A GARCH option pricing model with filtered historical simulation

• 成果类型: Article
• 署名作者: Barone-Adesi, Giovanni; Engle, Robert F.; Mancini, Loriano
• 署名单位: Universita della Svizzera Italiana; Swiss Finance Institute (SFI); New York University; University of Zurich
• 刊物名称: REVIEW OF FINANCIAL STUDIES
• ISSN/ISSBN: 0893-9454
• DOI: 10.1093/rfs/hhn031
• 发表日期: 2008
• 页码: 1223
• 关键词: stochastic volatility; risk-aversion; asset prices; conditional heteroskedasticity; implied volatility; ARCH models; valuation; consumption; returns; MARKETS

摘要

We propose a new method for pricing options based on GARCH models with filtered historical innovations. In an incomplete market framework, we allow for different distributions of historical and pricing return dynamics, which enhances the model's flexibility to fit market option prices. An extensive empirical analysis based on S&P 500 index options shows that our model outperforms other competing GARCH pricing models and ad hoc Black-Scholes models. We show that the flexible change of measure, the asymmetric GARCH volatility, and the nonparametric innovation distribution induce the accurate pricing performance of our model. Using a nonparametric approach, we obtain decreasing state-price densities per unit probability as suggested by economic theory and corroborating our GARCH pricing model. Implied volatility smiles appear to be explained by asymmetric volatility and negative skewness of filtered historical innovations.