Identifier

etd-06232005-133134

Degree

Doctor of Philosophy (PhD)

Department

Finance (Business Administration)

Document Type

Dissertation

Abstract

This dissertation relates the information contained in past trading volume to investor sentiment, and investigates its ability in predicting stock returns. Investor sentiment here refers to the enthusiasm of irrational investors on an asset, relative to that of rational investors. Motivated by Baker and Stein (2004) that an increase in trading volume reflects a rise in investor sentiment, I use the change in trading volume per unit of time, referring it as the trading volume trend, as a measure of investor sentiment on individual stocks. I document a negative and significant cross-sectional relation between the trading volume trend and stock returns, both in the short term and in the long run. This relation is dynamic and holds after controlling for several liquidity measures and other possible determinants of expected returns. It also holds for various volume measures and momentum portfolios. Specifically, both winner and loser portfolios show the effect of the trading volume trend. The effect exists in stocks of small and large firms, and in optioned and non-optioned stocks. These findings suggest that the negative effect of the trading volume trend on stocks returns is robust. Moreover, a composite trading volume trend, formed on the trading volume trends of individual stocks, can predict both the equally-weighted and the value-weighted market returns in the expected direction, after controlling for other possible determinants of market returns. The composite trading volume trend also explains closed-end fund discounts. Collectively these findings support that the trading volume trend contains information on investor sentiment, and that investor sentiment has a valuation effect on stocks.

Date

2005

Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Ji-Chai Lin

DOI

10.31390/gradschool_dissertations.2012

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