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Robustness and sensitivity analyses for rough Volterra stochastic volatility models

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  • Jan Matas
  • Jan Posp'iv{s}il

Abstract

In this paper, we analyze the robustness and sensitivity of various continuous-time rough Volterra stochastic volatility models in relation to the process of market calibration. Model robustness is examined from two perspectives: the sensitivity of option price estimates and the sensitivity of parameter estimates to changes in the option data structure. The following sensitivity analysis consists of statistical tests to determine whether a given studied model is sensitive to changes in the option data structure based on the distribution of parameter estimates. Empirical study is performed on a data set consisting of Apple Inc. equity options traded on four different days in April and May 2015. In particular, the results for RFSV, rBergomi and $\alpha$RFSV models are provided and compared to the results for Heston, Bates, and AFSVJD models.

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  • Jan Matas & Jan Posp'iv{s}il, 2021. "Robustness and sensitivity analyses for rough Volterra stochastic volatility models," Papers 2107.12462, arXiv.org, revised Jun 2023.
    • Handle: RePEc:arx:papers:2107.12462
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    References listed on IDEAS

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