Volatility Modelling of Chinese Stock Market Monthly Return and Investor Sentiment Using Multivariate GARCH Models
Keywords:
Stock Market Monthly Return, Investor Sentiment, volatility spillovers, Linkage, BEKK/DCC-GARCH.
Abstract
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.
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Zweig, M. E. (1973). An investor expectations stock price predictive model using closed-end fund premiums. The Journal of Finance, 28(1), 67-78.
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307-327.
Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of financial economics, 49(3), 307-343.
Brown, G. W. (1999). Volatility, sentiment, and noise traders. Financial Analysts Journal, 55(2), 82-90.
Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of empirical finance, 11(1), 1-27.
Black, F. (1986). Noise. The journal of finance, 41(3), 528-543.
Baker, M., & Wurgler, J. (2004). A catering theory of dividends. The Journal of finance, 59(3), 1125-1165.
Baker, M., & Stein, J. C. (2004). Market liquidity as a sentiment indicator. Journal of Financial Markets, 7(3), 271-299.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The journal of Finance, 61(4), 1645-1680.
Baker, M., Wurgler, J., & Yuan, Y. (2012). Global, local, and contagious investor sentiment. Journal of financial economics, 104(2), 272-287.
Ben-Rephael, A., Kandel, S., & Wohl, A. (2012). Measuring investor sentiment with mutual fund flows. Journal of financial Economics, 104(2), 363-382.
Campbell, R., Huisman, R., & Koedijk, K. (2001). Optimal portfolio selection in a Value-at-Risk framework. Journal of Banking & Finance, 25(9), 1789-1804.
Chen, H., Chong, T. T. L., & Duan, X. (2010). A principal-component approach to measuring investor sentiment. Quantitative Finance, 10(4), 339-347.
De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of political Economy, 98(4), 703-738.
Da, Z., Engelberg, J., & Gao, P. (2015). The sum of all FEARS investor sentiment and asset prices. The Review of Financial Studies, 28(1), 1-32.
Engle, R., & Kroner, K. F. (1995). Multivariate Simultaneous Generalized ARCH. Econometric Theory, 11(1), 122-150.
Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339-350.
Fisher, K. L., & Statman, M. (2000). Investor sentiment and stock returns. Financial Analysts Journal, 56(2), 16-23.
Hirshleifer, D., & Shumway, T. (2003). Good day sunshine: Stock returns and the weather. The Journal of Finance, 58(3), 1009-1032.
Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica: Journal of the Econometric Society, 53(6), 1315-1335.
Kaustia, M., & Knüpfer, S. (2008). Do investors overweight personal experience? Evidence from IPO subscriptions. The Journal of Finance, 63(6), 2679-2702.
Lee, C. M., Shleifer, A., & Thaler, R. H. (1991). Investor sentiment and the closed‐end fund puzzle. The journal of finance, 46(1), 75-109.
Lee, Y. H. (2014). What jump effects are implicit in Nikkei 225 returns and the changes in the volatility index Japan? Investment Analysts Journal, 43(80), 71-78.
Ni, Z. X., Wang, D. Z., & Xue, W. J. (2015). Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model. Economic Modelling, 50, 266-274.
Owji, A., & Kontonikas, A. (2018). Modelling & Forecasting Stock Market Volatility, Comparing Time Series Dynamics and Economic Fundamentals: A Study on the European Stock Markets.
Peng, L., & Xiong, W. (2006). Investor attention, overconfidence and category learning. Journal of Financial Economics, 80(3), 563-602.
Polk, C., & Sapienza, P. (2009). The stock market and corporate investment: A test of catering theory. The Review of Financial Studies, 22(1), 187-217.
Shefrin, H., & Statman, M. (1994). Behavioral Capital Asset Pricing Theory. Journal of Financial and Quantitative Analysis, 29(3), 323-349.
Schmeling, M. (2009). Investor sentiment and stock returns: Some international evidence. Journal of empirical finance, 16(3), 394-408.
Sayim, M., & Rahman, H. (2015). The relationship between individual investor sentiment, stock return and volatility. International Journal of Emerging Markets, 10(3), 504-520.
Trejos, C., van Deemen, A., Rodríguez, Y. E., & Gomez, J. M. (2019). Overconfidence and disposition effect in the stock market: A micro world-based setting. Journal of Behavioral and Experimental Finance, 21, 61-69.
Veldkamp, L. L. (2006). Media frenzies in markets for financial information. American Economic Review, 96(3), 577-601.
Yao, J., Ma, C., & He, W. P. (2014). Investor herding behaviour of Chinese stock market. International Review of Economics & Finance, 29, 12-29.
Zweig, M. E. (1973). An investor expectations stock price predictive model using closed-end fund premiums. The Journal of Finance, 28(1), 67-78.
Published
2020-06-27
How to Cite
Zeng, H. (2020). Volatility Modelling of Chinese Stock Market Monthly Return and Investor Sentiment Using Multivariate GARCH Models. International Journal of Accounting & Finance Review, 5(1), 123-133. https://doi.org/10.46281/ijafr.v5i1.643
Section
Research Paper/Theoretical Paper/Review Paper/Short Communication Paper
Copyright (c) 2020 Hongjun Zeng
This work is licensed under a Creative Commons Attribution 4.0 International License.
