We use a supervised deep convolution neural network to replicate the calibration of the Heston model to equity volatility surfaces. For this purpose we treat the implied volatility surface together with some auxiliary data, namely the strikes and moneyness of the corresponding options and the...

In this paper we consider the generation of implied volatility risk scenarios, with a special focus on swaption implied volatility smile, e.g., as modeled by a displaced SABR model.The generation of implied volatility risk scenarios is much more demanding than other risk factors, like interest...

We consider arbitrage-free interpolation of arbitrage-free input data of European option prices. The method derived is independent of the underlying (equity, rates, FX, etc.). A particular contribution of the paper is that for the chosen coordinate system and a wide variety of interpolation...

In this work we use the Parsimonious Multi–Asset Heston model recently developed in [Dimitroff et al., 2009] at Fraunhofer ITWM, Department Financial Mathematics, Kaiserslautern (Germany) and apply it to Quanto options. We give a summary of the model and its calibration scheme. A suitable...

In a recent paper "Deep Learning Volatility" a fast 2-step deep calibration algorithm for rough volatility models was proposed: in the first step the time consuming mapping from the model parameter to the implied volatilities is learned by a neural network and in the second step standard solver...