Open Source Fundamental Industry Classification
Zura Kakushadze, Willie Yu
TL;DR
This paper offers open source tools for constructing a fundamental industry classification and evaluates its effectiveness in short-term trading strategies using open source risk models.
Contribution
It provides a comprehensive, open source implementation of industry classification based on public data and compares its performance in trading signal generation.
Findings
The open source classification performs competitively in trading simulations.
The source code is modular and easily adaptable for different data sources.
The approach facilitates transparent and reproducible industry classification analysis.
Abstract
We provide complete source code for building a fundamental industry classification based on publically available and freely downloadable data. We compare various fundamental industry classifications by running a horserace of short-horizon trading signals (alphas) utilizing open source heterotic risk models (https://ssrn.com/abstract=2600798) built using such industry classifications. Our source code includes various stand-alone and portable modules, e.g., for downloading/parsing web data, etc.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.