A Machine Learning Approach for Cash Dividends’ Forecasting: A Research on Manufacturing Sector

Dividend payment is a factor that affects investment decisions in capital markets. Although dividend payments indicate past performance of corporate, they also give some clues about company’s future performance. In this study, feasibility of Marsh Merton (M M) model is tested in Turkey tried to develop a better model than M M model by applying machine learning techniques. For this study payout ratios between 2003 and 2012 from 139 manufacturing companies which are quoted on ISE are selected. M M model and five machine learning models namely Multi-Layer Perception (MLP), Radial Based Function Networks (RBFN), Support Vector Machines (SVM) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) are compared with each other. Generally it is occurred that RBFN models produces similar results with M M model, MLP models cannot forecast low paid dividend and SVM model executes worse than M M model. As a result ANFIS model is observed the most successful method in forecasting dividends.