A Python Pandas implementation of technical analysis indicators
created at July 16, 2015, 5:20 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.
Batch backtest, import and strategy params optimalization for Gekko Trading Bot. With one command you will run any number of backtests.
created at Feb. 25, 2018, 9:49 p.m.
Analysis of High Frequency Trading on Bitcoin exchanges
created at July 27, 2017, 7:11 a.m.
My algorithmic trading strategies with the Gekko cryptocurrency trading bot.
created at June 23, 2018, 4:08 a.m.
Gekko Trading Bot dataset dumps. Ready to use and download history files in SQLite format.
created at April 4, 2018, 10 p.m.
Strategies to Gekko trading bot with backtests results and some useful tools.
created at Feb. 11, 2018, 9:10 p.m.
💸 Papers and Code Implements for Quantitative-Trading
created at May 6, 2018, 7:21 a.m.
Genetic Algorithm for solving optimization of trading strategies using Gekko
created at Nov. 8, 2017, 2:45 a.m.
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
created at May 1, 2017, 1:53 p.m.