Optimal Execution of a Basket of Stocks under Regime-Switching Model Using Reinforcement Learning
Year: 2024
Type: article
Abstract: In this paper, we are concerned with the problem of successfully trading a portfolio of stocks when the overall marketplace is subject to change between various trends during a relatively short period. Such executions usually involve large positions of highly correlated assets. In this work, we address this problem as an optimal control of a multi-dimensional Markov switching process. We propose a solution based on a reinforcement learning methodology. We prove the convergence of our approximating scheme. We present an implementation of our algorithm using intra-day data.
Authors: Moustapha Pemy, Na Zhang
Institution: Towson University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4402315948