8 papers
Liquidity Provision and Rebate Design in Option Markets
Samuel N. Cohen, Lyndon Drake, Zihan Guo +1
We provide a model for the nested optimisation problem of market making and rebate design problems in option markets and find optimal strategies. A single market maker trades multi…
Extending SSMs with the Exponentially Weighted Signature
Alexandre Bloch, Samuel N. Cohen, Terry Lyons +3
We introduce the exponentially weighted signature (EWS), a continuous-time model that computes iterated integrals of a path, where each increment is weighted by the matrix exponent…
Linking Path-Dependent and Stochastic Volatility Models
Samuel N. Cohen, Cephas Svosve
We explore a link between stochastic volatility (SV) and path-dependent volatility (PDV) models. Using assumed density filtering, we map a given SV model into a corresponding PDV r…
Mean-Field Generalisation Bounds for Learning Controls in Stochastic Environments
Boris Baros, Samuel N. Cohen, Christoph Reisinger
We consider a data-driven formulation of the classical discrete-time stochastic control problem. Our approach exploits the natural structure of many such problems, in which signifi…
Neural Actor-Critic Methods for Hamilton-Jacobi-Bellman PDEs: Asymptotic Analysis and Numerical Studies
Samuel N. Cohen, Jackson Hebner, Deqing Jiang +1
We mathematically analyze and numerically study an actor-critic machine learning algorithm for solving high-dimensional Hamilton-Jacobi-Bellman (HJB) partial differential equations…
Hyperbolic contractivity and the Hilbert metric on probability measures
Samuel N. Cohen, Eliana Fausti
This paper gives a self-contained introduction to the Hilbert projective metric and its fundamental properties, with a particular focus on the space of probability me…
Arbitrage-free neural-SDE market models
Samuel N. Cohen, Christoph Reisinger, Sheng Wang
Modelling joint dynamics of liquid vanilla options is crucial for arbitrage-free pricing of illiquid derivatives and managing risks of option trade books. This paper develops a non…
Black-box model risk in finance
Samuel N. Cohen, Derek Snow, Lukasz Szpruch
Machine learning models are increasingly used in a wide variety of financial settings. The difficulty of understanding the inner workings of these systems, combined with their wide…