text analysis NVivo software was used to identify the factors driving herding behavior among Indian stock investors. The analysis of a text was performed using word frequency analysis. While in the second phase, the Fuzzy-AHP analysis techniques were employed to examine the relative importance of all the factors determined and assign priorities to the factors extracted.FindingsResults of the study depicted Investor Cognitive Psychology (ICP), Market Information (MI), Stock Characteristics (SC) as the top-ranked factors driving herding behavior, while Socio-Economic Factors (SEF) emerged as the least important factor driving herding behavior.Research limitations/implicationsThe current study was undertaken among stock investors from North India only. Moreover, numerous factors are not part of the study but might significantly influence the investors' herding behaviors.Practical implicationsComprehending the influences of the different factors discussed in the study would enable stock investors to be more aware of their investment choices and not resort to herd behavior. This research enables decision-makers to understand the reasons for herd activity and helps them act accordingly to improve the stock market's performance.Originality/valueThe current study will provide an inclusive overview of herding behavior motivators among Indian stock investors. This study's results can be extremely useful for both academics and policymakers to gain some insight into the functioning of the Indian stock market.

Herd behavior in the French stock market

2017 ◽  
Vol 16 (4) ◽  
pp. 497-515 ◽  
Author(s):  
Houda Litimi
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Design Methodology ◽  
Garch Model ◽  
Herd Behavior ◽  
Conditional Volatility ◽  
Herding Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Content Type

Purpose This paper aims to investigate the herding behavior in the French stock market and its effect on the idiosyncratic conditional volatility at a sectoral level. Design/methodology/approach This sample covers all the listed companies in the French stock market, classified by sector, over four major crisis periods. The author modifies the cross-sectional absolute deviation (CSAD) model to include trading volume and investors sentiment as herding triggers. Furthermore, the author uses a modified GARCH model to investigate the effect of herding on conditional volatility. Findings Herding is present in the French market during crises, and it is present in only some sectors during the entire period. The main trigger for investors to embark into a collective herding movement differs from one sector to another. Furthermore, herding behavior has an inhibiting effect on market conditional volatility. Originality/value The author modifies the CSAD model to investigate the presence of herding in the French stock market at a sectoral level during turmoil periods. Furthermore, the particularly designed GARCH model provides new insights on the effect of herding and volume turnover on the conditional volatility.

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