policy

Ensemble_Stock_Trading_with-DRL_optimized

RonVest92 · PyTorch

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Overview

Name
Ensemble_Stock_Trading_with-DRL_optimized
Author
RonVest92
Framework
PyTorch
License
MIT
Skill type
other
Evidence level
untested
Task description
Deep Reinforcement Learning Ensemble for Automated Stock Trading This project implements an ensemble trading strategy using five DRL agents — PPO, DDPG, TD3, SAC, and A2C — to trade the Dow 30 constituents. The system trains each agent on in-sample data, selects the one with the highest Sharpe ratio

Spaces

Action space
other · 0-dim · 0Hz
Observation space
  • type: other

Links

HuggingFace repo
null
Paper (arXiv)
null

Compatible robots

20

Compatible environments

0

No environments list Ensemble_Stock_Trading_with-DRL_optimized yet.

Datasets that reference this policy

0

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