Zipline, a Pythonic Algorithmic Trading Library
created at Oct. 19, 2012, 3:50 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.
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.
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
created at Dec. 18, 2017, 10:49 a.m.
Github.com/CryptoSignal - Trading & Technical Analysis Bot - 4,100+ stars, 1,100+ forks
created at Sept. 16, 2017, 11:49 p.m.
Visualizer for neural network, deep learning and machine learning models
created at Dec. 26, 2010, 12:53 p.m.
A stock trading bot powered by Trump tweets
created at Jan. 22, 2017, 3:54 a.m.
Bitcoin arbitrage - opportunity detector
created at Jan. 31, 2013, 11:43 a.m.
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
created at Jan. 9, 2019, 8:02 a.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.
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
created at July 30, 2019, 9:28 p.m.