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Found 7 papers, 3 papers with code
Risk premium and rough volatility
One the one hand, rough volatility has been shown to provide a consistent framework to capture the properties of stock price dynamics both under the historical measure and for pricing purposes.
Rough multifactor volatility for SPX and VIX options
We provide explicit small-time formulae for the at-the-money implied volatility, skew and curvature in a large class of models, including rough volatility models and their multi-factor versions.
Portfolio optimisation with options
We develop a new analysis for portfolio optimisation with options, tackling the three fundamental issues with this problem: asymmetric options' distributions, high dimensionality and dependence structure.
Clustering Market Regimes using the Wasserstein Distance
The problem of rapid and automated detection of distinct market regimes is a topic of great interest to financial mathematicians and practitioners alike.
Asymptotics for volatility derivatives in multi-factor rough volatility models
We present small-time implied volatility asymptotics for Realised Variance (RV) and VIX options for a number of (rough) stochastic volatility models via large deviations principle.
Deep Learning Volatility
We present a neural network based calibration method that performs the calibration task within a few milliseconds for the full implied volatility surface.
Mathematical Finance
Functional central limit theorems for rough volatility
The non-Markovian nature of rough volatility processes makes Monte Carlo methods challenging and it is in fact a major challenge to develop fast and accurate simulation algorithms.
Probability Pricing of Securities 60F17, 60F05, 60G15, 60G22, 91G20, 91G60, 91B25
