Volatility Components, Affine Restrictions, and Nonnormal Innovations
比较了GARCH模型的不同设定（成分模型与标准GARCH、仿射与非仿射、正态与非正态GED）在拟合收益率和期权定价上的表现，发现非仿射模型在两方面均优于仿射模型，而成分结构在仿射模型中表现显著，非正态GED在拟合日收益率时优势明显但在期权定价中不显著。
Here we assess the return fitting and option valuation performance of generalized autoregressive conditional heteroscedasticity (GARCH) models. We compare component versus GARCH(1, 1) models, affine versus nonaffine GARCH models, and conditionally normal versus nonnormal GED models. We find that nonaffine models dominate affine models in terms of both fitting returns and option valuation. For the affine models, we find strong evidence in favor of the component structure for both returns and options; for the nonaffine models, the evidence is less convincing in option valuation. The evidence in favor of the nonnormal GED models is strong when fitting daily returns, but not when valuing options.