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Uncovering Financial Constraints

Published online by Cambridge University Press:  05 May 2023

Matthew Linn  and
Daniel Weagley
Matthew Linn*
Affiliation:
University of Massachusetts Amherst Isenberg School of Management
Daniel Weagley
Affiliation:
Georgia Institute of Technology Scheller College of Business daniel.weagley@scheller.gatech.edu
*
mlinn@isenberg.umass.edu (corresponding author)
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Abstract

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We use a random forest model to classify firms’ financial constraints using only financial variables. Our methodology expands the range of classified firms compared to text-based measures while maintaining similar levels of informativeness. We construct two versions of our constraint measures, one using many firm characteristics and the other using a small set of more primitive characteristics. Using our measures, we find that institutional investors hold a lower percentage of shares in equity-focused constrained firms, while retail investors show a preference for them. Equity issuance and investment of constrained firms also increases during periods of high investor sentiment.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , First View , pp. 1 - 36
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We thank Jarrad Harford (the editor) and Gerard Hoberg (the referee) for constructive comments in the review process. We are grateful to Taylor Begley, Donald Bowen, András Danis, Joan Farra-Mensa, Anisha Ghosh (discussant), Sudip Gupta (discussant), Charles Hadlock (discussant), Armen Hovakimian (discussant), Alex Hsu, Russell Jame, Nikunj Kapadia, Soohun Kim, Bradley Paye, Manpreet Singh, Jason Sockin (discussant), Huan Yang, and seminar and conference participants at Georgia Tech, University of Massachusetts, Virginia Tech, the 2018 Northern Finance Association Conference, the 2019 Dolomites Winter Finance Conference, the 2019 Financial Management Association Conference, the 2020 Midwest Finance Association Conference, and the 2022 University of Florida Research Conference on Machine Learning in Finance for helpful comments on the article. Any remaining errors are our own. Some of the ideas in this article were spun out of a previous working article entitled “Seeing the Forest Through The Trees: Do Investors Underreact to Systemic Events?” This article was briefly circulated under the title “Estimating Financial Constraints with Machine Learning.”

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