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Judge Ideology and Opportunistic Insider Trading
Published online by Cambridge University Press: 29 February 2024
Abstract
Although federal judges are the ultimate arbiters of insider trading enforcement, the role of their political ideology in insider trading is unclear. Using the partisanship of judges’ nominating presidents to measure judge ideology, we first document that liberal judges are associated with heavier penalties in insider trading lawsuits than conservative judges. Next, we find that firms located in circuits with more liberal judges have fewer opportunistic insider sales. Cross-sectional analyses show that this deterrent effect is stronger when managers face a higher risk of insider trading lawsuits. Finally, we find that the Securities and Exchange Commission considers judges’ ideology when selecting litigation forums.
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- Research Article
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- Creative Commons
- 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), 2024. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington
Footnotes
We thank an anonymous reviewer and Mara Faccio (the editor) for constructive suggestions that helped to improve the article. For valuable comments, we also thank Ferhat Akbas (discussant), Giulio Anselmi (discussant), Utpal Bhattacharya, Jonas Heese (discussant), Lorraine Lee (discussant), Luca Lin (discussant), Joe López-Vilaró (discussant), Paul Richardson (discussant), Haoyang Xiong (discussant), participants at the 2021 AAA Annual Meeting, 2021 EFMA Annual Conference, 2021 EFA Conference, 2021 MFA Conference, 2021 MIT Asia Accounting Conference, 2021 Paris December Finance Meeting, 2022 Hawaii Accounting Research Conference, 2023 FARS Midyear Meeting, and seminar participants at the Hong Kong University of Science and Technology and University of Hong Kong. All errors are our own.
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