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The Puzzle of Frequent and Large Issues of Debt and Equity

Published online by Cambridge University Press:  07 September 2021

Rongbing Huang Open the ORCID record for Rongbing Huang [Opens in a new window]  and
Jay R. Ritter Open the ORCID record for Jay R. Ritter [Opens in a new window]
Rongbing Huang
Affiliation:
Kennesaw State University Coles College of [email protected]
Jay R. Ritter*
Affiliation:
University of Florida Warrington College of Business Administration
*
[email protected] (corresponding author)
Rights & Permissions [Opens in a new window]

Abstract

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More frequent, larger, and more recent debt and equity issues in the prior 3 fiscal years are followed by lower stock returns in the subsequent year. The intercept of a q-factor calendar-time regression for the value-weighted (VW) portfolio of firms with at least 3 large issues is −0.63% per month (t-stat. = −4.31). Purging the factor returns of recent issuers increases the magnitude of the estimated underperformance following frequent equity issues. A VW Fama–MacBeth regression shows that firms with 3 equity issues underperform nonissuers by 0.65% per month (t-stat. = −2.65). Earnings announcement returns are low following frequent issues, especially equity issues.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 57 , Issue 1 , February 2022 , pp. 170 - 206
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 (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We thank an anonymous referee, Mark Flannery, Jon Garfinkel, Jason Karceski, Paul Malatesta (the editor), Feng Zhang, and Clara Qing Zhou, and the participants in seminars at Kennesaw State University, the University of Calgary, York University, and the 2016 FMA Annual Meeting and the 2017 FMA Asia/Pacific Conference for comments, Kenneth French for making the Fama–French factor returns available, and Lu Zhang for sharing the q-factor returns.

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