[June 5, 2020] How could the stock market recover in 76 days?
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Updated
Jun 10, 2020 - R
[June 5, 2020] How could the stock market recover in 76 days?
This is the repository of Machine Learning Internship I have done with CareerLauncher endorsed by AICTE and Intel Partnership
reinforcement learning project for stock trading
QUANTARMY quantstack | One-click quantitative envoirment based in docker, debian, conda, jupyterlabs,zipline-reloaded and arcticdb
Algorithm Trading in Stock Market
A event can take multiple forms. The objective of this repository is to detect an event when it happens.
Deep-learning based trade bot based on Binance API to boost your net worth.
Binance Trading Bot - Buy & sell just due to changes of RSI indicator in different timeframes.
Artificial Intelligence for Trading
This project is part of a bigger one. I want to make Algo Trading Easy for you! You can find examples and more information in the documentation. easyT, easyTo trade, easyTo use!
This package offers both traditional benchmark and newly developed Online Portfolio Selection (OPS) algorithms implementation.
This project aims to select a supervised algorithm that can predict stock prices basing on historical data and use the predictor generated to form trading strategies.
Python Rebalancer
sharpe is a unified, interactive, general-purpose environment for backtesting or applying machine learning(supervised learning and reinforcement learning) in the context of quantitative trading
algo trading backtesting on BitMEX
It's a game to get money
Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierarchical reinforcement learning. It includes the code for the proposed method and experimental results on real-world stock data to demonstrate its effectiveness.
A Rust high performance cryptocurrency trading API with support for multiple exchanges and language wrappers.
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