Bayesian analysis of multivariate stochastic volatility with skew return distribution |
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Authors: | Jouchi Nakajima |
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Institution: | Department of Statistical Science, Duke University, Durham, North Carolina, USA |
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Abstract: | Multivariate stochastic volatility models with skew distributions are proposed. Exploiting Cholesky stochastic volatility modeling, univariate stochastic volatility processes with leverage effect and generalized hyperbolic skew t-distributions are embedded to multivariate analysis with time-varying correlations. Bayesian modeling allows this approach to provide parsimonious skew structure and to easily scale up for high-dimensional problem. Analyses of daily stock returns are illustrated. Empirical results show that the time-varying correlations and the sparse skew structure contribute to improved prediction performance and Value-at-Risk forecasts. |
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Keywords: | Generalized hyperbolic skew t-distribution multivariate stochastic volatility portfolio allocation skew selection stock returns value at risk |
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