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The IUP Journal of Bank Management
Brexit Effect on the Volatility
of Indian Banking Stock Returns: Some Evidence
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The effect of Brexit was hard on the Indian economy affecting many industries, especially the banking sector. This paper empirically analyzes the effect of Brexit on Nifty index returns and two sectoral bank indices returns (includes both public and private sector banks). The time series data of closing prices of CNX Nifty and two sectoral bank indices were taken for a period of 247 days pre- and post-Brexit. The analysis of the data is based on 493 observations using ARCH and GARCH(1,1) model which is tested on all the three distributions—Normal, Student’s-t and Generalized Error Distribution (GED) and considered normal distribution results in detail. The results of Ljung-Box test indicate absence of serial correlation and results of ARCH(LM) test indicate absence of ARCH effect, though histogram normality test indicates that residuals are not normally distributed. The test results conclude that there is a significant impact due to Brexit on the stock returns of the Indian banking sector.

 
 
 

Banks are the backbone of any economy as they are the vital institutions in any country which significantly contribute to the development of an economy providing support to businesses. Banks allow businesses and households to mitigate risks from exposures to stock markets through derivative instrument transactions. India is a rapidly emerging economy with several public and private sector banks forming the core foundation for its growth and development process. In India, banks have to their credit several outstanding achievements such as financial inclusion, helping in demonetization and many small to large businesses to flourish and grow under the guidance and observation of the Central Bank, the RBI. In India, the performance of banks is monitored separately for public and private sector banks under sectoral indices CNX PSU Bank Index and CNX Private Bank Index, respectively.

Bank stocks experience volatility due to several macro or micro conditions in the economy taking cues from both global and local news, on a daily basis. Modeling stock volatility in periods of financial crises such as sub-prime crisis, Brexit, demonetization, etc. provides us with data that helps to forecast and predict to an extent the outcome from such volatile situations. This paper aims to fulfill the requirement of assessing the impact/effect on the banking sector during such financial crises to get better equipped with useful forecasting that provides certain amount of readiness, going forward. Banks being the money centers absorb huge risk from all such effects both directly and indirectly. Thus, modeling volatility in bank returns, encompassing both public and private sector banks to Nifty gives better estimate of risk absorbed and also helps to forecast the future volatility to an extent.

 
 
 
Bank Management Journal, Nifty index returns ,Two sectoral bank indices returns, Generalized Error Distribution (GED), Absence of serial correlation and results of ARCH(LM).