research-article

Machine learning fund categorizations

Authors:

Jithin PradeepAuthors Info & Claims

ICAIF '20: Proceedings of the First ACM International Conference on AI in Finance

Article No.: 13, Pages 1 - 8

https://doi.org/10.1145/3383455.3422555

Published: 07 October 2021 Publication History

Abstract

Given the surge in popularity of mutual funds (including exchange-traded funds (ETFs)) as a diversified financial investment, a vast variety of mutual funds from various investment management firms and diversification strategies have become available in the market. Identifying similar mutual funds among such a wide landscape of mutual funds has become more important than ever because of many applications ranging from sales and marketing to portfolio replication, portfolio diversification and tax loss harvesting. The current best method is data-vendor provided categorization which usually relies on curation by human experts with the help of available data. In this work, we establish that an industry wide well-regarded categorization system is learnable using machine learning and largely reproducible, and in turn constructing a truly data-driven categorization. We discuss the intellectual challenges in learning this man-made system, our results and their implications.

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Cited By

Martin-Melero IGomez-Martinez RMedrano-Garcia MHernandez-Perlines F(2025)Comparison of sectorial and financial data for ESG scoring of mutual funds with machine learningFinancial Innovation10.1186/s40854-024-00719-y11:1Online publication date: 13-Feb-2025
https://doi.org/10.1186/s40854-024-00719-y
Castellanos NFrank SDesai DPasquali SMehta D(2024)Can an unsupervised clustering algorithm reproduce a categorization system?Proceedings of the 5th ACM International Conference on AI in Finance10.1145/3677052.3698616(213-221)Online publication date: 14-Nov-2024
https://dl.acm.org/doi/10.1145/3677052.3698616
Satone VDesai DMehta DCalinescu ASzpruch L(2021)Fund2VecProceedings of the Second ACM International Conference on AI in Finance10.1145/3490354.3494381(1-8)Online publication date: 3-Nov-2021
https://dl.acm.org/doi/10.1145/3490354.3494381

Index Terms

Machine learning fund categorizations
1. Applied computing
  1. Law, social and behavioral sciences
    1. Economics

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cover image ACM Conferences

ICAIF '20: Proceedings of the First ACM International Conference on AI in Finance

October 2020

422 pages

ISBN:9781450375849

DOI:10.1145/3383455

Conference Chair:
Tucker Balch
J.P. Morgan AI Research

Copyright © 2020 ACM.

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Published: 07 October 2021

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ICAIF '20: ACM International Conference on AI in Finance

October 15 - 16, 2020

New York, New York

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Cited By

Martin-Melero IGomez-Martinez RMedrano-Garcia MHernandez-Perlines F(2025)Comparison of sectorial and financial data for ESG scoring of mutual funds with machine learningFinancial Innovation10.1186/s40854-024-00719-y11:1Online publication date: 13-Feb-2025
https://doi.org/10.1186/s40854-024-00719-y
Castellanos NFrank SDesai DPasquali SMehta D(2024)Can an unsupervised clustering algorithm reproduce a categorization system?Proceedings of the 5th ACM International Conference on AI in Finance10.1145/3677052.3698616(213-221)Online publication date: 14-Nov-2024
https://dl.acm.org/doi/10.1145/3677052.3698616
Satone VDesai DMehta DCalinescu ASzpruch L(2021)Fund2VecProceedings of the Second ACM International Conference on AI in Finance10.1145/3490354.3494381(1-8)Online publication date: 3-Nov-2021
https://dl.acm.org/doi/10.1145/3490354.3494381

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