Multiagent-based deep reinforcement learning framework for multi-asset adaptive trading and portfolio management

The highly dynamic nature of stock markets has motivated researchers to propose various supervised learning models to assist investors to optimize financial performance. Machine learning models have been used to predict price trends, and approaches have been proposed for portfolio management. Howeve...

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Vydáno v:	Neurocomputing (Amsterdam) Ročník 594; s. 127800
Hlavní autoři:	Cheng, Li-Chen, Sun, Jian-Shiou
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 14.08.2024
Témata:	Multi agent Portfolio optimization Quantitative trading Reinforcement learning Twin delayed deep deterministic policy Gradient algorithm Portfolio optimization Quantitative trading Twin delayed deep deterministic policy Gradient algorithm Multi agent Reinforcement learning
ISSN:	0925-2312, 1872-8286
On-line přístup:	Získat plný text
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