yuriak / Rlquant
Applying Reinforcement Learning in Quantitative Trading
Stars: ✭ 271
Projects that are alternatives of or similar to Rlquant
A3c trading
Trading with recurrent actor-critic reinforcement learning
Stars: ✭ 305 (+12.55%)
Mutual labels: jupyter-notebook, trading, reinforcement-learning
Multihopkg
Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout
Stars: ✭ 202 (-25.46%)
Mutual labels: jupyter-notebook, reinforcement-learning
Alpha Zero General
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Stars: ✭ 2,617 (+865.68%)
Mutual labels: jupyter-notebook, reinforcement-learning
Icychesszero
中国象棋alpha zero程序
Stars: ✭ 206 (-23.99%)
Mutual labels: jupyter-notebook, reinforcement-learning
Popular Rl Algorithms
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
Stars: ✭ 266 (-1.85%)
Mutual labels: jupyter-notebook, reinforcement-learning
Deeprl Agents
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
Stars: ✭ 2,149 (+692.99%)
Mutual labels: jupyter-notebook, reinforcement-learning
Rad
RAD: Reinforcement Learning with Augmented Data
Stars: ✭ 268 (-1.11%)
Mutual labels: jupyter-notebook, reinforcement-learning
Pytorch sac
PyTorch implementation of Soft Actor-Critic (SAC)
Stars: ✭ 174 (-35.79%)
Mutual labels: jupyter-notebook, reinforcement-learning
Applied Reinforcement Learning
Reinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks
Stars: ✭ 229 (-15.5%)
Mutual labels: jupyter-notebook, reinforcement-learning
Nn
🧑🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Stars: ✭ 5,720 (+2010.7%)
Mutual labels: jupyter-notebook, reinforcement-learning
Rl learn
我的强化学习笔记和学习材料📖 still updating ... ...
Stars: ✭ 234 (-13.65%)
Mutual labels: jupyter-notebook, reinforcement-learning
Andrew Ng Notes
This is Andrew NG Coursera Handwritten Notes.
Stars: ✭ 180 (-33.58%)
Mutual labels: jupyter-notebook, reinforcement-learning
Deep Algotrading
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
Stars: ✭ 173 (-36.16%)
Mutual labels: jupyter-notebook, reinforcement-learning
Release
Deep Reinforcement Learning for de-novo Drug Design
Stars: ✭ 201 (-25.83%)
Mutual labels: jupyter-notebook, reinforcement-learning
Machine Learning And Reinforcement Learning In Finance
Machine Learning and Reinforcement Learning in Finance New York University Tandon School of Engineering
Stars: ✭ 173 (-36.16%)
Mutual labels: jupyter-notebook, reinforcement-learning
Rl Tutorial Jnrr19
Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019
Stars: ✭ 204 (-24.72%)
Mutual labels: jupyter-notebook, reinforcement-learning
Drq
DrQ: Data regularized Q
Stars: ✭ 268 (-1.11%)
Mutual labels: jupyter-notebook, reinforcement-learning
2048 Deep Reinforcement Learning
Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning
Stars: ✭ 169 (-37.64%)
Mutual labels: jupyter-notebook, reinforcement-learning
Machine Learning Notebooks
Machine Learning notebooks for refreshing concepts.
Stars: ✭ 222 (-18.08%)
Mutual labels: jupyter-notebook, reinforcement-learning
Applying Reinforcement Learning in Quantitative Trading
Overview
This is the repository of my graduate thesis which aims to use reinforcement learning in quantitative trading. Two types of RL models were experimented and could make good performance in the back-test:
- Policy Gradient
- Vanilla Policy Gradient (not implemented in this repo)
- Multi-Task Recurrent Policy Gradient (RPG)
- Direct RL
- Vanilla DRL (DRL)
- A hybrid network involves news embedding vectors (DRL with news)
Experiments
.ipynb files were details of experiments.
This repository contains 3 types of environments:
- CryptoCurrency (Huobi):
env/crc_env.py - End of day US stock prices (quandl):
env/stock_env.py - Continuous Futures (quandl):
env/futures_env.py
And, 2 types of agents:
- DRL:
agents/drl_agent.pyandagents/drl_news_agent.py - RPG:
agents/rpg_agent.pyandagents/rpg_news_agent.py
Also, there are some history codes in history and model_archive which have been deprecated, but contains some early ideas, please feel free to use them.
Reference
[1] Deep Direct Reinforcement Learning for Financial Signal Representation and Trading
[2] Using a Financial Training Criterion Rather than a Prediction Criterion
[3] A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem
[4] Recurrent Reinforcement Learning: A Hybrid Approach
[5] Reinforcement Learning for Trading
[6] Continuous control with deep reinforcement learning
[7] Memory-based control with recurrent neural networks
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].