3 citations · 5 across the 5 of their papers we have counts for
5 papers · 1 filter
Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions
Phillip Murray, Ben Wood, Hans Buehler +2
We present a method for finding optimal hedging policies for arbitrary initial portfolios and market states. We develop a novel actor-critic algorithm for solving general risk-aver…
Deep Bellman Hedging
Hans Buehler, Phillip Murray, Ben Wood
We present an actor-critic-type reinforcement learning algorithm for solving the problem of hedging a portfolio of financial instruments such as securities and over-the-counter der…
Multi-Asset Spot and Option Market Simulation
Magnus Wiese, Ben Wood, Alexandre Pachoud +4
We construct realistic spot and equity option market simulators for a single underlying on the basis of normalizing flows. We address the high-dimensionality of market observed cal…
Deep Hedging: Learning to Remove the Drift under Trading Frictions with Minimal Equivalent Near-Martingale Measures
Hans Buehler, Phillip Murray, Mikko S. Pakkanen +1
We present a machine learning approach for finding minimal equivalent martingale measures for markets simulators of tradable instruments, e.g. for a spot price and options written…
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…