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Computational-Finance-Course
Course materials for computational finance with Python code
What it is
A collection of course materials for computational finance from Lech Grzelak, including lecture content and code examples. The topics centre on financial modelling and numerical methods, with code that lets you run the techniques discussed in each lecture. Students and self-learners who want a guided route into quantitative modelling are the natural readers. It is a teaching resource, so the examples favour clarity over the robustness you would need in production pricing code.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Beginners |
|---|---|
| Used for | Strategy research, Data analysis |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Easy to start |
| Practical value | Low practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | No commits in over six months |
GitHub stars, last 30 days
Daily snapshots since 2026-09-28 (up to 30 days): +17 over the period, now 934. Gaps mean no snapshot was taken that day.
Materials for the course of Computational Finance.
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