A statistical analysis on the performance of Hatton National Bank and Seylan Bank J

A statistical analysis on the performance of Hatton National Bank and Seylan Bank

J. A. G. Jayakody1*, S. Arivalzahan2

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1University of Jaffna, Sri Lanka
2 Department of Mathematics and Statistics, University of Jaffna, Sri Lanka [email protected]*
This paper examines the impact of the bank-specific determinants and macroeconomic indicators, on the performance of two highly recognized Sri Lankan commercial banks, Hatton National Bank and the Seylan bank. Bank performance means its profitability and it is measured by performance indicators. The prime performance indicators are Return on Assets (ROA), Return on Equity (ROE), Banks Size and the Share Price. Among these, Share Price has been considered as the most important performance indicator. Thus the study examines the company internal factors and macroeconomic variables affecting the share prices of the two banks as well. Internal factors are dividend per share or earning per share and the macroeconomic variables are represented by the Money Supply, Gross Domestic Product, Consumer Price Index, Lending rates, Inflation Rate and the Foreign Direct Investments. Ten years of data is employed in this study during the period 2007 to 2016. A descriptive statistical study has been carried out to compare the performance of the two banks and the Multiple Linear Regression is employed to identify the factors affecting share prices. Stepwise regression and the best subset regression methods are used to identify the best linear models for the two banks. Results suggest that the Hatton National Bank has a better performance, in the long run, compared to the Seylan Bank. Regression Analysis suggests that the money supply and bank lending rates are the only statistically significant variables in the study for both banks. And the money supply has a positive impact on the share price while lending rates have a negative impact on the share price as per our study.

Keywords: Profitability, Performance indicators, Descriptive Statistical Analysis, Regression Analysis, Share price

1. Introduction
Banking sector can be considered as the “lifeblood” of a country’s economy, in collecting deposits and providing credits to states and people, households and businesses. As the most important financial intermediaries, commercial banks provide transactional, savings, and money market accounts and that accept time deposits. Commercial banking plays a vital role in economy by mobilizing savings from various sectors. Furthermore, Hatton National bank and Seylan Bank can be identified as premier private sector commercial banks operating in Sri Lanka with many branches spread across the island. Those banks are internationally recognized for their eminent service toward the Sri Lankan public. Within the last two decades those two banks have witnessed some profound changes, as enhancements in technology, creating more employment opportunities, globalization threats which make them to remain profitable in this competitive environment. Those subtle changes in environment have a significant impact on their performance. Therefore, the determinants of bank performance became a major concern for researchers in recent past.
When the performance is better, investors tend to invest more on the bank by purchasing its shares. If a particular bank has a better share price performance, the investors are craving to purchase more shares as they want to gain maximum return on their savings. Whenever any bank needs to raise funds, they float their shares into the stock market and issue their shares through a system called initial public offering. Thus, factors affecting bank stock prices has been an issue of concern for the researches in the past.
Most of the studies suggest that these stock prices are affected by macroeconomic variables of the economy and the bank internal factors. Macroeconomic variables can be considered as Gross Domestic Product, Foreign Direct Investment, Inflation, Remittances, Interest rate, Money supply, exchange rate and many others. Earning per Share and Dividend per Share can be categorized as the most important bank specific factors which influence the stock prices.
The primary objective of this study is to investigate the bank specific determinants of profitability along with the macroeconomic, bank internal factors which affects the stock prices of the two banks.

2. Literature Review
A lot of research work has been done on the determinants of bank performance and the factors affecting stock prices. The most important bank performance indicators are return on equity (ROE), return on assets (ROA), bank size and share price.
Weerasinghe and Tissa Ravinda Perera (2012) conducted a study on determinants of profitability of commercial banks in Sri lanka by applying multiple regression method to the data. They have used bank size, liquidity risk, operating cost, capital adequacy and credit risk as the bank specific factors and GDP growth rate and interest rate as the macroeconomic factors. Their study suggests that bank size, operational cost and interest rate have contributed significantly to the profitability of commercial banks in Sri lanka.
Javaid et al., (2011) examined the internal factor analysis of profitability of top ten banks in Pakistan from 2004 to 2008. The capital ratio which is measured by total equity over total assets (TE/TA) conveys the capital adequacy and the soundness of the financial institution. His results suggested that TE/TA has a significant impact on the ROA.
Deger and Adem (2011) focused their study on, the profitability of commercial banks during 2002 to 2010 in Turkey. Bank size showed a strong positive and significant relationship with profitability. Their study reveals that larger banks have higher ROA and ROE comparing to rest of the banks.
Ça?atay and Yakup (2015) based their study on relationship between financial performance of banks and stock revenues. A panel data analysis is carried out during the period 2002Q1-2013Q2 and concluded that there is a significant positive relationship between the share price and the ratio of net profit of the year to the total assets which is an indicator of profitability.
Atiq and Roohullah (2008) conducted a study on factors affecting stock prices in the Karachi stock exchange (KSE). Their study extends from the year 2001 to 2008. The have employed earnings per share (EPS) and dividends per share (DPS) as the bank internal factors whereas money supply (M1), consumer price index (CPI), interest rates (LR) and gross domestic product (GDP) as the macroeconomic factors. Their study reveals that, money supply and earnings per share have a positive and statistically significant relationship with share prices.
Adam, Anokye M. and Tweneboah, George (2008) based their study on the macroeconomic variables and their role in the Ghana stock market during the period 1991 to 2006. They implemented co-integration analysis in order to examine the long term relationship between the variables; interest rate (LR), inflation rate (IR), foreign direct investments (FDI) with share price. They finally concluded their study with the results that stock price association with inflation and interest rates are negative while foreign direct investments has a slight positive effect on the stock market of Ghana.
No study has been conducted recently with these two banks and the better performance of these two banks will help the investors as well as the public to find out financial remedies and negotiate properly with their financial matters.

Mostly the secondary type of data has been used in this study and those are monthly financial data taken from the period 2007-2016 courtesy of Colombo Stock Exchange and Central Bank of Sri Lanka.
For analyzing the performance of two banks, we have used a descriptive statistical study equipped with graphical plots, charts and tables. Only for the purpose of analyzing share price, we have implemented stepwise regression and the best subset regression methods in this study.


4.1 Performance Indicators
The following variables have been employed as the key performance indicators in this study: return on assets (ROA), return on equity (ROE), bank size and the share price. In this study, share price is considered as the most important performance indicator of all time.

4.2 Descriptive statistical results
The tables below illustrate the descriptive statistical results of the two banks. Measures of location and measures of dispersion are reported and it provides an overall description about the performance indicator data.

Table 1: Descriptive Statistics of HNB
ROA% 1.6 0.1764 11.0 1.3 1.475 1.600 1.800 1.800
ROE% 17.560 1.762 10.0 14.300 16.375 17.6 19.375 19.900
Bank Size 457646 210365 45.0 232906 274034 413421 610940 858874
Share Price 171.12 39.54 23.0 72 147.5 163.8 210.75 233.75

Table 2: Descriptive Statistics of Seylan Bank
ROA% 0.903 0.430 47.6 0.120 0.578 1.015 1.255 1.400
ROE% 10.68 4.420 41.3 2.200 6.540 11.41 14.37 15.62
Bank Size 204696 74378 36.3 132764 148548 174803 261065 356013
Share Price 65.530 23.840 36.3 21.000 47.000 64.400 88.060 112.350

For the Seylan bank, ROA% has a larger coefficient of variation of 47.6% compared to its mean and HNB has a very small coefficient of variation compared to its mean which indicates, Seylan bank ROA% is highly volatile than HNB. Similar results manifested by ROE% as well for the two banks. Bank size emphasizes some distinct results, where HNB has a larger coefficient of variation compared to Seylan bank suggesting that HNB bank size movement is more volatile. Finally the share price and it seems more non-deterministic in both cases where Seylan bank has a higher coefficient of variation of 36.3% and HNB has a coefficient of variation of 23%.

Figure 1 and Figure 2 suggest that HNB has higher ROA and ROE values compared to Seylan bank indicating that HNB performed better throughout the period. ROA and ROE values are more deterministic in HNB while Seylan bank’s values are bit stochastic. Figure 3 illustrates that bank size is exponentially increasing in HNB outpacing Seylan bank which means it has a better performance.Figure 4 illustrates the distribution of share price during the particular time period. Though the HNB share price values are high, still it fluctuates rapidly and much volatile, variability is high. But the Seylan bank share price values are more deterministic comparing to HNB. And it has a slight increasing trend too. Figure 5, box plot suggests that the HNB share price range is higher than the Seylan bank share price range. And also it indicates that HNB share price values are positively right skewed while Seylan bank share values are almost following the normal distribution.
Though the descriptive statistics table suggests that Seylan bank share price has the highest coefficient of variation, but it seems so deterministic than HNB in the Figure 4.

4.3 Regression Analysis
Since the share price is the most important performance indicator among the others, we develop statistical models to study the influence of the explanatory variables in the share price of two banks.

4.3.1 Variables
The following variables have been employed as the explanatory variables in this study: money supply (M1), inflation rate (IR), lending rates (LR), dividend per share (DPS), foreign direct investments (FDI), while the dependent variable is share price of the two companies.

4.3.2 Stepwise Regression Results

Table 3 : Model with Stepwise regression method for HNB
Term Coefficient T-value P-value
Constant 166.5 9.10 0.000
M1 1.252 5.84 0.000
LR -4.948 -5.91 0.000
R^2 70.83%
Adj.R^2 70.15%

Table 4 : Model with Stepwise regression method for Seylan Bank
Term Coefficient T-value P-value
Constant 46.89 7.26 0.000
M1 1.002 12.98 0.000
LR -2.356 -8.26 0.000
R^2 88.52%
Adj.R^2 88.29%

Table 3 and 4 suggest that there are only two statistically significant variables in our final model for both banks. Those are money supply (M1) and lending rates (LR). And also the results suggest that there is a positive relation exists between money supply and share price while there is a negative relation exists between lending rates and share price. As per the table, total variability explained by the fitted regression model is 70.15% by the two significant variables for HNB whereas total variability explained by the fitted regression model is 88.29% by the two significant variables for Seylan bank. Furthermore, for a unit increase in money supply (M1) on average the share price will increase by Rs.1.252 and by Rs.1.252 for the two banks respectively. Similarly, for a unit increase in lending rates (LR) on average the share price will decrease by Rs.4.948 and Rs.2.356 respectively.

4.3.3 Best Subsets regression results for Hatton National Bank

The best subset regression involves in examining all the models for all possible combinations of predictor variables and determines the best set of predictors for each subset size. It can be used as an alternative to the stepwise regression procedures. The best subset regression is also known as all possible subsets regression.
For the Hatton National Bank, best subsets results have selected the model consisted with the variables money supply (M1) and lending rates (LR) as the ideal model for the above explanatory variables using Mallows CP as the model selection criteria where CP value is almost similar to the number of parameters and having the highest adjusted R-squared value of 70.1% and the least standard deviation of 21.6.

4.3.4 Best Subsets regression results for Seylan Bank

For the Seylan Bank, Best subsets results suggested the model with the predictor variables MI, IR, DPS and LR is the most ideal one among the other selected models, which is consisted of a CP value almost similar to the number of parameters, and has the highest adjusted R-squared value of 88.4 % and the least standard deviation of 8.1138.

In both cases, best subsets results have selected the model consisted with variables money supply (M1) and lending rates (LR) as the most ideal statistical model for two banks.

The utmost goal of this research session was to find out the factors affecting the share prices of two banks and a descriptive statistical study on the performance of the two banks using the main performance indicators and also finding the best linear model for the two banks, considering share price as the most important performance measure. For this study secondary data has been employed during the period of 2007-2016 courtesy of Central Bank Sri Lanka and Colombo Stock Exchange. Descriptive statistical study suggests that the Hatton National bank has the better performance comparing to the Seylan Bank throughout the period 2007-2016. Though HNB has a higher share price movement but still it is volatile comparing to the Seylan Bank. In other words Seylan Bank indicates more deterministic share price movement than the HNB. The major reason behind the downfall of the Seylan Bank share price movement is that in 2008 it is participated by the unfolding drama with the Golden Key Credit Card Company which has nothing to do with the global financial crisis. Due to the efforts pulled by the new management, Seylan bank was able to maintain a steady growth rate of share price movement thereafter. Stepwise regression results suggested that the Money Supply (M1) and the Bank Lending Rates (LR) are the key factors which influence the share price movement of the two banks. Furthermore the researcher carried out the best subset regression method for analyzing the factors again and found out that the results are identical.


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