Calibrating rough volatility models: a convolutional neural network approach

Henry Stone

Quantitative Finance, 2020, vol. 20, issue 3, 379-392

Abstract: In this paper, we use convolutional neural networks to find the Hölder exponent of simulated sample paths of the rBergomi model, a recently proposed stock price model used in mathematical finance. We contextualise this as a calibration problem, thereby providing a very practical and useful application.

Date: 2020
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DOI: 10.1080/14697688.2019.1654126

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