1 citations · 1 across the 10 of their papers we have counts for
10 papers
Stochastic Maximum Principle for McKean-Vlasov Control with Discrete Path Dependence
Yadh Hafsi, Samy Mekkaoui, Huyên Pham
We study a class of McKean-Vlasov control problems with discrete path dependence. The coefficients and cost functional may depend on finitely many past values of the controlled sta…
Deep-MKV-TS: Path-Dependent McKean--Vlasov Control for Financial Time Series Generation
Samer El Boustany, Théo Basseras, Samy Mekkaoui +3
We introduce Deep-MKV-TS, a path-dependent McKean-Vlasov framework for financial scenario generation. The stochastic dynamics are chosen by matching selected path and volatility fe…
Policy Gradient Learning for Distributionally Robust Markov Decision Processes under Wasserstein Ambiguity
Yadh Hafsi, Samy Mekkaoui, Huyên Pham +1
We study finite-horizon Markov decision processes under distributional uncertainty in the transition kernels and develop a policy-gradient framework for Wasserstein distributionall…
Learning Generative Dynamics with Soft Path-Law Constraints: A McKean-Vlasov FBSDE Approach
Samer El Boustany, Samy Mekkaoui, Yadh Hafsi +2
We introduce a unified framework for learning stochastic dynamics from distributional observations and discretely observed trajectories. The key contribution is to combine soft law…
Trading in CEXs and DEXs with Priority Fees and Stochastic Delays
Philippe Bergault, Yadh Hafsi, Leandro Sánchez-Betancourt
We develop a mixed control framework that combines absolutely continuous controls with impulse interventions subject to stochastic execution delays. The model extends current impul…
Reinforcement Learning in Queue-Reactive Models: Application to Optimal Execution
Tomas Espana, Yadh Hafsi, Fabrizio Lillo +1
We investigate the use of Reinforcement Learning for the optimal execution of meta-orders, where the objective is to execute incrementally large orders while minimizing implementat…
Optimal Execution under Liquidity Uncertainty
Etienne Chevalier, Yadh Hafsi, Vathana Ly Vath +1
We study an optimal execution strategy for purchasing a large block of shares over a fixed time horizon. The execution problem is subject to a general price impact that gradually d…
Optimal Execution with Reinforcement Learning
Yadh Hafsi, Edoardo Vittori
This study investigates the development of an optimal execution strategy through reinforcement learning, aiming to determine the most effective approach for traders to buy and sell…
Optimal Execution under Incomplete Information
Etienne Chevalier, Yadh Hafsi, Vathana Ly Vath
We study optimal liquidation strategies under partial information for a single asset within a finite time horizon. We propose a model tailored for high-frequency trading, capturing…
Uncovering Market Disorder and Liquidity Trends Detection
Etienne Chevalier, Yadh Hafsi, Vathana Ly Vath
The primary objective of this paper is to conceive and develop a new methodology to detect notable changes in liquidity within an order-driven market. We study a market liquidity m…