Factor Engine: A Python Library for Systematic Financial Factor Computation and Analysis

TL;DR

Factor Engine is an open-source Python library that simplifies the computation and analysis of financial factors, enabling integration with data science tools and supporting machine learning applications in finance.

Contribution

It introduces a modular, extensible API for defining custom financial factors and demonstrates its effectiveness through comparison with existing tools and practical machine learning applications.

Findings

High similarity between Factor Engine and Stata in factor computation

Comparable performance in backtesting analyses

Successful application in machine learning workflows

Abstract

Factor Engine is a high-performance, open-source Python library designed for the systematic computation and analysis of financial factors. Built around a modular and extensible API that leverages Python decorators, Factor Engine enables users to define custom factors with ease and integrates seamlessly with the modern data science ecosystem. To assess its practical effectiveness, we compare the mispricing factors computed by Factor Engine to those generated using a reference Stata implementation, finding that both approaches yield highly similar results and comparable performance in backtesting analyses. Furthermore, we experimentally apply these factors within machine learning workflows for trading strategy development, illustrating their practical utility and potential for quantitative finance research.