Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.

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

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

Statistical and Algorithmic Investing Strategies for Everyone

The Operator Splitting QP Solver

Machine Learning in Asset Management (by @firmai)

Python library for portfolio optimization built on top of scikit-learn

Portfolio optimization and back-testing.

An Open Source Portfolio Backtesting Engine for Everyone | 面向所有人的开源投资组合回测引擎

Research in investment finance with Python Notebooks

Portfolio optimization with deep learning.

Helps you with managing your investments

The Open-Source Backtesting Engine/ Trading Simulator by Bertram Solutions.

Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets

An open source library for portfolio optimisation

📈This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com

Fast and scalable construction of risk parity portfolios

Entropy Pooling views and stress-testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.

Investment portfolio and stocks analyzing tools for Python with free historical data