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

This article aims to study the factors affecting the dividend payout ratio and compare the forecast accuracy of neural network and regression models using the data for the companies listed on Iran OTC market. This article also studies the relationship of last year dividend payout ratio, fixed assets to total assets ratio, current ratio, assets-to-debt ratio, revenue growth, accounting earnings quality ratio, and cash return on assets as independent variables with dividend payout ratio as dependent variable. For hypothesis testing, second-order multiple egression model was employed with a sample size of 50 companies in OTC market during a 5-year period of which their end of fiscal year was from March 20th, 2011 to September 22nd, 2015. The results showed that last year dividend payout ratio, fixed assets to total assets ratio, current ratio, assets-to-debt ratio, and accounting earnings quality ratio have no significant relationship with the dependent variable. Revenue growth and cash return on assets, however, have a positive, significant relationship with dividend payout ratio. Findings also indicate that forecast error of neural network is smaller than that of regression model. Therefore, neural network gives better forecast