Calibrating Rough Volatility Models: A Convolutional Neural Network Approach

In this paper we use convolutional neural networks to find the Holder 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.