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GH skew Student’s t-distribution in stochastic volatility model with application to stock returns

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Abstract

This paper represents empirical studies of SV models with a generalized hyperbolic (GH) skew Student's t-error distribution to embed both asymmetric heavy-tailness and leverage effects for financial time series. An efficient Markov chain Monte Carlo estimation method is described and the model is fit to daily S&P500 stock returns. The practical importance of the proposed model is highlighted through the model comparison based on the marginal likelihood, Value at Risk (VaR) and expected shortfall. The empirical results show that incorporating leverage and asymmetric heavy-tailness contributes to the model fit and predicting the expected shortfall.
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