[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
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.
QUANTARMY quantstack | One-click quantitative envoirment based in docker, debian, conda, jupyterlabs,zipline-reloaded and arcticdb
Artificial Intelligence for Trading
This package offers both traditional benchmark and newly developed Online Portfolio Selection (OPS) algorithms implementation.
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 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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