Echo-GYX

Echo-GYX's Stars

• theanh97/Deep-Reinforcement-Learning-with-Stock-Trading

  This project uses Deep Reinforcement Learning (DRL) to develop and evaluate stock trading strategies. By implementing agents like PPO, A2C, DDPG, SAC, and TD3 in a realistic trading environment with transaction costs, it aims to optimize trading decisions based on return, volatility, and Sharpe ratio.

  Language:Jupyter Notebook4622

• ThibautTheate/An-Application-of-Deep-Reinforcement-Learning-to-Algorithmic-Trading

  Experimental code supporting the results presented in the scientific research paper entitled "An Application of Deep Reinforcement Learning to Algorithmic Trading"

  Language:Python17991

• abhinavkolli03/StockBot-Research

  ARIMA-LSTM hybrid model testing on stock model prediction and DQN Learning Agent trial

  Language:Jupyter Notebook3

• Joeyipp/rl-stock-trading

  Stock Trading with Reinforcement Learning (DQN & DDPG)

  Language:Python73

• somsagar07/RL-stock-trading-

  RL algorithm for stock trading with multiple reward functions

  Language:Python73

• nandahkrishna/StockTrading

  Stock Trading using Reinforcement Learning

  Language:Jupyter Notebook97

• DemaciaLarz/TDQN-in-keras

  Applying the Trading Deep Q-Network algorithm (TDQN) on shares in the hydrogen sector.

  Language:Jupyter Notebook122

• MehranTaghian/DQN-Trading

  A Deep Reinforcement Learning Framework for Stock Market Trading

  Language:Python15152

• evgps/a3c_trading

  Trading with recurrent actor-critic reinforcement learning

  Language:Jupyter Notebook425126

• conditionWang/DRQN_Stock_Trading

  This is the code implementation of the paper "Financial Trading as a Game: A Deep Reinforcement Learning Approach".

  Language:Python8025

• thuml/Time-Series-Library

  A Library for Advanced Deep Time Series Models.

  Language:Python7.4k1.2k

• HjzQAQ/FTGP23_Group5_05

  Language:JavaScript4