A Study on Market Capitalisation of Public Sector Banks in India

Transcription

1 A Study on Market Capitalisation of Public Sector Banks in India Kommajosyula Venkata Ramesh Asst. Professor, School of Economics and Finance Institute of Public Enterprise, Osmania University Campus Prof. A. Sudhakar Registrar, Dr. B.R. Ambedkar Open University, Jubliee Hills, Hyderabad Abstract The paper makes an attempt to find the pattern of movement of the SBI and Canara Bank stocks quoted at BSE and BSE total market capitalization and to find whether market capitalization of SBI and Canara Bank plays a significant role in the total BSE market capitalization. Market capitalisation is the total value of a company's free float as determined by its share price in the stock market; it is calculated as the number of free float of ordinary shares multiplied by the previous day's closing share price. The data is collected from Prowess database and statistical techniques like Simple regression, correlation matrix, simple line graphs, t- test, and tabulation of data. The paper concludes that the SBI and Canara Bank market movement was not in line to that of BSE Market Capitalisation but they have done significant contribution to the growth of the BSE Market Capitalisation. The paper makes an attempt to find the pattern of movement of the SBI and Canara Bank stocks quoted at BSE and BSE total market capitalization and to find whether market capitalization of SBI and Canara Bank plays a significant role in the total BSE market capitalization. Market capitalisation is the total value of a company's free float as determined by its share price in the stock market; it is calculated as the number of free float of ordinary shares multiplied by the previous day's closing share price. Thus market capitalisation = Share Price * Free float of shares. The market capitalisation of any stock is an important indicator showing what the worth of the company is. Data and sources: The Year End Market Capitalization of Canara Bank and State Bank of India, Total BSE market capitalization for the period to The data is collected from Prowess database. Tools used: Simple regression, correlation matrix, simple line graphs, t- test, tabulation of data. To study the influence of PSB market capitalization on BSE market capitalization a simple regression is run taking PSB market capitalization as an independent variable and BSE as a dependent variable for the study period. To obtain the influence of each PSB sector s market capitalization on the total BSE market capitalization, a simple regression is run taking each sector s market capitalization as an independent variable and BSE market capitalization as a dependent variable and coefficient is tested using t-test. Table:1 Contribution by Canara Bank and SBI to BSE Sensex Year Canara Bank SBI Total Contribution by Canara Bank and SBI BSE Sensex > RJSSM: Volume: 03, Number: 11, March-2014 Page 115

2 Source: Calculated from stock price and outstanding shares The above table represents the actual Market Capitalisation contribution of SBI and Canara Bank to Total BSE Market Capitalization. It is observed that during the year of the contribution of SBI has suddenly increase to Rs Crores and there after decrease till the year , it is inferred during this period it was traded at a high price and no of shares traded has increased enormously ( as seen in the Table: 3). There after the SBI market capitalization has shown an increasing trend up to the period of During the year the SBI market capitalization has shown a decreasing trend Rs Crores it is due to the decrease in the closing share price. The Canara Bank has shown a study progress in contribution of market capitalization over the study period barring the years of and this may due to the poor stock prices in the market. Table: 2 Contribution of Canara Bank and SBI to Total Market Capitalization (in %) Year Canara Bank SBI Contribution by Canara Bank and SBI Source: Table: 1 > RJSSM: Volume: 03, Number: 11, March-2014 Page 116

3 Figure: 1 From the analysis of table: 2 and figure:1 where the contribution of SBI and Canara Banks market capitalization to BSE Market Capitalisation is depicted for the period of to It is observed that the contribution of the SBI and Total BSE market capitalization are moving in the same direction. While the movement of the Canara Bank is horizontal to the X- axis which shows that there are no fluctuations in the Canara Banks contribution to the total market capitalization indicating consistent trend in its contribution. Table: 3 No. of Shares Traded in the BSE Year Canara Bank SBI Source: Compiled from Prowess data base > RJSSM: Volume: 03, Number: 11, March-2014 Page 117

4 Figure: 2 Number of Shares of Canara Bank and State Bank of India Traded in the BSE From the analysis of table: 3 and figure: 2 it is observed that the number of shares traded in the stock market is fluctuating in the case of SBI whereas the Canara Bank have declined in the initial phase of the study and there after it has become consistent. Both the banks have reported a sudden decline in the year which were reported at and numbers respectively. There after the trend of trading has increased in the year and over all it can be said that the trading has been consistent through out the study period. Regression analysis is used to assess the relationship between one dependent variable and several independent variables. This is the most commonly used technique in much of the social sciences research. Regression coefficient is a measure of how strongly each independent variable (also known as predictor variable) predicts the dependent variable. There are two types of regression coefficients unstandardized coefficients and standardized coefficients, also known as beta value. The unstandardized coefficients can be used in the equation as coefficients of different independent variables along with the constant term to predict the value of dependent variable. The standardized coefficient (beta) is, however, measured in standard deviations. A beta value of 2 associated with particular independent variables indicates that a change of 1 standard deviation in those particular independent variables will result in a change of 2 standard deviations in the dependent variable. If there is independent variable to predict one dependent variable, the beta value obtained would be same as the correlation coefficient between the dependent variable and the independent variable. R represents the correlation between the observed values and the predicted values (based on the regression equation obtained) of the dependent variable. R Square is the square of R and gives the proportion of variance in the dependent variable accounted for by the set of independent variables chosen for the model. R Square is used to find out how well the independent variables are able to predict the dependent variable. However, the R Square value tends to be a bit inflated when the number of independent variables is more or when the number of cases is large. The adjusted R Square takes into account these things and gives more accurate information about the fitness of the model. For example, an adjusted R Square value of 0.70 would mean that the IVs in the model can predict 70% of the variance in the dependent variable. While in natural science research it is not uncommon to get R Square values as high as 0.99, a much lower value ( ) of R Square R Value = R Square = Adjusted R- Square = > RJSSM: Volume: 03, Number: 11, March-2014 Page 118

5 Model Un standardised Coefficients t P Value. β Std. Error 1 (Constant) SBI Canara bank Dependent Variable: Sensex A high R-Squared value observed in the above table, may lead to a conclusion that linear model is good fit for the data. But, insignificant t-ratios of the regression coefficients at 1% suggest presence of Multi collinearity. This is observation is further strengthened by the strong correlation, 0.903, between SBI and Canara Bank. Correlations Canara bank SBI BSE Canara bank Pearson Correlation ** ** Sig. (2-tailed) N SBI Pearson Correlation ** ** Sig. (2-tailed) N BSE Pearson Correlation ** ** 1 Sig. (2-tailed) N **. Correlation is significant at the 0.01 level (2-tailed). From the above table, it is evident that the correlation coefficients between Canara Bank and SBI; Canara Bank and BSE ; SBI and BSE are significant at 1 % level. The correlation coefficients and of Canara Bank and SBI, respectively, with BSE suggest that returns of the two banks are highly positively correlated with Sensex returns. The co-movements of Canara Bank and SBI are in same direction and strong, as the correlation coefficient of is high and significant at 1 % level. Squared Euclidean Distance Variables PSB s BSE PSB s BSE Absolute Squared Euclidean Distance is computed and proximity matrix is obtained. The Table indicates that the dissimilarity between Canara Bank and BSE market capitalization is This indicates that there are dissimilarities between BSE market capitalization and PSU market capitalization to an extent of 14.6 percent. Proximity Matrix Correlation between Vectors of Values Canara bank SBI BSE Canara bank SBI BSE This is a similarity matrix This table is of no further use as the correlations computed were interpreted as above. > RJSSM: Volume: 03, Number: 11, March-2014 Page 119

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