Time-inhomogeneous Gaussian stochastic volatility models: Large deviations and super roughness
Probability
2021-01-01 v8 Mathematical Finance
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.
Cite
@article{arxiv.2002.05143,
title = {Time-inhomogeneous Gaussian stochastic volatility models: Large deviations and super roughness},
author = {Archil Gulisashvili},
journal= {arXiv preprint arXiv:2002.05143},
year = {2021}
}