Forecasting Financial Indicators of Public Joint-Stock Companies Using Machine Learning Algorithms

Student: Zamylin Sergey

Supervisor: Ilya Makarov

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2018

The paper is devoted to forecast the dividend payout ratio (percentage of the company's net profit paid to shareholders in the form of dividends) by machine learning algorithms. The author provides the main factors that may be taken into consideration in the formation of the dividend policy of the company. On the basis of the received factors, the training sample is formed. Prediction the dividend payout ratio is achieved through solving classification and regression problems.

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