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Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects

1990; Wiley; Volume: 45; Issue: 1 Linguagem: Inglês

10.2307/2328817

1540-6261

Christopher G. Lamoureux, William D. Lastrapes,

Complex Systems and Time Series Analysis

The Journal of FinanceVolume 45, Issue 1 p. 221-229 Shorter Paper Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects CHRISTOPHER G. LAMOUREUX, CHRISTOPHER G. LAMOUREUXSearch for more papers by this authorWILLIAM D. LASTRAPES, WILLIAM D. LASTRAPES John M. Olin School of Business, Washington University and Department of Economics, College of Business Administration, Louisiana State University, respectively. This work was completed while Lamoureux was at Louisiana State University. This paper has benefitted from the comments of seminar participants at LSU and Washington University. We are especially grateful to Richard T. Baillie, Frank Diebold, Phil Dybvig, Rob Engle, Clive Granger, Mel Jameson, Ken Kroner, Chowdhury Mustafa, David Mayers (the co-editor), Percy Poon, Mike Salemi, Gary Sanger, George Tauchen, and an anonymous referee. All errors remain ours.Search for more papers by this author CHRISTOPHER G. LAMOUREUX, CHRISTOPHER G. LAMOUREUXSearch for more papers by this authorWILLIAM D. LASTRAPES, WILLIAM D. LASTRAPES John M. Olin School of Business, Washington University and Department of Economics, College of Business Administration, Louisiana State University, respectively. This work was completed while Lamoureux was at Louisiana State University. This paper has benefitted from the comments of seminar participants at LSU and Washington University. We are especially grateful to Richard T. Baillie, Frank Diebold, Phil Dybvig, Rob Engle, Clive Granger, Mel Jameson, Ken Kroner, Chowdhury Mustafa, David Mayers (the co-editor), Percy Poon, Mike Salemi, Gary Sanger, George Tauchen, and an anonymous referee. All errors remain ours.Search for more papers by this author First published: March 1990 https://doi.org/10.1111/j.1540-6261.1990.tb05088.xCitations: 522 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat ABSTRACT This paper provides empirical support for the notion that Autoregressive Conditional Heteroskedasticity (ARCH) in daily stock return data reflects time dependence in the process generating information flow to the market. Daily trading volume, used as a proxy for information arrival time, is shown to have significant explanatory power regarding the variance of daily returns, which is an implication of the assumption that daily returns are subordinated to intraday equilibrium returns. Furthermore, ARCH effects tend to disappear when volume is included in the variance equation. REFERENCES Baillie, Richard and Tim, Bollerslev, 1989, The message in daily exchange rates: A conditional variance tale, Journal of Business and Economic Statistics, Forthcoming. Bollerslev, Tim, 1986, Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics 31, 307–327. Bollerslev, Tim, 1987, A conditionally heteroskedastic time series model for speculative prices and rates of return, Review of Economics and Statistics 69, 542–547. Clark, Peter, 1973, A subordinated stochastic process model with finite variance for speculative prices, Econometrica 41, 135–56. 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