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File name: SSRN-id442200. ; Size: 206K
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Volume Autocorrelation, Information and Investor Trading
Vicentiu Covrig
California State University, Northridge - Department of Finance, Real Estate, & Insurance
Lilian K. Ng
University of Wisconsin - Milwaukee - Sheldon B. Lubar School of Business
Abstract:
This study investigates whether the widely documented daily correlated trading volume of stocks is driven by individual investor trading, institutional trading, or both. We find that at least 95 percent of NYSE and AMEX stocks exhibit statistically significant, positive serial correlation. Volume autocorrelation decreases with the level of institutional ownership of a stock. We also show that the rate of arrivals of new information to the market contributes to the clustering of the trades. When there is high information flow to the market, institutional trading generates a more pronounces effect on volume autocorrelation than individual investor trading. Our results are broadly consistent with the predictions of trading volume patterns suggested by most theoretical models of stock trading and by empirical research on investor trading.
Number of Pages in PDF File: 31
Keywords: institutions, autocorrelation, information flow
JEL Classification: G12, G14, G20
working papers series
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Date posted: November 3, 2003
Suggested CitationCovrig, Vicentiu and Ng, Lilian K., Volume Autocorrelation, Information and Investor Trading. Available at SSRN: http://ssrn.com/abstract=442200 or http://dx.doi.org/10.2139/ssrn.442200
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