3 papers
q-fin.CP2021
Deep Hedging: Learning Risk-Neutral Implied Volatility Dynamics
Hans Buehler, Phillip Murray, Mikko S. Pakkanen +1
We present a numerically efficient approach for learning a risk-neutral measure for paths of simulated spot and option prices up to a finite horizon under convex transaction costs…
q-fin.ST2020
A Data-driven Market Simulator for Small Data Environments
Hans Bühler, Blanka Horvath, Terry Lyons +2
Neural network based data-driven market simulation unveils a new and flexible way of modelling financial time series without imposing assumptions on the underlying stochastic dynam…
q-fin.CP2019
Deep Hedging: Learning to Simulate Equity Option Markets
Magnus Wiese, Lianjun Bai, Ben Wood +1
We construct realistic equity option market simulators based on generative adversarial networks (GANs). We consider recurrent and temporal convolutional architectures, and assess t…