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

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 %.

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Publication Details

Journal
Journal of Radiation Research and Applied Sciences
Published
2025-04-01
DOI
https://doi.org/10.1016/j.jrras.2025.101470
Citations
1
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
2.11

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article

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

H. E. Semary, Mohamed F. Abd El-Aal, Safar M. Alghamdi
1 citations
Journal of Radiation Research and Applied Sciences
Stock Market Forecasting Methods
2.11
article

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

H. E. Semary, Mohamed F. Abd El-Aal, Safar M. Alghamdi
article en
1 citations

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 %.

Journal of Radiation Research and Applied SciencesVol. 18(2)
Taif University (SA), Imam Mohammad ibn Saud Islamic University (SA), Arish University (EG)
Al-Imam Muhammad Ibn Saud Islamic University
Decent work and economic growth
Openalex Percentile: Top 15%
Stock Market Forecasting Methods
2.11
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Amazon's share price value determinants: Using machine learning algorithms — H. E. Semary, Mohamed F. Abd El-Aal, et al. · Journal of Radiation Research and Applied Sciences (2025) | TGRS Research Map | TGRS