Title: RELATIONSHIP OF NIFTY WITH PUNJAB NATIONAL BANK
Author: PURVA SANDEEP KADAV
Introduction:
Punjab National Bank (PNB) is one of India’s oldest and largest public sector banks, founded in 1894. Headquartered in New Delhi, it plays a key role in supporting India’s banking and financial system. PNB offers a wide range of services including retail banking, corporate banking, MSME finance, and international banking. With a strong nationwide branch network, the bank focuses on financial inclusion and economic development across the country.
Objective:
Calculation of beta of Punjab National Bank (PNB) and observe its significance.
Literature Review:
VIEW 1: Pawan Kumar Gupta
ANALYSING THE DYNAMIC INTERRELATIONSHIP BETWEEN NIFTY-FIFTY AND SECTORAL INDICES DAILY RETURNS OF THE NATIONAL STOCK EXCHANGE
Earlier studies on the Indian stock market have analysed the relationship between the Nifty-50 and sectoral indices to assess market behaviour and diversification opportunities. The literature shows that sectoral indices differ significantly in terms of volatility and correlation due to sector-specific factors. Researchers frequently use descriptive statistics, unit root tests, and correlation analysis to examine return characteristics. Most studies conclude that the Nifty-50 is relatively stable, while sectors such as realty, metal, and IT exhibit higher volatility.
VIEW 2: Jain, Dipak; Sarma, Susmita
An Analysis of Non-Performing Assets (NPA) on Punjab National Bank.
Previous studies on asset quality in Indian banking have consistently highlighted the rising concern of Non-Performing Assets, particularly in public sector banks. Researchers have found that weak credit appraisal, economic slowdowns, and sector-specific stress significantly contribute to the growth of NPAs. Several empirical studies focusing on banks like Punjab National Bank reveal that increasing NPAs adversely affect profitability, liquidity, and overall financial stability. The literature also emphasizes the importance of effective fund management and timely recovery mechanisms to improve asset quality and strengthen the banking sector.
Data Collection:
Data for Nifty50 and Punjab National Bank was downloaded from NSE India.com for the period 1/12/24 to 30/11/2025. Then, Friday closing prices where calculated. Then, weekly returns of Nifty and Punjab National Bank were calculated. Weekly return of Nifty was calculated. Weekly return of Nifty was taken as X and weekly return of Punjab national bank were taken as Y. Y was regressed as X.
Data Analysis:
Regression equation is Punjab National Bank(Y) = 1.78698 −0.0000808 Nifty50 (X)
The above equation shows the relationship between Nifty50 and Punjab National Bank. The negative sign means inverse relationship which means if Nifty50 rises Punjab National Bank fall and vice versa. If Nifty50 rises with 1 unit Punjab National Bank will fall by 0.0000808 units, the p value for Nifty50 is 0.892989 which is not less than 0.01 which means Nifty50 is not statistically significant at 1% level. No. of observations are 48. R Square is 0.000398 which means 0.0398% of the variances of Punjab National Bank are explained by Nifty50. 99.9602% is the error which is due to the variables which are not in the model. F is 0.018298 and the P value for which is 0.892989 which is not less than 0.01 overall model is not statistically significant at 1% level.
Conclusion:
A beta of −0.0000808 for Punjab National Bank is almost zero, which means the stock has no real connection with market movements. The small negative value is insignificant and does not indicate inverse behaviour. This is not good or bad by itself. It shows very low market risk but also means the stock does not gain from market rises and is influenced mainly by bank-specific factors.
References:
ANALYSING THE DYNAMIC INTERRELATIONSHIP BETWEEN NIFTY-FIFTY AND SECTORAL INDICES DAILY RETURNS OF THE NATIONAL STOCK EXCHANGE Pawan Kumar Gupta, Google Scholar, PK Gupta – researchgate.net.
An Analysis of Non-Performing Assets (NPA) on Punjab National Bank Jain, Dipak; Sarma, Susmita, Google Scholar, Special Education, 2022, Vol 1, Issue 43, p8404.