A GARCH Option Pricing Model with Filtered Historical Simulation



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.


Root Mean Square Error Option Price Price Model Stochastic Volatility Implied Volatility 
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