JOURNAL ARTICLE

Equity Market Fragmentation and Capital Investment Efficiency.

  • Published In: Management Science (INFORMS), 2024, v. 70, n. 7. P. 4381 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Landsman, Wayne; Pan, Jing; Stubben, Stephen 3 of 3

Abstract

This study investigates how equity market fragmentation—the dispersion of trades across multiple trading venues—affects firms' capital investment decisions by enhancing revelatory price efficiency (RPE), defined as the extent to which stock prices reveal information useful for investment. Using a large U.S. sample from 1995 to 2017, the authors find that greater market fragmentation increases the sensitivity of capital investment to investment opportunities, with a 6.8% rise across the interquartile range of fragmentation. The study provides evidence that this effect operates through two channels: a managerial learning channel, where managers glean more precise information from prices, and a financing channel, where public creditors better assess firms' investment prospects, alleviating financing constraints—particularly for firms relying on public rather than private debt. Additional analyses show that market fragmentation is associated with increased investor information acquisition, more informed trading, and stock prices that more fully incorporate future earnings, supporting the conclusion that fragmentation improves price informativeness and thereby influences real corporate investment decisions.

Additional Information

  • Source:Management Science (INFORMS). 2024/07, Vol. 70, Issue 7, p4381
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2024
  • ISSN:0025-1909
  • DOI:10.1287/mnsc.2023.4905
  • Accession Number:178319268
  • Copyright Statement:Copyright of Management Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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