low-cost, high-efficiency, easy-to-implement

OpenFE: automated feature generation with expert-level performance

A game theoretic approach to explain the output of any machine learning model.

Package based on the work of Dr Marcos Lopez de Prado regarding his research with respect to Advances in Financial Machine Learning

Collection of algorithms for online portfolio selection

让免费版ccxt也能使用ws功能，在ccxtws的基础上做了简单的修改

Python implementation of L1 trend filtering algorithm

Open source software that helps you create and deploy high-frequency crypto trading bots

Optimal control of risk aversion in Avellaneda Stoikov high frequency market making model with Soft Actor Critic reinforcement learning

📈 如何用深度强化学习自动炒股

A custom OpenAI gym environment for simulating stock trades on historical price data.

Common financial risk and performance metrics. Used by zipline and pyfolio.

Awesome machine learning for trading

Python code for High-frequency trading in a limit order book by Marco Avellaneda and Sasha Stoikov

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

A collection of homeworks of market microstructure models.

FinRL: Financial Reinforcement Learning. 🔥

A cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym

An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.

OpenAI Gym Environment API based Bitcoin trading environment

A genetic programming algorithm used for generating alpha factors in the multi-factor investment strategy

Market Making via Reinforcement Learning

Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.

Machine Learning in Asset Management (by @firmai)

Notebook for <Advances in Financial Machine Learning> using Python 3.7

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

Advances in Financial Machine Learning

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]