Purpose The banking industry in India is contributing substantially to the economy, with over 7% of the GDP as part of the service sector. This study focuses on returns and volatility within the public and private sector bank indices, examining key characteristics such as persistence and leverage effect. Design/methodology/approach The current study used the daily closing prices of ten public sector and seven private sector bank indices from the Bombay Stock Exchange (BSE) between April 1, 2008, and March 31, 2024. The data is analyzed using GARCH, GARCH-M, and EGARCH models. Findings The results show volatility persistence in most indices, except for the Central Bank of India, which exhibits a faster mean-reverting process. The GARCH-M model reveals an insignificant risk premium across all indices, suggesting that investors may not be adequately compensated for taking on additional risk, potentially leading them towards more conservative investment approaches. Furthermore, the EGARCH model is the most effective for capturing volatility in the sampled indices. Research limitations/implications The current study is limited to analysing the returns and volatility of the banking sector, utilizing daily closing prices of indices and employing a univariate model to capture volatility characteristics. It can serve as a basis for future research to expand beyond the banking sector, applying multivariate models better to understand the effects of returns and volatility across sectors, and using different time intervals to capture a fuller picture of market dynamics. Originality/value Previous research has extensively focused on returns and volatility across various sectors; however, limited attention has been given to the banking sector. This study fills a gap by examining the Indian banking sector specifically. The insights gained from the study can be valuable for investors, as they enhance the understanding of stock market volatility, thereby aiding in portfolio construction and improving strategic investment decisions and risk management.
Kumar et al. (Sun,) studied this question.