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An evolutionary algorithmic investigation of US corporate payout policy determination
Author(s)
Date Issued
2011
Date Available
2012-04-03T11:53:46Z
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.
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.
Sponsorship
Science Foundation Ireland
Type of Material
Book Chapter
Publisher
Springer
Copyright (Published Version)
2011 Springer Verlag Berlin Heidelberg
Subject – LCSH
Evolutionary computation
Dividends--United States
Stock repurchasing
Regression analysis
Web versions
Language
English
Status of Item
Peer reviewed
Journal
Brabazon, A., O’Neill, M., Maringer, D. (eds.). Natural Computing in Computational Finance (Volume IV)
ISBN
978-3-642-23335-7
This item is made available under a Creative Commons License
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gp_bookchapter.pdf
Size
3.35 MB
Format
Adobe PDF
Checksum (MD5)
9d11dce80daafabbd2c6f6ebc9cd247d
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