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

H.A. Abdou, J. Pointon, A. El-Masry, M. Olugbode, R.J. Lister

Research output: Contribution to journalArticle

6 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)796-813
Number of pages18
JournalJournal of International Financial Markets, Institutions and Money
Volume22
Issue number4
Early online date1 May 2012
DOIs
Publication statusPublished - Oct 2012
Externally publishedYes

Fingerprint

Dividend policy
Share prices
Network analysis
Neural networks
Canada
Growth opportunities
Confidence
Dividends
Dividend yield
Pecking order theory
Book value

Keywords

  • Dividend yield
  • Retention
  • Market-to-book value
  • Neural networks
  • Transportation

Cite this

A variable impact neural network analysis of dividend policies and share prices of transportation and related companies. / Abdou, H.A.; Pointon, J.; El-Masry, A.; Olugbode, M.; Lister, R.J.

In: Journal of International Financial Markets, Institutions and Money, Vol. 22, No. 4, 10.2012, p. 796-813.

Research output: Contribution to journalArticle

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