Open AccessVolatility Modelling of Chinese Stock Market Monthly Return and Investor Sentiment Using Multivariate GARCH Models
Author(s) -
Hongjun Zeng
Publication year - 2020
Publication title -
international journal of accounting and finance review
Language(s) - English
Resource type - Journals
eISSN - 2576-1293
pISSN - 2576-1285
DOI - 10.46281/ijafr.v5i1.643
Subject(s) - volatility (finance) , economics , spillover effect , stock market , stock market index , econometrics , autoregressive conditional heteroskedasticity , consumer confidence index , stock (firearms) , financial economics , index (typography) , linkage (software) , monetary economics , macroeconomics , geography , computer science , biochemistry , context (archaeology) , chemistry , archaeology , world wide web , gene
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.