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Article Dans Une Revue The Annals of Applied Probability Année : 2021

Precise asymptotics: robust stochastic volatility models

Peter K. Friz
  • Fonction : Auteur
Paolo Pigato

Résumé

We present a new methodology to analyze large classes of (classical and rough) stochastic volatility models, with special regard to short-time and small noise formulae for option prices. Our main tool is the theory of regularity structures, which we use in the form of [Bayer et al; A regularity structure for rough volatility, 2017]. In essence, we implement a Laplace method on the space of models (in the sense of Hairer), which generalizes classical works of Azencott and Ben Arous on path space and then Aida, Inahama--Kawabi on rough path space. When applied to rough volatility models, e.g. in the setting of [Forde-Zhang, Asymptotics for rough stochastic volatility models, 2017], one obtains precise asymptotic for European options which refine known large deviation asymptotics.

Dates et versions

hal-03099736 , version 1 (06-01-2021)

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Peter K. Friz, Paul Gassiat, Paolo Pigato. Precise asymptotics: robust stochastic volatility models. The Annals of Applied Probability, 2021, ⟨10.1214/20-AAP1608⟩. ⟨hal-03099736⟩
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