Empirical Identification of Non-Informational Trades Using Trading Volume Data

Empirical Identification of Non-Informational Trades Using Trading Volume Data This paper empirically identifies non-informational and informational trades using stock returns and trading volume data of the U.S., Japanese, and U.K. stock markets and five individual firms. We achieve the identification by imposing a restriction from theoretical considerations. Our results show that trading volume is mainly driven by non-informational trades, while stock price movements are primarily driven by informational trades. We also find that, around the 1987 stock market crash, trading volumes due to non-informational trades increased dramatically, while the decline in stock market prices was due mainly to informational trades. Increases in volatilities both in returns and in trading volumes during and after the crash are mainly due to non-informational trades. Regarding the trading volume-serial correlation in the stock returns relationship, we find evidence that is consistent with theoretical predictions that non-informational components can account for high trading volume accompanied by a low serial correlation of stock returns. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

Empirical Identification of Non-Informational Trades Using Trading Volume Data

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Kluwer Academic Publishers
Copyright © 2001 by Kluwer Academic Publishers
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
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