The Determinants of Conditional Autocorrelation in Stock Returns
AbstractWe investigate whether return volatility, trading volume, return asymmetry, business cycles, and day-of-the-week are potential determinants of conditional autocorrelation in stock returns. Our 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 generalized autoregressive conditional heteroskedasticity (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. 2003 The Southern Finance Association and the Southwestern Finance Association.
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Bibliographic InfoArticle provided by Southern Finance Association & Southwestern Finance Association in its journal Journal of Financial Research.
Volume (Year): 26 (2003)
Issue (Month): 2 ()
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