3 citations · 6 across the 5 of their papers we have counts for
5 papers
An elementary approach to delta and gamma hedging, and the Black--Scholes PDE
John Armstrong, Purba Das
We show how the robustness of gamma hedging can be understood just using the concepts of variation along a partition sequence and Taylor's theorem. There is no need to def…
Abundant Superintegrable Systems and Hessian Structures
John Armstrong, Andreas Vollmer
We show that a large class of non-degenerate second-order (maximally) superintegrable systems gives rise to Hessian structures, which admit natural (Hessian) coordinates adapted to…
Deep Gamma Hedging
John Armstrong, George Tatlow
We train neural networks to learn optimal replication strategies for an option when two replicating instruments are available, namely the underlying and a hedging option. If the pr…
Low-dimensional approximations of the conditional law of Volterra processes: a non-positive curvature approach
Reza Arabpour, John Armstrong, Luca Galimberti +2
Predicting the conditional evolution of Volterra processes with stochastic volatility is a crucial challenge in mathematical finance. While deep neural network models offer promise…
Gamma Hedging and Rough Paths
John Armstrong, Andrei Ionescu
We apply rough-path theory to study the discrete-time gamma-hedging strategy. We show that if a trader knows that the market price of a set of European options will be given by a d…