Volatility Models in Practice: Rough, Path‐Dependent, or Markovian?
基于SPX期权数据，实证检验粗糙波动率模型，发现其与微笑曲线全局形状不符，短期限表现不如单因子马尔可夫模型，并识别出更优的非粗糙路径依赖和双因子马尔可夫模型。
ABSTRACT We present an empirical study examining several claims related to option prices in rough volatility literature using SPX options data. Our results show that rough volatility models with the parameter are inconsistent with the global shape of SPX smiles. In particular, the at‐the‐money SPX skew is incompatible with the power‐law shape generated by these models, which increases too fast for short maturities and decays too slowly for longer maturities. For maturities between 1 week and 3 months, rough volatility models underperform one‐factor Markovian models with the same number of parameters. When extended to longer maturities, rough volatility models do not consistently outperform one‐factor Markovian models. Our study identifies a non‐rough path‐dependent model and a two‐factor Markovian model that outperform their rough counterparts in capturing SPX smiles between 1 week and 3 years, with only three to four parameters.