A curated list of practical financial machine learning tools and applications.
created at March 21, 2019, 9 p.m.
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
created at Feb. 11, 2023, 8:21 p.m.
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
created at April 3, 2018, 2:08 p.m.
FinRL: Financial Reinforcement Learning. 🔥
created at July 26, 2020, 1:18 p.m.
Performance analysis of predictive (alpha) stock factors
created at June 3, 2016, 9:49 p.m.
High-performance TensorFlow library for quantitative finance.
created at July 24, 2019, 4:09 p.m.
Strategies to Gekko trading bot with backtests results and some useful tools.
created at Feb. 11, 2018, 9:10 p.m.
A visual, technical analysis and charting (Candlestick, OHLC, indicators) library built on D3.
created at May 28, 2014, 1:24 p.m.
A cryptocurrency arbitrage opportunity calculator. Over 800 currencies and 50 markets.
created at July 6, 2017, 9:33 a.m.
Quant/Algorithm trading resources with an emphasis on Machine Learning
created at Nov. 5, 2018, 9:09 p.m.
R2 Bitcoin Arbitrager is an automatic arbitrage trading system powered by Node.js + TypeScript.
created at Oct. 28, 2017, 7:57 a.m.
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
created at Nov. 12, 2017, 4:08 p.m.
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
created at March 10, 2018, 11:22 a.m.
Python module to get stock data from Yahoo! Finance
created at May 2, 2014, 9:12 p.m.
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
created at May 1, 2017, 1:53 p.m.