A1016
Title: Stochastic volatility with regimes, skew, fat tails, and leverage using returns and realized volatility for inference
Authors: Sebastian Trojan - None (Germany) [presenting]
Abstract: A general stochastic volatility (SV) model specification with leverage, heavy tails, skew, and switching regimes, using realized volatility (RV) as an auxiliary time series to improve inference on latent volatility is presented. The information content of the range, and of implied volatility using the VIX index, is also analyzed. Asymmetry in the observation error is modeled by the generalized hyperbolic skew Student-$t$ distribution, whose heavy and light tail enable substantial skewness. Database is the S\& P500 index. Number of regimes and dynamics differ dependent on the deployed auxiliary volatility proxy and are investigated for the financial crash period 2008/09 in more detail. An extended in-sample model selection is provided. An out-of-sample study comparing predictive ability of various model variants for a calm and a volatile period yields insights about the gains on forecasting performance that can be expected by incorporating different volatility proxies into the model. Findings indicate that including RV pays off mostly in more volatile market conditions, whereas in calmer environments SV specifications using no auxiliary series outperform. Results for the VIX as a measure of implied volatility point in a similar direction. The range as volatility proxy provides a superior in-sample fit, but its predictive performance is found to be weak.
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