Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities

Allan Timmermann and Gabriel Perez-Quiros
Authors registered in the RePEc Author Service: Gabriel Perez Quiros

FMG Discussion Papers from Financial Markets Group

Abstract: Markov switching models with time-varying means, variances and mixing weights are applied to characterize business cycle variation in the probability distribution and higher order moments of stock returns. This allows us to provide a comprehensive characterization of risk that goes well beyond the mean and variance of returns. Several mixture models with different specifications of the state transition are compared and we propose a new mixture of Gaussian and student-t distributions that captures outliers in returns. The models produce very similar expected returns and volailites but imply very different time series for conditional skewness, kurtosis and predictive density. Consistent with economic theory, the gains in predictive accuracy from considering two-state mixture models rather than a single-state specification are higher for small firms than for large firms.

Date: 2000-10
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities (2001)
Working Paper: Business cycle asymmetries in stock returns: evidence from higher order moments and conditional densities (2001)
Working Paper: Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities (2001)
Working Paper: Business cycle asymmetries in stock returns: evidence from higher order moments and conditional densities (2000)
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