A variable impact neural network analysis of dividend
policies and share prices of transportation
and related companies

Abdou, HAH; Pointon, J; El-Masry, A; Olugbode, M; Lister, R

Abstract

The purpose of this research is to investigate dividend policy,including its impact on share prices of transportation providers and related service companies, by comparing generalized regression neural networks with conventional regressions. Our results using regressions reveal that for Europe and for the US and Canada
the market-to-book-value, as a surrogate for growth opportunities,fulfils expectations of pressures on dividends leading to a negative association with dividend yields in accordance with the pecking order theory. Neural network analysis indicates a clear role for growth opportunities for the US and Canada pointing to an underlying confidence on the part of transportation companies in their own internal policies. Finally, risk is rewarded especially in Europe.

Citation

and related companies. Journal of International Financial Markets, Institutions and Money, 22(4), 796-813. https://doi.org/10.1016/j.intfin.2012.04.008

• Journal Article Type: Article
• Publication Date: Oct 1, 2012
• Deposit Date: Mar 5, 2013
• Journal: Journal of International Financial Markets Institutions & Money
• Print ISSN: 1042-4431
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 22
• Issue: 4
• Pages: 796-813
• DOI: https://doi.org/10.1016/j.intfin.2012.04.008
• Publisher URL: http://dx.doi.org/10.1016/j.intfin.2012.04.008
• Related Public URLs: http://www.sciencedirect.com/science/journal/10424431