Risk-Adjusted Deep Reinforcement Learning for Portfolio Optimization: A Multi-reward Approach

Abstract Portfolio optimization is a widely studied topic in quantitative finance. Recent advances in portfolio optimization have shown promising capabilities of deep reinforcement learning algorithms to dynamically allocate funds across various potential assets to meet the objectives of prospective...

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Prif Awduron:	Himanshu Choudhary, Arishi Orra, Kartik Sahoo, Manoj Thakur
Fformat:	Artigo
Iaith:	Inglês
Cyhoeddwyd:	Springer 2025-05-01
Cyfres:	International Journal of Computational Intelligence Systems
Pynciau:	Deep reinforcement learning Portfolio optimization Convolutional neural network Proximal policy optimization Quantitative finance
Mynediad Ar-lein:	https://doi.org/10.1007/s44196-025-00875-8
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