Predicting Stock Performance in Indian Mid-Cap and Small-Cap Firms: An Exploration of Financial Ratios Through Logistic Regression Analysis

The principal objective of this research was to investigate the impact of numerous financial ratios on the performance of mid-cap and small-cap stocks on the Indian market from 2018 to 2023. The aim was to create a predictive tool for stock price movements, utilizing logistic regression analysis as a tool to examine relationships between a dichotomous dependent variable and multiple independent variables. The research scrutinized nine key financial ratios. A binary dependent variable was established to represent stock price movements. The univariate logistic regression was initially employed to identify ratios with significance at a 95% confidence level. These selected ratios were then exposed to multivariate logistic regression to take into account interrelations, subsequently leading to the derivation of odds ratios for each financial ratio. The analysis encompassed 714 companies, revealing that mid-cap firms were more likely to experience stock price appreciation than small-cap counterparts. The results offer invaluable insights for investors and financial analysts, especially those focusing on mid-cap and smallcap stocks. Despite certain research limitations, this study lays a robust foundation for future investigations into the predictability of stock performance using financial ratios in emerging markets such as India.