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A Bayesian analysis of the stochastic volatility model with regime-switching skewness in heavy-tailed errors is proposed using a generalized hyperbolic (GH) skew Student’s  t -distribution. The skewness parameter is allowed to shift according to a first-order Markov switching process. We summarize Bayesian methods for model fitting and discuss analyses of exchange rate return time series. Empirical results show that interpretable regime-switching skewness can improve model fit and Value-at-Risk performance in a comparison against several other SV models with constant skewness or jump diffusions.

Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns