Amazon's share price value determinants: Using machine learning algorithms

Abstract

This paper aims to determine the factors affecting Amazon's share price based on machine learning algorithms at the level of macroeconomic variables or the company's financial ratios. The support vector machine algorithm was the most accurate for measuring the impact of the first variables, and the random forest was the most accurate for measuring the effects of the second variables. The first algorithm proved that the gross domestic product and the inflation rate are the most influential factors in Amazon's share price. The results of the second algorithm were divided into two parts. The first section measured the effect of financial ratios on the share price. The results showed that the asset turnover ratio (28 %) and the fixed asset turnover ratio (27 %) influence the company's share price the most. As for the second section, which is concerned with measuring the impact of each financial group, the results of which are: the total asset turnover ratio has the most influence on Amazon's share price by 63 % in activity ratios, the current ratio is liquidity ratios by 76 %, the gross profit margin ratio in profitability ratios by 62 %, Debt to equity ratio in solvency ratios by 27 %, and P/S ratio in valuation ratios by 95.1 %.