VIX option pricing through nonaffine GARCH dynamics and semianalytical formula
为波动率指数（VIX）期权定价开发了非仿射GARCH模型下的近似解析公式，通过三种展开方法在四个实证模型下评估表现，发现肥尾加权核能显著减少误差，而条件矩泰勒展开在高持续性参数下可能发散。
Abstract This paper develops analytical approximations for volatility index (VIX) option pricing under nonaffine generalized autoregressive conditional heteroskedasticity (GARCH) models as advocated by Christoffersen et al. We obtain the approximation formulae for pricing VIX options and then evaluate their performance with three expansions under four empirically well‐tested models. Our numerical experiments find that the weighted expansion generated by the fat‐tailed weighting kernel can significantly reduce approximation error over the Gram‐Charlier expansion; the Taylor expansion of conditional moments can lead to divergence for parameters with certain high persistence in the affine GARCH, nonlinear asymmetric GARCH, and Glosten‐Jagannathan‐Runkle GARCH models, while surviving during high persistence in the exponential GARCH.