Correct implied volatility shapes and reliable pricing in the rough Heston model
Svetlana Boyarchenko, Sergei Levendorski\v{i}

TL;DR
This paper improves option pricing accuracy in the rough Heston model by using advanced numerical methods, identifies issues with current calibration techniques causing spurious volatility surfaces, and proposes a new principle to enhance calibration reliability.
Contribution
It introduces a Conformal Bootstrap principle to prevent ghost calibration errors and demonstrates how to achieve fast, accurate option pricing and calibration in the rough Heston model.
Findings
Fast and accurate pricing of vanilla options using modified Fourier inversion methods.
Identification of calibration errors leading to spurious volatility surfaces.
Proposal of a new calibration approach to avoid ghost calibration errors.
Abstract
We use modifications of the Adams method and very fast and accurate sinh-acceleration method of the Fourier inversion (iFT) (S.Boyarchenko and Levendorski\u{i}, IJTAF 2019, v.22) to evaluate prices of vanilla options; for options of moderate and long maturities and strikes not very far from the spot, thousands of prices can be calculated in several msec. with relative errors of the order of 0.5\% and smaller running Matlab on a Mac with moderate characteristics. We demonstrate that for the calibrated set of parameters in Euch and Rosenbaum, Math. Finance 2019, v. 29, the correct implied volatility surface is significantly flatter and fits the data very poorly, hence, the calibration results in op.cit. is an example of the {\em ghost calibration} (M.Boyarchenko and Levendorki\u{i}, Quantitative Finance 2015, v. 15): the errors of the model and numerical method almost cancel one another.…
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Taxonomy
TopicsStochastic processes and financial applications
MethodsSparse Evolutionary Training
