Do reverse stock splits indicate future poor stock performance?

Authors:
Melody Y. Kiang;Peter Ammermann;Dorothy M. Fisher;Steve A. Fisher;Robert T. Chi
Affiliations:
Information Systems Department, College of Business Administration, California State University, Long Beach, United States and School of Management, Harbin Institute of Technology, Heilongjiang, C ...;Department of Finance, College of Business Administration, California State University, Long Beach, United States;Department of Information Systems and Operations Management, College of Business Administration and Public Policy, California State University, Dominguez Hills, United States;Department of Accountancy, College of Business Administration, California State University, Long Beach, United States;Information Systems Department, College of Business Administration, California State University, Long Beach, United States
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Managerial applications of neural networks: the case of bank failure predictions

Management Science

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Abstract

There has been much written on the individual topics of bankruptcy prediction, corporate performance, and forward/reverse stock splits. However, there is little research into the relationship between reverse stock splits and subsequent corporate performance and the potential for bankruptcy. Previous research suggested there is a negative drift in stock prices following reverse splits. The purpose of this study is to provide and empirically support rationales for reverse splits by classifying reverse splitting firms into two groups. The presumed rationales for engaging in reverse splits would differ between the two groups, so do the subsequent stock performance. Our results show that both neural networks and Z-scores can successfully distinguish the two groups of firms while neural networks outperforms Z-scores in finding the firms with best performing stocks.