Common financial risk and performance metrics. Used by zipline and pyfolio.
created at March 18, 2016, 10:22 a.m.
This trading-gym is the first trading for agent to train with episode of short term trading itself.
created at June 3, 2018, 7:12 a.m.
Trading Environment(OpenAI Gym) + DDQN (Keras-RL)
created at Aug. 24, 2018, 7:19 a.m.
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
created at Sept. 30, 2015, 9:53 a.m.
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.
created at Feb. 23, 2019, 12:01 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.
Building a population of models that trade crypto and mutate iteratively
created at June 10, 2018, 2:55 a.m.
Bitcoin - MACD Crossover Trading Strategy Backtest
created at Sept. 10, 2017, 6:35 p.m.
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.
This is the code for "Bitcoin Prediction" by Siraj Raval on Youtube
created at Feb. 1, 2018, 10:02 a.m.
【停止维护】新版本更新已迁移到 IBATS 项目组对应名称项目中。连接火币交易所，获取火币实时行情、火币历史行情，保存到mysql数据库同时redis广播，供 ABAT 交易平台进行策略回测、分析，交易使用
created at June 21, 2018, 1:39 a.m.
High-performance TensorFlow library for quantitative finance.
created at July 24, 2019, 4:09 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.
A dumping ground for my files I use with this awesome crypto currency trading platform https://github.com/askmike/gekko
created at May 31, 2017, 8:08 p.m.
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot
created at April 8, 2018, 2:06 p.m.