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Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
Translatedstock. Get stock data, calculate stock indicators, chip distribution, identify stock patterns, comprehensive stock selection, stock selection strategies, stock verification and backtesting, automatic stock trading, supports PC and mobile devices.
TranslatedQUANTAXIS: a purely local quantitative solution for stocks/futures/options that supports task scheduling and distributed deployment, covering data/backtesting/simulation/trading/visualization/multiple accounts
Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD
11 Claude skills for day trading: scan thousands of charts, track breaking news, time every entry and exit, and replay every outcome before you risk a dollar.
modular quant framework.
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
Scalable, event-driven, deep-learning-friendly backtesting library
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot