This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.
created at Oct. 4, 2016, 2:42 p.m.
Common financial technical indicators implemented in Pandas.
created at Sept. 1, 2016, 9:02 p.m.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
created at July 21, 2016, 5:14 a.m.
Performance analysis of predictive (alpha) stock factors
created at June 3, 2016, 9:49 p.m.
Common financial risk and performance metrics. Used by zipline and pyfolio.
created at March 18, 2016, 10:22 a.m.
Node.js native library performing technical analysis over an OHLC dataset with use of genetic algorithm
created at Feb. 28, 2016, 10:16 p.m.
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
created at Sept. 30, 2015, 9:53 a.m.
A Python Pandas implementation of technical analysis indicators
created at July 16, 2015, 5:20 a.m.
Python Backtesting library for trading strategies
created at Jan. 10, 2015, 7:14 a.m.
Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
created at Nov. 28, 2014, 4:20 a.m.
A visual, technical analysis and charting (Candlestick, OHLC, indicators) library built on D3.
created at May 28, 2014, 1:24 p.m.
A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python
created at May 18, 2014, 7:20 p.m.