swyang50066/rl-stock-trading
WATERMELON: Multi-Agent Reinforcement Learning Based Algorithmic Stock Trading System with GUI Application
WATERMELON helps quantitative traders and financial analysts develop and test automated stock trading strategies. It takes historical stock market data and a chosen reinforcement learning algorithm to simulate trading performance, outputting insights on strategy effectiveness. This tool is designed for anyone managing investment portfolios who wants to automate and optimize their trading decisions.
No commits in the last 6 months.
Use this if you are a quant trader or analyst looking to design and evaluate automated stock trading systems using advanced machine learning techniques.
Not ideal if you are looking for a ready-to-use trading bot without needing to understand or configure the underlying algorithmic strategies.
Stars
18
Forks
8
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 08, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/swyang50066/rl-stock-trading"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
quantylab/rltrader
파이썬과 케라스를 이용한 딥러닝/강화학습 주식투자 - 퀀트 투자, 알고리즘 트레이딩을 위한 최첨단 해법 입문 (개정판)
matlab-deep-learning/reinforcement_learning_financial_trading
MATLAB example on how to use Reinforcement Learning for developing a financial trading model
erhardtconsulting/tensortrade-ng
TensorTrade-NG is an open source Python framework for building, training, evaluating, and...
TradeMaster-NTU/TradeMaster
TradeMaster is an open-source platform for quantitative trading empowered by reinforcement...
LeonardoBerti00/DeepMarket
DeepMarket is a framework for performing Limit Order Book simulation with Deep Learning. This is...