We present a neural network-based calibration method that performs the calibration task
within a few milliseconds for the full implied volatility surface. The framework is consistently …

In this paper, we present a comprehensive survey of continuous stochastic volatility models,
discussing their historical development and the key stylized facts that have driven the field …

We conduct an empirical analysis of rough and classical stochastic volatility models to the
SPX and VIX options markets. Our analysis focusses primarily on calibration quality and is …

We present a neural network based calibration method that performs the calibration task
within a few milliseconds for the full implied volatility surface. The framework is consistently …

The rough Bergomi model, introduced by Bayer et al.[Quant. Finance, 2016, 16 (6), 887–
904], is one of the recent rough volatility models that are consistent with the stylised fact of …

Since VIX options started trading in 2006, many researchers have tried to build a model that
jointly and exactly calibrates to the prices of S&P 500 (SPX) options, VIX futures and VIX …

We discuss the pricing and hedging of volatility options in some rough volatility models. First,
we develop efficient Monte Carlo methods and asymptotic approximations for computing …

The non-Markovian nature of rough volatility makes Monte Carlo methods challenging, and
it is in fact a major challenge to develop fast and accurate simulation algorithms. We provide …

We introduce the notion of rough local stochastic volatility models, extending the classical
concept to the case where volatility is driven by some Volterra process. In this setting, we …

We solve for the first time a longstanding puzzle of quantitative finance that has often been
described as the holy grail of volatility modelling: build a model that jointly and exactly …