An Evolutionary Algorithmic Investigation of US Corporate Payout Policy
Created by W.Langdon from
gp-bibliography.bib Revision:1.8178
- @InCollection{Agapitos:NCFE:2011,
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author = "Alexandros Agapitos and Abhinav Goyal and
Cal Muckley",
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title = "An Evolutionary Algorithmic Investigation of {US}
Corporate Payout Policy",
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booktitle = "Natural Computing in Computational Finance (Volume
4)",
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publisher = "Springer",
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year = "2012",
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editor = "Anthony Brabazon and Michael O'Neill and
Dietmar Maringer",
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volume = "380",
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series = "Studies in Computational Intelligence",
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chapter = "7",
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pages = "123--139",
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keywords = "genetic algorithms, genetic programming, US Corporate
Payout Policy, Symbolic Regression",
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isbn13 = "978-3-642-23335-7",
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URL = "http://hdl.handle.net/10197/3552",
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URL = "https://researchrepository.ucd.ie/bitstream/10197/3552/1/gp_bookchapter.pdf",
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URL = "http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-642-23335-7",
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DOI = "doi:10.1007/978-3-642-23336-4_7",
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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.",
- }
Genetic Programming entries for
Alexandros Agapitos
Abhinav Goyal
Cal Muckley
Citations