A NEURAL NETWORK OF DIVIDEND PAYOUT RATIO DETERMINANTS

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MORADZADEH FARD MAHDI; ATTARY MOTLAGH PARISA

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Journal: The Financial Accounting and Auditing Researches Year:2013 | Volume:5 | Issue:17 Page(s): 91-130

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Information Journal Paper

Title

A NEURAL NETWORK OF DIVIDEND PAYOUT RATIO DETERMINANTS

Author(s)

MORADZADEH FARD MAHDI | ATTARY MOTLAGH PARISA | Issue Writer Certificate

Keywords

EARNING PER SHAREQ2

DIVIDEND PER SHAREQ2

DIVIDEND PAYOUT RATIOQ2

NEURAL NETWORKQ2

Abstract

This research analyzes the determinants of DIVIDEND PAYOUT RATIO, using a sample of Tehran Stock Exchange companies and it also compares the predictive power of NEURAL NETWORKs and regression model to estimate DIVIDEND PAYOUT RATIO. The purpose of this research is identification and explanation of the determinants of DIVIDEND PAYOUT RATIO, evaluation of the importance of these determinants, and presentation of a descriptive model of DIVIDEND PAYOUT RATIO determinants. Among the different theories and ideas from researchers in the field of finance about dividend, in this study, signaling theory, agency theory and residual theory of dividend have been studied. In order to review the theories, first substituting variables were determined and then the necessary information for 133 companies was gathered during six years (83-88). The information was analyzed via statistical methods based on correlation coefficient, multivariate regression, and artificial NEURAL NETWORKs. The results of this research indicate the existence of a significant and positive relationship between DIVIDEND PAYOUT RATIO and “last year DIVIDEND PAYOUT RATIO, ownership dispersion and free cash flow (FCF)”. A comparison between regression and NEURAL NETWORK models indicating more accurate prediction of DIVIDEND PAYOUT RATIO using NEURAL NETWORK model. Also in structure (7-13-1) of NEURAL NETWORK, a model with “learning initial=0.15 and momentum=0.9” shows that revenue growth, last year DIVIDEND PAYOUT RATIO, and ownership dispersion are the most important determinants of DIVIDEND PAYOUT RATIO.

Cites

FACTORS AFFECTING DIVIDEND PAYOUT RATIO AND COMPARING FORECAST ACCURACY OF DIVIDEND PAYOUT RATIO USING REGRESSION MODEL AND NEURAL NETWORK IN IRAN OVER-THE-COUNTER (OTC) MARKET

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APA: Copy

MORADZADEH FARD, MAHDI, & ATTARY MOTLAGH, PARISA. (2013). A NEURAL NETWORK OF DIVIDEND PAYOUT RATIO DETERMINANTS. THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES, 5(17), 91-130. SID. https://sid.ir/paper/198086/en

Vancouver: Copy

MORADZADEH FARD MAHDI, ATTARY MOTLAGH PARISA. A NEURAL NETWORK OF DIVIDEND PAYOUT RATIO DETERMINANTS. THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES[Internet]. 2013;5(17):91-130. Available from: https://sid.ir/paper/198086/en

IEEE: Copy

MAHDI MORADZADEH FARD, and PARISA ATTARY MOTLAGH, “A NEURAL NETWORK OF DIVIDEND PAYOUT RATIO DETERMINANTS,” THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES, vol. 5, no. 17, pp. 91–130, 2013, [Online]. Available: https://sid.ir/paper/198086/en

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