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A Study on Predicting the Stock Prices of Banking and Non- Banking Financial Institutions

Mr. P. Gayathri,

Student of II MBA

Department of Management Studies. Madanapalle Institute of Technology & Science

 Dr. K.V. GEETHA DEVI, MBA, Ph.D.

Associate Professor, Department of Management Studies. Madanapalle Institute of Technology & Science

ABSTRACT

This study examines the prediction of stock prices for Indian banking and non-banking financial companies (NBFCs) from 2015 to 2024 using ARMA models. It analyses ten leading institutions—five banks such as SBI and HDFC, and five NBFCs including Muthoot Finance and Kotak Mahindra—to evaluate the ARMA model’s effectiveness in capturing stock price behaviour. After testing for stationarity with the Augmented Dickey-Fuller test and selecting optimal ARMA structures, forecasts were generated to assess trend alignment and accuracy. Results show that banking stocks exhibited more stable and predictable patterns, with strong autoregressive components in institutions like SBI and HDFC. In contrast, NBFC stocks were generally more volatile, leading to inconsistent forecasting results, though Muthoot Finance stood out by aligning well with its historical growth trends. The study acknowledges limitations of the ARMA model, particularly its assumption of linearity and inability to incorporate external shocks or market sentiments. Nevertheless, it highlights ARMA’s value as a foundational forecasting tool and recommends future research integrating macroeconomic variables to enhance prediction, ultimately supporting more informed investment decisions in the Indian financial sector.

Key words: stock prices of banking and non-banking of financial institution.