A STUDY OF OPM RATIO: PUBLIC V/S PRIVATE SECTOR BANKS Authors: Parekh Komal, Sharma Sandhya (Finance) Abstract In this research paper we have done a study of OPM ratio of different banks in India. The objective was to study whether OPM is same across all the public banks and private banks in India. Our samples included secondary data and comparative analysis on twenty- three public sector banks and sixteen private sector banks. Our hypothesis on opm varies across public and private sector banks. And we proved our hypothesis using statistical techniques of Single way ANNOVA and T-test. INTRODUCTION A bank is a financial institution that provides banking and other financial services to their customers. A bank is generally understood as an institution which provides fundamental banking services such as accepting deposits and providing loans. There are also nonbanking institutions that provide certain banking services without meeting the legal definition of a bank. Banks are a subset of the financial services industry. A banking system also referred as a system provided by the bank which offers cash management services for customers, reporting the transactions of their accounts and portfolios, throughout the day. The banking system in India should not only be hassle free but it should be able to meet the new challenges posed by the technology and any other external and internal factors. For the past three decades, India s banking system has several outstanding achievements to its credit. The Banks are the main participants of the financial system in India. The Banking sector offers several facilities and opportunities to their customers. All the banks safeguards the money and valuables and provide loans, credit, and payment services, such as checking accounts, money orders, and cashier s cheques. The banks also offer investment and insurance products. As a variety of models for cooperation and integration among finance industries have emerged, some of the traditional distinctions between banks, insurance companies, and securities firms have diminished. In spite of these changes, banks continue to maintain and perform their primary role accepting deposits and lending funds from these deposits. Operating profit margin is a measurement of what proportion of a company's revenue is left over after paying for variable costs of production such as wages, raw materials, etc. A healthy operating margin is required for a company to be able to pay for its fixed costs, such as interest on debt. The Operating profit margin ratio indicates the profitability of current operations. OPM is a way for a company to measure the amount of revenue that is left over after their operating costs, thus helping to also determine an appropriate pricing strategy for products that are produced and offered.
OBJECTIVES To study the concept of OPM To study the application of OPM To study the OPM of public sector banks To study the OPM of private sector banks RESEARCH METHODOLOGY Data sources The research was quantitative in nature and secondary data (internet) was collected from established sources. The post-reform period of five years has been taken for the analysis of profitability of public sector and private sector banks in India. The years selected for analysis are 2009 to 2013. Sample Size Twenty-three public sector banks Sixteen private sector banks Tools of data collection The data for the study have been collected mainly from secondary sources comprising various audited reports and publication. Measurement technique used Excel based technique is used to come up the solution. T-test, ANOVA are used to test the hypothesis.
MAJOR FINDINGS H o : OPM across all banks is same H a : OPM across at least one bank is different Anova: Single Factor SUMMARY Groups Count Sum Average Variance Tranvancore 5 1 0 0 Punjab national bank 5 0 0 0 State Bank Of Bikaner and Jaipur 5 1 0 0 State Bank of India 5 1 0 0 State Bank Of Mysore 5 1 0 0 IDBI 5 0 0 0 Maharashtra Bank 5 1 0 0 Canara Bank 5 1 0 0 Central Bank of India 5 0 0 0 Corporation Bank 5 1 0 0 Dena Bank 5 1 0 0 Bank of baroda 5 1 0 0 Bank of india 5 1 0 0 Syndicate bank 5 1 0 0 Vijaya Bank 5 0 0 0 United Bank of India 5 1 0 0 Indian Bank 5 1 0 0 Indian Overseas Bank 5 1 0 0 Punjab & Sind 5 0 0 0 Oriental 5 1 0 0 Allahabad Bank 5 1 0 0 Union bank of india 5 1 0 0 Andhra bank 5 1 0 0 ANOVA Source of Variation SS df MS F P-value F crit Between Groups 0.12 22.00 0.01 5.73 0.00 1.66 Within Groups 0.09 92.00 0.00 Total 0.20 114.00 Since, F O >Fc that means REJECT the NULL which means that we accept the alternate hypotheses which says that at least one of the bank has different OPM. Now to find which banks have different OPM, we will conduct a t-test.
T-test for checking the OPM of Travancore bank and State bank H o : OPM of Travancore bank and State bank is same H a : OPM of Travancore bank and State bank is different t-test: Paired Two Sample for Means Travancore State Bank Of Mysore Mean 0.15 0.15 Variance 0.00 0.00 Observations 5.00 5.00 Pearson Correlation 0.73 Hypothesized Mean Difference - df 4.00 t Stat (0.08) P(T<=t) one-tail 0.47 t Critical one-tail 2.13 P(T<=t) two-tail 0.94 t Critical two-tail 2.78 Randomly, two banks i.e. Travencore bank and State Bank of Mysore bank were selected to check whether the NPM of these banks are same or not. But since the P-value > alpha, it means that the NPM are not different for both the banks.
H o : OPM of Vijaya bank and Indian bank is same H a : OPM of Vijaya bank and Indian bank is different T-Test: Paired Two Sample for Means Vijaya Bank Indian Bank Mean 0.07 0.19 Variance 0.00 0.00 Observations 5.00 5.00 Pearson Correlation 0.73 Hypothesized Mean Difference - df 4.00 t Stat (7.95) P(T<=t) one-tail 0.00 t Critical one-tail 2.13 P(T<=t) two-tail 0.00 t Critical two-tail 2.78 When the t-test was run for the banks like Vijaya bank and Indian Bank, it was found that the P- value < alpha, which means that both the banks have different OPM.
Hypothesis 2: H o : OPM across all private banks is same H a : OPM across at least one private bank is different Anova: Single Factor SUMMARY Groups Count Sum Average Variance HDFC 5 1.17 0.23 0 Axis 5 1.11 0.22 0 Federal 5 0.87 0.17 0 ING 5 0.61 0.12 0 Kotak 5 1.03 0.21 0 Yes Bank 5 1.14 0.23 0 Indusind 5 0.61 0.12 0 ICICI 5 0.89 0.18 0 Jammu & Kashmir 5 1.13 0.23 0 Karnataka 5 0.49 0.1 0 Dhanlaxmi 5-0.17-0.03 0.01 Laxmi Vilas Bank 5 0.4 0.08 0 South Indian Bank 5 0.73 0.15 0 Karur Vysya Bank 5 0.97 0.19 0 City Union Bank 5 0.76 0.15 0 Development credit bank 5 0.11 0.02 0.01 ANOVA Source of Variation SS df MS F P-value F crit Between Groups 0.45 15 0.03 11.22 0.00 1.83 Within Groups 0.17 64 0 Total 0.62 79 Since, Fo>Fc that means REJECT the NULL hypotheses which means that we accept the alternate hypotheses.this means that atleast one of the bank has different OPM. Now to find which companies have different OPM, we will conduct a t-test.
T-test for checking the OPM of Yes Bank and Indusind Bank H o : OPM of Yes bank and Indusind bank is same H a : OPM of Yes bank and Indusind bank is different t-test: Paired Two Sample for Means Yes Bank Indusind Mean 0.23 0.12 Variance 0.00 0.00 Observations 5.00 5.00 Pearson Correlation 0.78 Hypothesized Mean Difference - df 4.00 t Stat 7.08 P(T<=t) one-tail 0.00 t Critical one-tail 2.13 P(T<=t) two-tail 0.00 t Critical two-tail 2.78 When the t-test was run for the banks like Yes bank and Indusind bank, it was found that the P- value < alpha, which means that both the banks have different OPM T-Test for checking the OPM of HDFC and Axis Bank H o : OPM of HDFC and Axis bank is same H a : OPM of HDFC and Axis bank is different t-test: Paired Two Sample for Means HDFC Axis Mean 0.23 0.22 Variance 0.00 0.00 Observations 5.00 5.00 Pearson Correlation 0.90 Hypothesized Mean Difference - df 4.00 t Stat 1.01 P(T<=t) one-tail 0.19 t Critical one-tail 2.13 P(T<=t) two-tail 0.37 t Critical two-tail 2.78 Randomly, two banks i.e. HDFC bank and Axis bank were selected to check whether the OPM of these banks are same or not. But since the P-value > alpha, it means that the OPM are not different for both the banks.
Limitations It is based on secondary data which is collected from online websites The collected data is limited that is of 5yrs so if we increase or decrease the collection period the decision may vary. It is the Excel based data so it can contain minute error. Conclusion In this research paper it is proved that the operating profit margin across all the banks i.e public sector banks and private sector banks are same. It reflects the correlation between operating profit margin between all the banks. Operating profit margin ratio is by subtracting selling, general and administrative (SG&A), or operating, expenses from a company's gross profit number, we get operating income. It shows as how does management has much more control over operating expenses than its cost of sales outlays. Thus, investors need to scrutinize the operating profit margin carefully in the banks. Positive and negative trends in this ratio are, for the most part, directly attributable to management decisions. A company's operating income figure is often the preferred metric (deemed to be more reliable) of investment analysts, versus its net income figure, for making inter-company comparisons and financial projections. The objective of margin analysis is to detect consistency or positive/negative trends in a company's earnings. Positive profit margin analysis translates into positive investment quality. To a large degree, it is the quality, and growth, of a company's earnings that drive its stock price.