Robustness and sensitivity analyses of rough Volterra stochastic volatility models

Jan Matas and Jan Pospíšil ()
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Jan Matas: University of West Bohemia
Jan Pospíšil: University of West Bohemia

Annals of Finance, 2023, vol. 19, issue 4, No 4, 523-543

Abstract: 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 $$\alpha $$ α RFSV models are provided and compared to the results for Heston, Bates, and AFSVJD models.

Keywords: Volterra stochastic volatility; Rough volatility; Rough Bergomi model; Robustness analysis; Sensitivity analysis (search for similar items in EconPapers)
JEL-codes: C12 C52 C58 C63 G12 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10436-023-00433-2

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