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On the rate of convergence of estimating the Hurst parameter of rough stochastic volatility models

On the rate of convergence of estimating the Hurst parameter of rough stochastic volatility models ArXiv ID: 2504.09276 “View on arXiv” Authors: Unknown Abstract In [“Han & Schied, 2023, \textit{“arXiv 2307.02582”}”], an easily computable scale-invariant estimator $\widehat{"\mathscr{R"}}^s_n$ was constructed to estimate the Hurst parameter of the drifted fractional Brownian motion $X$ from its antiderivative. This paper extends this convergence result by proving that $\widehat{"\mathscr{R"}}^s_n$ also consistently estimates the Hurst parameter when applied to the antiderivative of $g \circ X$ for a general nonlinear function $g$. We also establish an almost sure rate of convergence in this general setting. Our result applies, in particular, to the estimation of the Hurst parameter of a wide class of rough stochastic volatility models from discrete observations of the integrated variance, including the rough fractional stochastic volatility model. ...

April 12, 2025 · 2 min · Research Team