An evolutionary algorithmic investigation of US corporate payout policy determination

Alexandros Agapitos*, Abhinav Goyal, Cal Muckley

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This Chapter examines cash dividends and share repurchases in the United States during the period 1990 to 2008. In the extant literature a variety of classical statistical methodologies have been adopted, foremost among these is the method of panel regression modelling. Instead, in this Chapter, we have informed our model specifications and our coefficient estimates using a genetic program. Our model captures effects from a wide range of pertinent proxy variables related to the agency cost-based life cycle theory, the signalling theory and the catering theory of corporate payout policy determination. In line with the extant literature, our findings indicate the predominant importance of the agency-cost based life cycle theory. The adopted evolutionary algorithm approach also provides important new insights concerning the influence of firm size, the concentration of firm ownership and cash flow uncertainty with respect to corporate payout policy determination in the United States.

Original languageEnglish
Title of host publicationNatural Computing in Computational Finance
Subtitle of host publicationVolume 4
EditorsAnthony Brabazon, Michael O'Neill, Dietmar Maringer
Pages123-139
Number of pages17
DOIs
Publication statusPublished - 2011

Publication series

NameStudies in Computational Intelligence
Volume380
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

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