The Quadratic Rough Heston Model and the Joint S&P 500/VIX Smile Calibration Problem
By Jim Gatheral, Paul Jusselin, Mathieu Rosenbaum. Social Science Research Network, 2020
59 citations recorded by the source corpus.
Fitting simultaneously SPX and VIX smiles is known to be one of the most challenging problems in volatility modeling. A long-standing conjecture due to Julien Guyon is that it may not be possible to calibrate jointly these two quantities with a model with continuous sample-paths. We present the quadratic rough Heston model as a counterexample to this conjecture. The key idea is the combination of rough volatility together with a price-feedback (Zumbach) effect.
Subfields: Economics and Econometrics, Finance, Mathematical Physics
View Paper: https://www.semanticscholar.org/paper/125f7d04544c37124d382bdcdf6d9e830718be48
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Citations in the corpus
- Joint calibration to SPX and VIX options with signature‐based models (2023, methodology): “Even though the roughness of the trajectories found in Gatheral et al. (2018), can also be explained by the estimation procedure as discussed e.g. in Cont and Das (2023), the non-Markovianity given by the fractional Brownian motion with Hurst parameter H < 0 .”