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arXiv · 2002.05143

Time-inhomogeneous Gaussian stochastic volatility models: Large deviations and super roughness

Archil Gulisashvili
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Abstract

We introduce time-inhomogeneous stochastic volatility models, in which the volatility is described by a nonnegative function of a Volterra type continuous Gaussian process that may have very rough sample paths. The main results obtained in the paper are sample path and small-noise large deviation principles for the log-price process in a time-inhomogeneous super rough Gaussian model under very mild restrictions. We use these results to study the asymptotic behavior of binary barrier options, exit time probability functions, and call options.

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Archil Gulisashvili. 2020-02-12. Time-inhomogeneous Gaussian stochastic volatility models: Large deviations and super roughness. https://arxiv.org/abs/2002.05143

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