Stock return volatility and trading volume: evidence from the chinese stock market

Abstract

This study investigates the dynamic relationship between stock return volatility and trading volume for individual stocks listed on the Chinese stock market as well as market portfolios of these stocks. We found that the inclusion of trading volume, which is used as a proxy of information arrival, in the GARCH specification reduces the persistence of the conditional variance dramatically, and the volume effect is positive and statistically significant in all the cases for individual stocks. Consistent with our analysis of the institutional and ownership structure of listed Chinese companies, trading volume is found to play a role of proxies of information arrivals for the two B share portfolios, but not for the two A share portfolios. Our conclusion is that the information-based effect helps in explaining the GARCH effect to a large extent. Nevertheless, GARCH does not completely vanish as a result of this inclusion.Trading volume, stock market return volatility, GARCH models, China,

ARCH effects, trading volume and the information flow interpretation: empirical evidence from the Chinese stock markets

“…If we accept the criterion widely used in previous studies, this result indicates that volume may explain ARCH effects in the context of individual equity level but not at the market-wide index level. This result is in some way consistent with Wang, Wang, and Liu's (2005) finding, which suggests that information arrivals represented by trading volume tend to be company specific. However, we have a different assumption for our finding from that which Wang, Wang, and Liu (2005) make.…”

“…In the literature, the conclusions of Lamoureux and Lastrapes (1990) and Wang, Wang, and Liu (2005) are drawn from the dramatically subsumes in their estimated and values. However, this simple inference method turns out to be problematic, which is later criticised by Omran and McKenzie (2000), Wagner and Marsh (2005) and Ostdiek (2006, 2008).…”

“…For example, Omran and McKenzie (2000) select 50 companies amongst the 100 biggest British companies and fit the VA-GARCH (1, 1) model. Wang, Wang, and Liu (2005) select 20 Chinese companies from the top 100 in terms of market capitalisation. Due to the prevailing short-termist behaviour of the Chinese investors, small-cap shares are more likely being traded actively (Chen 2003); thus, the sampling criteria of Wang, Wang, and Liu (2005) is questionable.…”

“…Wang, Wang, and Liu (2005) select 20 Chinese companies from the top 100 in terms of market capitalisation. Due to the prevailing short-termist behaviour of the Chinese investors, small-cap shares are more likely being traded actively (Chen 2003); thus, the sampling criteria of Wang, Wang, and Liu (2005) is questionable. This study adopts turnover velocity as sample selection criterion for individual equities, which is…”

The Relationship between Information Asymmetry and Stock Return in the Presence of Accounting Conservatism

“…These studies mainly return to (Rogalski, 1978), (Figlewski, 1981), and (Cornell, 1981), these studies sought to examine the relationship between these variables, which found that there is a positive relationship between risk, trading volume, and stock return. Also (Wang et al, 2005) tested the relationship between the behavior of market stock returns, volatility of returns (Risk), and trading volume. The results confirmed that the volume of trading , which was used as a measure of information access, has a positive effect on the stock return.…”