Calibrating rough volatility models: a convolutional neural network approach

Henry Stone

Papers from arXiv.org

Abstract: In this paper we use convolutional neural networks to find the H\"older 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: 2018-12, Revised 2019-07
New Economics Papers: this item is included in nep-big, nep-cmp and nep-ets
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1812.05315

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