Short-time asymptotics for non self-similar stochastic volatility models

Giacomo Giorgio; Barbara Pacchiarotti; Paolo Pigato

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arXiv · 2204.10103

Short-time asymptotics for non self-similar stochastic volatility models

Giacomo Giorgio·Barbara Pacchiarotti·Paolo Pigato

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Abstract

We provide a short-time large deviation principle (LDP) for stochastic volatility models, where the volatility is expressed as a function of a Volterra process. This LDP does not require strict self-similarity assumptions on the Volterra process. For this reason, we are able to apply such an LDP to two notable examples of non self-similar rough volatility models: models where the volatility is given as a function of a log-modulated fractional Brownian motion [Bayer et al., Log-modulated rough stochastic volatility models. SIAM J. Financ. Math, 2021, 12(3), 1257-1284], and models where it is given as a function of a fractional Ornstein-Uhlenbeck (fOU) process [Gatheral et al., Volatility is rough. Quant. Finance, 2018, 18(6), 933-949]. In both cases we derive consequences for short-maturity European option prices, implied volatility surfaces and implied volatility skew. In the fOU case we also discuss moderate deviations pricing and simulation results.

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Giacomo Giorgio, Barbara Pacchiarotti, Paolo Pigato. 2022-04-21. Short-time asymptotics for non self-similar stochastic volatility models. https://arxiv.org/abs/2204.10103

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