The Determinants of Conditional Autocorrelation in Stock Returns
Posted: 19 Aug 2002
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
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