Empirical Analysis of Automated Stock Trading Using Deep Reinforcement Learning

Empirical Analysis of Automated Stock Trading Using Deep Reinforcement Learning

There are several automated stock trading programs using reinforcement learning, one of which is an ensemble strategy. The main idea of the ensemble strategy is to train DRL agents and make an ensemble with three different actor–critic algorithms: Advantage Actor–Critic (A2C), Deep Deterministic Pol...

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Bibliographic Details
Main Authors: Minseok Kong, Jungmin So
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Applied Sciences
Subjects:
empirical analysis
automated stock trading
deep reinforcement learning
policy gradient method
actor–critic algorithms
ensemble strategy
Online Access:https://www.mdpi.com/2076-3417/13/1/633

Internet

https://www.mdpi.com/2076-3417/13/1/633

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