GARCH Option Valuation: Theory and Evidence

We survey the theory and empirical evidence on generalized autoregressive conditional heteroskedasticity (GARCH) option valuation models. We provide an overview of different functional forms for the volatility dynamic, multifactor models, non-normal innovation distributions, and valuation techniques. We also discuss alternative pricing kernels used for risk neutralization, various strategies for empirical implementation, and the links between GARCH and stochastic volatility models. In the appendices, we provide Matlab computer code for option pricing via Monte Carlo simulation for nonaffine models as well as via Fourier inversion for affine models.