54 Pages Posted: 15 Oct 2004 Last revised: 29 Apr 2008
Date Written: January 2008
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 enhancing the model 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.
Keywords: Option pricing, GARCH model, state price density, Monte Carlo simulation
JEL Classification: G13
Suggested Citation: Suggested Citation
Barone-Adesi, Giovanni and Engle, Robert F. and Mancini, Loriano, A GARCH Option Pricing Model with Filtered Historical Simulation (January 2008). Review of Financial Studies, 2008. Available at SSRN: https://ssrn.com/abstract=603382 or http://dx.doi.org/10.2139/ssrn.603382
By David Bates