Unlock best-in-class analytics with Python

One command and three lines of code unlocks the most powerful derivative analytics library in the industry.

FINCAD Python empowers traders, portfolio managers and risk managers alike to easily work within the vast Python ecosystem.

Together, Python’s native data handling and FINCAD’s analytics enable you to compute values, sensitivities and cash flows of a derivative, in just a few lines of code. How is this done? Our FINCAD Python datasheet explains. Results can then be conveniently returned as pandas data structures, making further analysis and aggregation simple and straightforward. 

Learn how one front office team at a total return asset manager is backtesting trading and investment strategies for combined portfolios of cash and derivative instruments using FINCAD Python. 

Total Asset Return Manager - Case Study 


FINCAD Python empowers clients to solve complex derivative analytics challenges with unparalleled simplicity. Deployable on desktop, servers, or the cloud, our Python framework allows for truly lightweight installation. 

With preconfigured modelling and valuation, and straightforward instrument and market data integration, users can get up and running quickly, with utmost confidence in their calculations. 

Datasheet - FINCAD Python


Natively built in Python, this powerful framework provides all the valuable modelling capabilities of FINCAD’s libraries, while also offering integration, configuration and coverage for more advanced use cases. 

Users have the ability to fully configure their modelling and valuation frameworks to fit their specific requirements.  

They can also extend their FINCAD solution via the Python Ecosystem, which offers open source data libraries and package managers that are easy to work with. Not to mention that being able to leverage FINCAD’s best-in-class derivative analytics enables you to understand all the risk in your portfolio.


As a client, you have access to the most thorough product documentation available. This enables you to understand what’s going on under the hood and provides full self-sufficiency when using FINCAD technology. If any questions do arise, you can turn to our expert team of

quantitative developers and analysts who are ready and available to help you navigate any issues and ultimately achieve your goals. In fact, the FINCAD support team can be involved with your solution as little or as much as you need. 

Value Trades with Confidence

FINCAD Python gives you the edge you need to make informed investment decisions with confidence.

Easy to Use
No Black Boxes

Flexible Technology

In addition to Python, FINCAD solutions are also accessible through Java, C++, C# and Microsoft Excel. Learn about our FINCAD Excel and FINCAD SDK solutions. 


Explore Python Resources

FINCAD Python (Extended)
FINCAD Python: Documentation
Python - Improving Data Science in Finance: Video
Case Study
Total Return Asset Manager: Powering Portfolio Strategies with Native Python-based Analytics