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Time-inhomogeneous Gaussian stochastic volatility models: Large deviations and super roughness (2002.05143v8)
Published 12 Feb 2020 in math.PR and q-fin.MF
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.