Appraising Model Complexity in Option Pricing
研究了期权定价模型中增加复杂性是否值得，通过模型置信集比较了多种随机波动率跳跃扩散模型，发现简约模型往往表现更好。
ABSTRACT The research question we consider is whether incremental complexity in option pricing models is justified by incremental model performance. We apply the model confidence set as a formal model comparison approach in appraising stochastic volatility jump‐diffusion option pricing models, spanning affine and nonaffine specifications. Jumps in price with stochastic (constant) arrival intensity produce superior (inferior) outcomes. A parsimonious negative exponential price jump distribution outperforms the popular normal distribution. Jumps in volatility (synchronized or not) worsen model performance. A parsimonious nonlinear hyperbolic drift extension of the Heston model performs particularly well. Nonlinear CEV models generally do not produce appreciable model performance.