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Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
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.
Portfolio optimization with deep learning.
Research in investment finance with Python Notebooks
An Open Source Portfolio Backtesting Engine for Everyone | 面向所有人的开源投资组合回测引擎
Helps you with managing your investments
The Open-Source Backtesting Engine/ Trading Simulator by Bertram Enterprises.
Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets
Quantitative Investment Strategies (QIS) package implements Python analytics for visualisation of financial data, performance reporting, analysis of quantitative strategies.
📈This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com
An open source library for portfolio optimisation
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.