awesome-quant is a curated list (“awesome list”) of libraries, packages, articles, and resources for quantitative finance (“quants”). It includes tools, frameworks, research papers, blogs, datasets, etc. It aims to help people working in algorithmic trading, quant investing, financial engineering, etc., find useful open source or educational resources. Licensed under typical “awesome” list standards.
Features
- Collections of quant-finance libraries & packages across multiple languages (Python, R, C++, etc.)
- Links to datasets and data sources for financial / market data
- Resources for research, articles, blogs, educational content in quant finance
- Frameworks/platforms, backtesting tools, risk management, portfolio optimization tools included
- Curated; quality filtered; community contributions via pull requests are accepted
- Tagged / organized by topic: algorithmic trading, time series, data visualization etc.
Categories
Algorithmic TradingFollow Awesome-Quant
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