期刊名称：CORE Discussion Papers / Center for Operations Research and Econometrics (UCL), Louvain
出版年度：2009
卷号：1
出版社：Center for Operations Research and Econometrics (UCL), Louvain
摘要：While stochastic volatility models improve on the option pricing error when
compared to the Black-Scholes-Merton model, mispricings remain. This paper uses
mixed normal heteroskedasticity models to price options. Our model allows for
significant negative skewness and time varying higher order moments of the risk
neutral distribution. Parameter inference using Gibbs sampling is explained and we
detail how to compute risk neutral predictive densities taking into account
parameter uncertainty. When forecasting out-of-sample options on the S&P 500
index, substantial improvements are found compared to a benchmark model in
terms of dollar losses and the ability to explain the smirk in implied volatilities.
