FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
- deep-reinforcement-learning
- stock-trading
- a2c-algorithm
- ppo
Repository Index
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A Java library for technical analysis.
Python trading framework with AI agents that actually place the trade. Backtest, paper and live trade on 12 brokers: stocks, options, futures, forex, crypto and prediction markets.
High-performance technical analysis indicators and backtesting framework in Go. Zero dependencies. ✨ See how! 👀
- indicators
- technical-analysis
- stock-analysis
- stock-market
TranslatedA-share market analysis and AI intelligent investment research agent: a desktop workbench for stock analysis, quantitative trading analysis, and post-market review — easy stock
Python module to get stock data from Yahoo! Finance
- python
- yahoo-finance-api
- finance
Strategies to Gekko trading bot with backtests results and some useful tools.
- gekko
- strategies
- gekko-strategies
- gekko-backtest
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
- reinforcement-learning
- supervised-learning
- stock-data
- trading
Portfolio optimization with deep learning.
- deep-learning
- portfolio-optimization
- finance
- machine-learning
Technical Analysis Library for Golang
- technical-analysis
- golang
- go
- stock
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
Trady is a handy library for computing technical indicators, and it targets to be an automated trading system that provides stock data feeding, indicator computing, strategy building and automatic trading. It is built based on .NET Standard 2.0.
- strategy
- technical
- analysis
- stock
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
TranslatedMulti-market intelligent quantitative workbench (A-shares/Hong Kong stocks/US stocks) — secondary development based on shy3130/tickflow-stock-panel, adding multi-market support for Hong Kong and US stocks. Self-hosted stock screening + monitoring + backtesting. MIT.
- a-shares
- backtesting
- fastapi
- hongkong-stocks
Analyze the Indonesian stock market (IDX/IHSG) from web terminal, CLI, or any AI agents via MCP server. IHSG Prices, Fundamentals, and Screening. Free and No API keys required.
Do stock correlations predict the market? 66 pre-registered tests, the data, and a triple pendulum that explains why not. If you have an idea you want me to try, submit it as a PR and I will test it and get back to you.
WebApp Quandl.com API to tell stock growth history in a given period.
- stocks
- quandl
- webapp
- stock-growth-history
A Node.js CLI for displaying stock exchange quotes
Simple Elixir wrapper for the Stockfighter API
Financial Market Intelligence MCP Server — stock quotes, technical analysis, crypto data, and portfolio insights for AI agents
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.