awesome-ai-in-finance

Why we included this project

Before you commit to a stack for anything quantitative, this list is a fast way to map the field. It pulls together agents, papers, data sources, exchange APIs, and ready-made strategies into one place, so you can see which frameworks are mature and which research is still promising in a single pass. The sections are organized by use case, with market data, trading execution, portfolio management, and high-frequency trading each getting their own space, which makes it practical for scoping a project rather than just browsing. It is a reference and discovery resource, not software you run, but for teams evaluating options it saves hours of scattered searching.