jialuechen/torchquant

PyTorch for Quantitative Finance : Refine Derivatives Hedging and Pricing with Architecture Alightment in Operators

49
/ 100
Emerging

This tool helps quantitative finance professionals, such as derivatives traders, risk managers, and quantitative analysts, price and manage complex financial derivatives more accurately and efficiently. You provide details about various exotic options and other instruments, and it uses advanced deep learning techniques to calculate their fair value and associated risks, even for highly complex, path-dependent structures.

195 stars.

Use this if you need to precisely price and hedge a wide range of derivatives, from standard European options to highly exotic instruments like Everest or Himalaya options, and you want to leverage GPU acceleration for faster computations.

Not ideal if you are looking for a simple spreadsheet-based solution or do not work with complex, differentiable financial models.

derivatives-pricing quantitative-finance risk-management stochastic-modeling financial-engineering
No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 17 / 25

How are scores calculated?

Stars

195

Forks

28

Language

Python

License

Apache-2.0

Last pushed

Dec 16, 2025

Commits (30d)

0

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