Dividend Payout Forecast : Multiple Linear Regression vs Genetic Algorithm-Neural Network

Lidya Chitra Laoh

doi:10.31154/cogito.v5i2.210.252-265

Authors

Lidya Chitra Laoh Universitas Klabat

DOI:

https://doi.org/10.31154/cogito.v5i2.210.252-265

Abstract

This research aims to compare two methods of forecasting, i.e Multiple Linear Regression (MLR) and Genetic Algorithm-Neural Network (GA-NN), in forecasting dividend payout of Indonesian manufacturing company listed on Indonesia Stock Exchange from 2010-2014. Having collected 1384 firm-year observations, the result shows that these two methods could be used to predict dividend payout by considering earnings, free cash flow, growth opportunity, leverage, liquidity and size. This resesarch finds that even though both methods are powerful in prediction, yet in this case, MLR outperforms GA-NN. Keywords : Forecasting, Genetic Algorithm-Neural Network (GA-NN), Multiple Linear Regression (MLR), Dividend Payout Policy , Indonesian Manufacturing Companies

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