scholarly journals Volatility Modelling of Chinese Stock Market Monthly Return and Investor Sentiment Using Multivariate GARCH Models

2020 ◽  
Vol 5 (1) ◽  
pp. 123-133
Author(s):  
Hongjun Zeng
Keyword(s):  
Stock Market ◽  
Investor Sentiment ◽  
Multivariate Garch ◽  
Volatility Spillover ◽  
Chinese Stock Market ◽  
Volatility Spillovers ◽  
Stock Market Return ◽  
Monthly Return ◽  
Multivariate Garch Models ◽  
Linkage Effects

This article examines the linkage and volatility spillover among Chinese Stock Market Monthly Return and Investor Sentiment, investigating the effect dynamic links of various investor sentiment indicators and Chinese stock market return volatility. Employing the DCC and BEKK GARCH, we find investor sentiment is to some extent linked to the yield fluctuations of the Chinese stock market, but the volatility spillover is relatively weak. In the test period (2005-2020), we observe that several indicators do not explain their linkage effects with CSI 300 index of return fluctuations and volatility spillovers well, with no indicators can reflect both of these effects. Most indicators are linkage with the CSI 300 index, especially consumer confidence index (CCI), new investor account openings last month (NIA) and the volume of transactions last month (TURN) have significant linkage effects with the CSI 300 index. We also find that only the CCI index has a one-way volatility spillover on the CSI 300 index, and the CSI 300 index has no volatility spillover on any indicator.

Volatility Modelling of Chinese Stock Market Monthly Return and Investor Sentiment Using Multivariate GARCH Models

2020 ◽  
Vol 5 (1) ◽  
pp. 123-133
Author(s):  
Hongjun Zeng
Keyword(s):  
Stock Market ◽  
Investor Sentiment ◽  
Multivariate Garch ◽  
Volatility Spillover ◽  
Chinese Stock Market ◽  
Volatility Spillovers ◽  
Stock Market Return ◽  
Monthly Return ◽  
Multivariate Garch Models ◽  
Linkage Effects

This article examines the linkage and volatility spillover among Chinese Stock Market Monthly Return and Investor Sentiment, investigating the effect dynamic links of various investor sentiment indicators and Chinese stock market return volatility. Employing the DCC and BEKK GARCH, we find investor sentiment is to some extent linked to the yield fluctuations of the Chinese stock market, but the volatility spillover is relatively weak. In the test period (2005-2020), we observe that several indicators do not explain their linkage effects with CSI 300 index of return fluctuations and volatility spillovers well, with no indicators can reflect both of these effects. Most indicators are linkage with the CSI 300 index, especially consumer confidence index (CCI), new investor account openings last month (NIA) and the volume of transactions last month (TURN) have significant linkage effects with the CSI 300 index. We also find that only the CCI index has a one-way volatility spillover on the CSI 300 index, and the CSI 300 index has no volatility spillover on any indicator.

scholarly journals International Stock Market Comovements: What Happened during the Financial Crisis?

2012 ◽  
Vol 12 (1) ◽  
pp. 1850252 ◽  
Author(s):  
Roman Horvath ◽  
Petr Poldauf
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Equity Returns ◽  
Multivariate Garch ◽  
Garch Models ◽  
Chinese Stock Market ◽  
Common Shock ◽  
The Usa ◽  
Multivariate Garch Models ◽  
The Uk

We investigate the stock market comovements in Australia, Brazil, Canada, China, Germany, Hong Kong, Japan, Russia, South Africa, the UK, and the USA, both at the market and sectoral level in 2000-2010. Using multivariate GARCH models, our results suggest that the correlation among equity returns during the financial crisis (2008-2010) somewhat increased, suggesting that the crisis represented a common shock to all countries. The U.S. stock market is found to be the most correlated with the stock markets in Brazil, Canada and UK. The correlation of U.S. and Chinese stock market is essentially zero before the crisis; it becomes slightly positive during the crisis. The sectoral indices are less correlated than the market indices over the whole period, but, again, the correlations increase during the crisis.

scholarly journals The Nonlinear Relationship between Investor Sentiment, Stock Return, and Volatility

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Gang He ◽  
Shuzhen Zhu ◽  
Haifeng Gu
Keyword(s):  
Stock Market ◽  
Stock Return ◽  
Investor Sentiment ◽  
Chinese Stock Market ◽  
Stock Market Volatility ◽  
Market Returns ◽  
Stock Market Returns ◽  
Bear Market ◽  
Stock Market Return ◽  
Space Effect

Based on the DSSW model, we analyze the nonlinear impact mechanism of investor sentiment on stock return and volatility by adjusting its hypothesis in Chinese stock market. We examine the relationship between investor sentiment, stock return, and volatility by applying OLS regression and quantile regression. Our empirical results show that the effects of investor sentiment on stock market return are asymmetric. There is “Freedman effect” in Chinese stock market, but only optimistic sentiment has a significant nonlinear impact on stock market returns when the stock market is a balanced market or a bear market. Meanwhile, “create the space effect” does exist in Chinese stock market too. It only exists when the market is in equilibrium, and only pessimistic sentiment has the nonlinear effect on stock market volatility.

scholarly journals Modeling Mediterranean Stock Markets Volatility with Univariate and Multivariate Approaches

2021 ◽  
Vol 16 ◽  
pp. 457-468
Author(s):  
Saoussan Bouchareb ◽  
Mohamed Salah Chiadmi ◽  
Fouzia Ghaiti
Keyword(s):  
Stock Market ◽  
Strong Evidence ◽  
Stock Markets ◽  
Multivariate Garch ◽  
Garch Models ◽  
Volatility Spillovers ◽  
Daily Data ◽  
Multivariate Approaches ◽  
Multivariate Garch Models

In our study we use the univariate and multivariate GARCH models to analyze the volatility behavior of the daily data of four Mediterranean stock markets (Morocco, Turkey, Spain, and France) spanning the period 2000-2020. We find a strong evidence of persisting of volatility in each of these markets. Results also indicate that both the univariate and the multivariate approaches capture well the ARCH and GARCH effects. We analyze the conditional covariances, and co-volatility spillovers between the Moroccan stock market and the three other Mediterranean stock markets. In order to study co-volatility spillovers, our work is built on the diagonal BEKK model especially the conditional covariances.

Does investor sentiment predict Mexican equity returns?

2018 ◽  
Vol 14 (4) ◽  
pp. 484-502 ◽  
Author(s):  
Daniel Liston-Perez ◽  
Patricio Torres-Palacio ◽  
Sidika Gulfem Bayram
Keyword(s):  
Stock Market ◽  
Investor Sentiment ◽  
Equity Returns ◽  
Multivariate Garch ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
Dynamic Correlation ◽  
Predictive Regressions ◽  
Multivariate Garch Models

Purpose The purpose of this paper is to test whether investor sentiment is a significant predictor of future Mexican stock market returns. It also estimates the dynamic correlation between investor sentiment and equity returns. Finally, it examines if investor sentiment innovations impact unexpected returns for a variety of portfolios. Design/methodology/approach This study utilizes predictive regressions to determine if sentiment can predict Mexican equity returns. Multivariate GARCH models are estimated to examine the time-varying correlations between investor sentiment and equity returns. Findings The results show that Mexican investor sentiment is a significant predictor of Mexican equity returns for up to 24 months ahead. The findings show that high levels of sentiment today are associated with lower equity returns over the near term. Furthermore, multivariate GARCH estimations indicate that the correlation between investor sentiment and equity returns is not static and varies considerably over time. Finally, the findings indicate that sentiment innovations are significantly correlated with unexpected returns, reinforcing the notion that unexplained sentiment fluctuations lead to unexplained changes in stock market returns. Overall, these results suggest that investor sentiment is a significant source of risk for the Mexican stock market. Originality/value This study seeks to further our understanding of how behavioral factors influence and predict Mexican equity returns.

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.

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