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RFS Advance Access published online on March 18, 2008

Review of Financial Studies, doi:10.1093/rfs/hhn031
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© The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

A GARCH Option Pricing Model with Filtered Historical Simulation

Giovanni Barone-Adesi
Swiss Finance Institute at the University of Lugano

Robert F. Engle
Stern School of Business, New York University

Loriano Mancini
Swiss Banking Institute, University of Zurich

Address correspondence to Giovanni Barone-Adesi, Swiss Finance Institute at the University of Lugano, Via Buffi 13, CH-6900 Lugano, Switzerland; telephone: +41-58-666-4753; fax: +41-58-666-4734; e-mail: baroneg{at}lu.unisi.ch

JEL Classification: G13


   Abstract

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.


For helpful comments, we thank Yacine Aït-Sahalia (the editor), two anonymous referees, Fulvio Corsi, Robert Elliott, Jens Jackwerth, and Claudia Ravanelli. Financial support from the NCCR-FinRisk Swiss National Science Foundation (Barone-Adesi and Mancini) and the University Research Priority Program "Finance and Financial Markets" University of Zurich (Mancini) is gratefully acknowledged.


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