NDLI: Disposition Effects and Investor Overconfidence: Evidence from Trading Volume in China Stock Market

Content Provider	IEEE Xplore Digital Library
Author	Duan Liu Shou Chen
Copyright Year	2008
Description	Author affiliation: Coll. of Bus. Adm., Hunan Univ., Changsha (Duan Liu; Shou Chen)
Abstract	Stock trading activity is very important to market volatility. The particular market environment of China makes the internal reason of trading volume change more complicated. In order to test how trading activities are driven, we use a vector autoregressive and impulse-response function methodology. First, we study the intertemporal relationship between individual stock trading volume and individual stock return. Then we extend the bivariate vector autoregressive equation to a trivariate vector autoregressive equation to see how lagged market returns as well as lagged individual stock returns impact trading activity. It is concluded that historical stock returns have significantly positive effects on trading volume, and the shocks of both individual firm return and market wide return are transferred to trading activities, and then bring a shock in the same direction to stock trading volume. And this shock can last for times. It suggests that overconfidence and disposition effect are both important factors to drive trading activities. Investors trade (or do not trade) stock not only because of the desire to increase their mental accounts, but also because of their overconfidence and cognitive error.
Starting Page	1
Ending Page	4
File Size	110965
Page Count	4
File Format	PDF
ISBN	9781424421077
DOI	10.1109/WiCom.2008.2325
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electric shock Pricing Drives Educational institutions Computer crashes Security Impulse testing Stock markets Equations Portfolios
Content Type	Text
Resource Type	Article

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