Volatility Models in Practice: Rough, Path-Dependent, or Markovian?

Research output: Contribution to journalArticlepeer-review

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 (Formula presented.) 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.

Original languageEnglish
Pages (from-to)796-817
Number of pages22
JournalMathematical Finance
Volume35
Issue number4
DOIs
Publication statusPublished - 1 Oct 2025

Keywords

  • SPX options
  • calibration
  • functional quantization
  • neural networks
  • pricing
  • stochastic volatility

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