Adaptive Algorithm for Selecting the Optimal Trading Strategy Based on Reinforcement Learning for Managing a Hedge Fund
B Belyakov, D Sizykh - IEEE Access, 2024 - ieeexplore.ieee.org
In hedge fund management, the ability to dynamically select optimal trading strategies is
paramount for maximizing returns and mitigating risk. This paper presents a pioneering …
paramount for maximizing returns and mitigating risk. This paper presents a pioneering …
Structured multi-agent-based model for bankruptcy contagion with cash flow
J Zhang, C Xia - IEEE Access, 2020 - ieeexplore.ieee.org
Numerous multi-agent models have been proposed for various economic phenomena,
especially for the bankruptcy contagion phenomenon, which is a seriously destructive …
especially for the bankruptcy contagion phenomenon, which is a seriously destructive …
Reinforcement Learning Methods in Algorithmic Trading
O Guéanta - Machine Learning and Data Sciences for Financial …, 2023 - cambridge.org
This chapter is dedicated to the third paradigm of machine learning alongside supervised
and unsupervised learning: reinforcement learning (RL). RL methods have recently been …
and unsupervised learning: reinforcement learning (RL). RL methods have recently been …
Order book regulatory impact on stock market quality: a multi-agent reinforcement learning perspective
J Lussange, B Gutkin - arXiv preprint arXiv:2302.04184, 2023 - arxiv.org
Recent technological developments have changed the fundamental ways stock markets
function, bringing regulatory instances to assess the benefits of these developments. In …
function, bringing regulatory instances to assess the benefits of these developments. In …