Barone-Adesi, Giovanni Engle, Robert F. Mancini, Loriano 2008 We propose a new method for pricing options based on GARCH models with filtered historical innovaions. 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. application/pdf https://susi.usi.ch/global/documents/318169 https://n2t.net/ark:/12658/srd1318169 https://susi.usi.ch/documents/318169/files/baroneadesi_RFS_2008.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.1093/rfs/hhn031 info:eu-repo/semantics/altIdentifier/ark/12658/srd1318169 info:eu-repo/semantics/openAccess License undefined The review of financial studies. - Oxford Publishing Limited. - 2008, vol. 21, no. 3, p. 1223-1258 Option pricing GARCH model state price density Monte Carlo simulation info:eu-repo/classification/udc/33 A GARCH option pricing model with filtered historical simulation http://purl.org/coar/resource_type/c_6501