Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities
By Gabriel Pérez-Quirós, Allan G. Timmermann. Social Science Research Network, 2001
110 citations recorded by the source corpus.
Markow switching models with time-varying means, variances and mixing weights are applied to characterise 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 volatilities 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. JEL Classification: C22, C52
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/0ab09b41c78bfc700254bb1ea4f5ae281f5158cd
Citations in the corpus
- New Evidence of Asymmetric Dependence Structures in International Equity Markets (2008, unknown): “19The idea of mixtures of different distributions can also be found in Perez-Quiros and Timmermann (2001).”
- On More Robust Estimation of Skewness and Kurtosis: Simulation and Application to the S&P500 Index (2003, unknown): “Important recent work on mixture models of this sort is that of Timmermann (2000) and Perez-Quiros and Timmermann (2001) .”
- Time-varying Integration and International diversification strategies (2009, unknown): “Second, regime-switching models typically accommodate some of the nonlinearities that may show up in higher order moments, such as skewness and kurtosis, as well as asymmetric volatility (see e.g. Perez-Quiros and Timmermann, 2001).”
- Time‐Varying Transition Probabilities for Markov Regime Switching Models (2017, unknown): “Following Perez-Quiros and Timmermann (2001), the first two conditional moments for our two-regime Markov-switching model are given by t D EŒyt jIt 1 D 0P Œxt D 0jIt 1 C 1P Œxt D 1jIt 1 ; 2t D V Œ.yt t /2jIt 1 D 2 C P Œxt D 0jIt 1 .”