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dx
Python library for derivatives analytics and valuation
What it is
A Python library for financial and derivatives analytics by Yves Hilpisch, published as DX Analytics. It offers an object-oriented framework for derivatives valuation, risk measurement and portfolio simulation without relying on commercial libraries. Developers, researchers and quant practitioners who want to build pricing and risk models in pure Python are the target users. It is closely tied to the author's books and teaching, so it is more of a learning and prototyping framework than an enterprise risk system.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Strategy research, Data analysis |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Steep learning curve |
| Practical value | Medium 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): +1 over the period, now 768. Gaps mean no snapshot was taken that day.
DX Analytics | Financial and Derivatives Analytics with Python.
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