Vector quantisation enables fast daily calibration of mixed Bergomi models to VIX futures and options, and a one-factor version may suffice.
Volatility models in practice: Rough, Path-dependent or Markovian?
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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 $H \in (0,1/2)$ 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 one week and three 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 one week and three years, with only 3 to 4 parameters.
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Pricing and Calibration of VIX Derivatives in Mixed Bergomi Models via Quantisation
Vector quantisation enables fast daily calibration of mixed Bergomi models to VIX futures and options, and a one-factor version may suffice.