A Comparative Study of Stock Return and Volatility Across Major Indian Sectors Using ARIMA and GARCH Model

Abstract

Forecasting stock returns and analyzing market volatility are important aspects of financial research, as they help investors and financial analysts make informed decisions while managing investment risk. This study examines the return and volatility behaviour of five major sectors of the Indian economy: Banking, FMCG, Information Technology, Pharmaceutical & Healthcare, and Renewable Energy & Power. Using ten years of daily stock price data, the study applies the Auto-regressive Integrated Moving Average (ARIMA) model to forecast stock returns and the Generalized Auto-regressive Conditional Heteroskedasticity (GARCH) model to analyse volatility dynamics. The results indicate that return predictability and volatility persistence vary across sectors, reflecting differences in risk and market sensitivity. While sectors such as FMCG exhibit relatively stable performance, Banking, Pharmaceutical & Healthcare, and Renewable Energy show higher levels of volatility. The findings demonstrate the effectiveness of ARIMA and GARCH models in capturing sector-specific market behaviour and provide valuable insights for investors, portfolio managers, and researchers seeking to improve investment decisions, portfolio diversification, and risk management strategies in the Indian stock market.