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An Evolutionary Algorithmic Investigation of US Corporate Payout Policy Determination

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Book cover Natural Computing in Computational Finance

Part of the book series: Studies in Computational Intelligence ((SCI,volume 380))

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Summary

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.

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Agapitos, A., Goyal, A., Muckley, C. (2011). An Evolutionary Algorithmic Investigation of US Corporate Payout Policy Determination. In: Brabazon, A., O’Neill, M., Maringer, D. (eds) Natural Computing in Computational Finance. Studies in Computational Intelligence, vol 380. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23336-4_7

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  • DOI: https://doi.org/10.1007/978-3-642-23336-4_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23335-7

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