paperswithbacktest/awesome-systematic-trading

This repository is not a piece of software you install and run. It is a curated list, a big organized bookmark page, pointing to other people's libraries, papers, books, videos, blogs, and courses about systematic (also called quantitative or algorithmic) trading. Systematic trading means using rules and code, instead of gut feeling, to decide when to buy or sell financial assets like stocks, bonds, currencies, or crypto. Inside the README you will find sections for backtesting and live trading frameworks (tools that let you test a trading idea on historical data before risking real money), trading bots, analytics tools for indicators and risk, broker APIs for connecting to real exchanges, data sources, databases, and machine learning and time series libraries. It lists 97 libraries and packages in total, over 40 trading strategies described by academics and institutions, 55 books ranging from beginner to professional level, more than 20 videos and interviews, plus assorted blogs and courses. Each library entry names the project, gives a short description, shows its GitHub star count, and notes the programming language it is written in, mostly Python, with some C++ and other languages mixed in. This is useful if you are trying to learn about trading strategy development and want a map of what already exists, rather than starting from a blank search engine. A vibe coder or beginner could use it to find a beginner friendly Python backtesting library, then read a linked book to understand the strategy behind it. The project also points to a companion website, paperswithbacktest.com, for a deeper collection of Python trading strategy implementations. Because this is a list rather than a working application, there is nothing here to install or run directly. Its value is as a starting reference point before you pick one of the linked tools. The full README is longer than what was shown.