The Determinants of Conditional Autocorrelation in Stock Returns

Posted: 19 Aug 2002

See all articles by Michael D. McKenzie

Michael D. McKenzie

The University of Sydney - Discipline of Finance; University of Cambridge - Cambridge Endowment for Research in Finance (CERF); Financial Research Network (FIRN)

Robert W. Faff

University of Queensland

Abstract

This paper investigates whether return volatility, trading volume, return asymmetry, business cycles and day-of-the-week are potential determinants of conditional autocorrelation in stock returns. The primary focus is on the role of feedback trading and the interplay of return volatility. We present empirical evidence using conditional autocorrelation estimates generated from multivariate generalised autoregressive conditional heteroscedasticity (M-GARCH) models for individual U.S. stock and index data. In addition to return volatility, we find that trading volume and market returns are important in explaining the time-varying patterns of return autocorrelation.

JEL Classification: G12

Suggested Citation

McKenzie, Michael David and Faff, Robert W., The Determinants of Conditional Autocorrelation in Stock Returns. Journal of Financial Research, Forthcoming. Available at SSRN: https://ssrn.com/abstract=315360

Michael David McKenzie (Contact Author)

The University of Sydney - Discipline of Finance ( email )

Level 2 9 Castlereagh Street
Sydney, NSW 2000
Australia
+61 2 9114 0578 (Phone)
+61 2 9351 6461 (Fax)

University of Cambridge - Cambridge Endowment for Research in Finance (CERF) ( email )

Trumpington Street
Cambridge, CB2 1AG
United Kingdom

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Robert W. Faff

University of Queensland ( email )

St Lucia
Brisbane, Queensland 4072
Australia

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