Title: Factors affecting equity price: a machine learning study of the Indian IT and FMCG industries

Authors: Amit Hedau

Addresses: NICMAR University of Construction Studies, Hyderabad, India

Abstract: The current study makes an effort to identify the factors that affect stock market prices using historical financial data from India's FMCG and IT industries. Machine learning (ML) techniques were used to examine the data from 2013 to 2022. According to the study, in both the sector PE ratios, ROE, and company sizes are common, whereas promoter holdings, the price/earnings-to-growth (PEG) ratio in the IT sector, and liquidity and operating profit margin in the FMCG sector, are sector-specific factors that affect the market price of stock. The study discovered that the XGBoost classifier had the highest prediction capability (89%). This study continues with the subject regarding the dominance of machine learning methods over statistical techniques. Stock market players can benefit from the study's findings by understanding the dynamics of the stock's market price and its underlying causes.

Keywords: capital market; equity pricing; machine learning; XGBoost; India.

DOI: 10.1504/IJAF.2025.152573

International Journal of Accounting and Finance, 2025 Vol.12 No.3, pp.185 - 197

Accepted: 20 Oct 2025
Published online: 27 Mar 2026 *

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