Case Study: a US-based quantitative hedge fund boosts alpha generation with Numerix's Python-based derivatives pricers

US-based Quantitative Hedge Fund speeds alpha generation with NumeriX

A US-based quantitative hedge fund needed to perform high-frequency backtesting of its credit derivatives strategies but required a robust, production-ready solution beyond open-source options. They sought a Python-integrated pricing library that was fast, reliable, and well-supported. The vendor, Numerix, provided its FINCAD derivatives pricing library and Python SDK to meet this challenge.

The solution from Numerix included the FINCAD library combined with a user-friendly Python SDK, which allowed for seamless integration into the fund's existing workflows and data sets. By using Numerix's tools for prototyping and then scaling their backtests, the client was able to rapidly validate and deploy trading strategies. This increased their alpha generation and allowed team members to focus on higher-value analytical work.