Weak approximations and VIX option price expansions in forward variance curve models
Florian Bourgey, Stefano De Marco, and Emmanuel Gobet

TL;DR
This paper develops explicit approximation formulas for VIX futures and options within forward variance models, especially Bergomi models, using weak approximation techniques that handle fractional kernels and non-smooth payoffs, applicable across various maturities.
Contribution
It introduces a novel weak approximation approach for VIX derivatives in rough volatility models, accommodating fractional kernels and non-smooth payoffs without relying on small-time asymptotics.
Findings
Accurate explicit formulas for VIX options in complex models
Effective handling of fractional kernels and non-smooth payoffs
Numerical results show good calibration to market data
Abstract
We provide explicit approximation formulas for VIX futures and options in forward variance models, with particular emphasis on the family of so-called Bergomi models: the one-factor Bergomi model [Bergomi, Smile dynamics II, Risk, 2005], the rough Bergomi model [Bayer, Friz, and Gatheral, Pricing under rough volatility, Quantitative Finance, 16(6):887-904, 2016], and an enhanced version of the rough model that can generate realistic positive skew for VIX smiles -- introduced simultaneously by De Marco [Bachelier World Congress, 2018] and Guyon [Bachelier World Congress, 2018] on the lines of [Bergomi, Smile dynamics III, Risk, 2008], that we refer to as 'mixed rough Bergomi model'. Following the methodology set up in [Gobet and Miri, Weak approximation of averaged diffusion processes. Stochastic Process.\ Appl., 124(1):475-504, 2014], we derive weak approximations for the law of the…
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Taxonomy
TopicsStochastic processes and financial applications · Reservoir Engineering and Simulation Methods · Stock Market Forecasting Methods
MethodsDiffusion
