staskh/awesome-math-and-trading
Curated list of mathematics, probability, ML, and quantitative trading resources for quants and algorithmic traders.
Why it is useful
awesome-math-and-trading is a recent open-source project in Education. It is included because it has recent repository activity and can support mathematical learning, research, modelling, software development, or AI workflows.
Repository at a glance
- Owner: staskh
- Primary language: Not specified
- Latest update: 2026-09-22
- Stars / forks: 21 / 4
- License: MIT
- Links: No separate project site was listed.
Good starting points
- Read the project README and installation instructions.
- Try the smallest example before changing parameters or datasets.
- Check tests, issues, and release notes before relying on results in teaching or research.
- Cite the repository and its license when reusing code or figures.
README snapshot
A curated list of high-quality resources on mathematics, statistics, machine learning, and quantitative trading. Designed for: - 🤖 ML practitioners in finance - 🎓 Students preparing for quant interviews - 📊 Quant traders - 📈 Systematic/algorithmic traders This list focuses on the mathematical and quantitative foundations of trading — from probability theory and stochastic calculus to practical algorithmic trading resources. All links are carefully selected for depth and long-term usefulness. - BOOKS — Books on ML, deep learning, financial mathematics, and options. - LECTURES — Lectures, keynotes, and long-form t