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

H. Zeng
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引用次数: 1

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.
基于多元GARCH模型的中国股市月收益与投资者情绪波动模型
本文考察了中国股市月收益与投资者情绪之间的联系和波动外溢,考察了各种投资者情绪指标与中国股市收益波动之间的影响动态联系。运用DCC和BEKK GARCH,我们发现投资者情绪在一定程度上与中国股市收益率波动相关,但波动溢出相对较弱。在检验期内(2005-2020年),我们观察到有几个指标不能很好地解释它们与沪深300指数的收益波动和波动溢出的联动效应,没有一个指标能同时反映这两种效应。多数指标与沪深300指数联动,尤其是消费者信心指数(CCI)、上月新开户数(NIA)和上月交易量(TURN)与沪深300指数联动效果显著。我们还发现,只有CCI指数对沪深300指数存在单向波动溢出,沪深300指数对任何指标都不存在波动溢出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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