CENTRAL BANK OF SRI LANKA
The Cost of Equity for Sri Lankan Private Banks: a CAPM Based Approach
Research Paper
By
K. P. M. Perera (1902)
Central Bank of Sri Lanka
i
This research paper is submitted in fulfillment of requirement to obtain the scholarship for post graduate studies abroad offered by
the Central Bank of Sri Lanka for its Staff Officers.
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Acknowledgement
This research paper was made possible through the help and support of everyone, including:
superiors & colleagues, family, friends, and in essence, all sentient beings, Please allow me to
dedicate my acknowledgment of gratitude toward the following significant advisors and
contributors:
First and foremost, I would like to thank Dr. Chandranath Amamrasekara & Dr. Roshan Perera
for their support and encouragement. They kindly read my proposal and offered invaluable
detailed advice on objectives, contents and the methodology to be used in presenting the paper.
Secondly, I should thank Mr. Nimal Gunawardena, Director, Internal Audit for his invaluable
advice during my stay at the department encouraging me for higher studies as well as all other
Directors and Deputy Directors who encouraged me.
Thirdly, I would like to thank all my collegues at Management Audit Department who
encouraged me, especially Ms. Chamila Rupasinghe, Ms. Thilini Jayasinghe amd Mr. Mahesh
Kumara of the Management Audit Department who read my paper and provided valuable
insights. Further, I should thank all my collegues at the Ministry of Defence & Urban
Development for encouraging me in finishing this paper early.
Finally, I sincerely thank my family and friends, who were supportive in making this study a
success. The production of this research paper would not be possible without all of them.
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Abstract
This paper is an empirical study of the cost of equity of Sri Lankan Private Banks listed in the
Colombo Stock exchange. A Single Factor Capital Assets Pricing Model (CAPM) was used to
examine the overall equity return of Sri Lankan Private Banks. Model which uses regression
analysis, has been tested for serial correlation and heteroscedasticity. Using pre-tested stationary
variables for the whole market based on monthly observations of averaged market returns and
risk free interest rate from 2003 to 2012, we find that: (i) equity market risk premium and risk
free interest rate explains over 80% of bank equity risk premium (ii) bank risk premium is
negative from 2007 to 2012 on 5 year monthly rolling regression (iii) Cost of equity of private
sector banks had declined from 3.28% to 0.62% from 2007 to 2012 (iv) cost of equity of banks is
very much less than cost of interest (v) Therefore, raising equity capital is cheaper for banks
instead of debt capital. It was observed that Sri Lankan market results are not consistent with
results of studies of either King (2009) or Thiripalraju et al (2011) on foreign markets.
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List of Annexures
1. Table 01 – List of Banks used for the study (Page 22)
2. Table 02 – Results of the Unit Root test (Page 22)
3. Table 03 – Results of the Heteroscedasticity test (Page 22)
4. Table 04 – Results of the study (Page 23)
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Table of Contents
Chapter One………………………………………………………………………………. 06
Chapter Two………………………………………...…………………………………….. 08
Chapter Three…………………………………………………………………………….. 11
Chapter Four…...………………………………………………………………………….15
Chapter Five……………………………………………………………………………….17
Chapter Six……………………………………………………………………………… 19
List of References…………………………………………………………………………. 21
Annexures………………………………………………………………………………….22
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Chapter One
Overview of the Study
1.1 Introduction
The best cushion a company has to absorb losses is the equity. That means, more the equity, less
the risk for creditors. However, based on the risk and return tradeoff theory more equity might
turn into higher cost. The cost of equity could be higher than long term debt due to several
factors such as tax deductible nature of interest and high risk premium for equity due to higher
risk. Therefore, analyzing the cost of equity in any company or industry is very important in
deciding the optimal capital mix in the long term.
1.2 What is Cost of Equity?
As per Damodaran cost of equity is “the rate of return investors require on an equity investment
in a firm”. This is the required rate of return (RRR) in the portfolio theory in finance on any
investment. The return of any investment is measured on market value of the investment as
historical data such as book value does not reflect the reality. As such, cost of equity should also
be measured on the market value.
1.3 Methods of Estimating Cost of Equity
There are several methods in measuring the cost of equity. One method is the accounting ROE.
Since the accounting ROE does not take into account the market changes in value of equity this
is not acceptable in academic research. Reported earnings divided by market capitalization is
another method and has been used by researchers in determining the cost of equity. However, a
more market based approach would provide a realistic picture of the cost of equity. Dividend
discount model introduced by Gordon in 1956 is another approach which has been widely used
in calculating the cost of equity. In this approach all future cash flows arising from equity are
discounted to get the present value of the stock and therefore cost of equity is the discount rate
which equalizes the market value of equity with present value. However, the most popular and
realistic approach might be Capital Assets Pricing Model (CAPM) as it incorporates the market
risk as well as individual company risk in calculating cost of equity of a company. From 2006
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onwards Federal Reserve System in USA has been using only CAPM approach in calculating the
average cost of equity of the bank in charging commercial banks for services provided. (King
M.R. 2009). More descriptive analysis of CAPM will be discussed under methodology.
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Chapter Two
Research Problem and Literature Survey
2.1 Introduction
Banking business entails borrowing at a lower rate and disbursing loans and advances at a higher
rate. They act as financial intermediaries of a country where they collect excess funds from
surplus units and loan to deficit units. Therefore, banks do a yeoman service to the growth of the
country. However, a banks’ balance sheet generally has liabilities with shorter maturities and
assets with longer maturities. This is called the maturity mismatch. Therefore, the industry is run
on the trust of depositors with the assumption that at any given point in time only a fraction of
the total depositors will withdraw the deposits. As a result, banking sector is said to be a very
fragile sector in any country.
2.2 The Background of the Research
In promoting financial system stability of the country, analyzing risk and return trade off of
equity of banks is of vital importance for policy makers in formulating capital regulations for
local banks as well as will help in applying the globally developed standards in the local arena.
Further, comparison of these rates and their patterns with other countries could reveal the
structural & conceptual similarities & dissimilarities of cross-border equity markets as well as
reactions of investors of bank equity to any dramatic changes in the financial markets.
2.3 Research Problem
In view of foregoing and the lack of local literature on the area, following research problems was
derived.
“What is the cost of equity of private sector banks in Sri Lanka in the last decade? Are
there any observable patterns in the behavioral trend of the estimated cost of equity?”
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2.4 Sample
The monthly stock market data for banks from January 2003 to December 2012 based on
availability, was used in estimations. All eight private banks who had listed stock during the
period of 2003 to 2012 were included in the study. Please refer, Table 01 of annexures for the
list of banks.
2.5 Prior Studies
Zimmer & McCauley (1991) estimated cost of equity of 34 international banks from six
countries over 1984-90 using the bank-level return on equity (ROE). This considers the ratio of
banks reported earnings to market capitalization. This ROE was averaged over time and across
banks from each country to arrive at a country specific ROE. They observed that real cost of
equity of UK, US & Canadian banks are higher compared to their counterparts in Swiss,
Germany & Japan. The authors recognized that though a backward looking accounting measure
is not ideal it has the advantage of being observable.
A Dividend Discount Model (DDM) had been used by Maccario et al (2002) to measure the cost
of equity of non-US banks in 12 countries from 1993-2001 period. They have used the earnings
yield with the assumptions that analyst forecast are the best estimate of next years’ earnings,
earning grow at the economic growth level and dividend payout ratio is constant. However, the
weakness of this approach is that banks with higher earnings will face a higher cost of equity.
They have concluded that banks in Canada, Holland and Sweden face higher cost of capital
compared to banks in Germany and Japan. Easton (2009) has highlighted the shortcomings of
past earnings based approach through empirical evidence, though, the approach has its own
merits.
2.7 Green et al (2003) described methods used by Federal Reserve Bank to charge for its
services from other banks. The cost of equity is necessarily an input for the calculation of Private
Sector Adjustment Factor for this. Up until 2002 an earnings based approach was used to
calculate the cost of equity. However, from 2002 to 2005 an average of earnings based figure,
discounted cash flows & CAPM based cost of equity was used. Barnes & Lopez (2006) has
concluded that recent research suggests that the Federal Reserve’s decision to set the COE
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estimate equal to that of the overall equity market (that is, to set their beta equal to one) is
reasonable.
King (2009) has estimated cost of equity for banks in six countries over 1990-2009 using CAPM.
As per him the cost of equity estimates declined steadily across all countries from 1990 to 2005
but rose from 2006 onwards. He summarizes the reasons for fall in the cost of equity as decrease
in risk-free rate over the period and a decline in the sensitivity of bank stock returns to market
risk in all countries except Japan.
Thiripalraju & Acharya (2011) used CAPM approach to estimate cost of equity of 19 Indian
banks from 2004-2009. They further estimated sector-wise cost of equity (public sector banks,
new private sector banks & old private sector banks) based on individual bank estimates. They
concluded that cost of equity increased for all banks in the study period though declined
marginally in 2009. As per them the major contribution for rise of equity came from increase in
risk free rate and marginally by rising CAPM beta.
As per Fama & French (1997) estimates of the cost of equity for industries are imprecise.
Standard errors are more than 3.0% per year are typical for both the CAPM and the three factor
model of Fama & French. These large standard errors are the result of the uncertainty about true
factor risk premiums and imprecise estimates of the loadings of the industries on the risk factor.
As per them estimates of the cost of equity for firms and projects am surely even more imprecise.
Baker & Wulger (2013) confirm that the equity of better-capitalized banks have both lower
systematic risk (beta) and lower idiosyncratic risk (firm specific risk) based on a sample of more
than 4000 banks and 70 years of data.
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Chapter Three
Methodology
3.1 Introduction
The cost of equity is generally defined as the expected return of purchasing the common stock of
a firm. Therefore, it is vital for asset valuations. This study being focused on private sector banks
present in the Colombo Stock Exchange, will be of importance to regulators at the Central Bank.
For example, the changes with regard to capital requirements coming up with the adaptation of
new BASEL requirements could have a direct impact on the cost of equity of banks. The
management of the banks as well as regulators could have an idea of the possible costs faced by
them based on these estimates.
3.2 Capital Assets Pricing Model
The Capital Asset Pricing Model introduced by Sharpe, Treynor, Lintner & Mossin
independently is one of the commonly used models to arrive at the RRR of a financial asset. It
basically consists of three variables. They are the risk free rate, expected market return or market
risk premium and the firm or industry specific beta.
3.3 Risk Free Rate
Risk free rate is the alternative an investor of a financial asset has, had he not invested in the
specific market. Generally, short term government bill rate is considered as an acceptable proxy
for risk free rate since they are default free in nature.
3.4 Market Return
Market return is the equity market return in the economy. This consists of two parts. That is
return due to capital appreciation and returns due to dividends. Returns due to capital
appreciation are the ASPI returns. Returns due to dividends do occur only a few times a year and
are generally factored in the market price as cumdiv. This can be supported by the Fama’s
efficient market hypothesis that all information of the value of the stock is factored in the market
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price since they are publicly available. As a result the stock price variances reflect the total return
of the stock. The market risk premium is the average return of the market minus risk free return.
3.5 Firm or Industry Specific Return
Firm specific return or the industry specific return depends on the return of the market.
Variability or volatility of the market returns is referred to as systemic risk. Firm specific risk is
the degree of volatility of the specific return in comparison with market volatility. This measures
the riskiness of the individual firm compared to the market. Estimating this sensitivity factor is
the core of this study. As a result company risk premium is the dependent variable and the
market risk premium is the independent variable.
3.6 Variable and Model Building
Three variables described above are constructed into form the following model.
Rit = Rft + β (Rmt - Rft ) + Eit………………………………………………………………………………………………....(1)
where, Rit = the return on the stock i on day t, Rft = the risk free rate, βi = the systematic risk of
stock I, Rmt = the return on the market on day t, εit = the error term in the model
The model can be rearranged as follows, based on the excess returns for the stock and the excess
returns of the market.
Rit - Rft = β (Rmt - Rft) + Eit
The model can be built in to a regression model as,
Rit - Rft = αi + β (Rmt - Rft) + Eit …………………………………………………………………………………………….(2)
Where αi refers to intercept which should not be statistically different from zero. The CAPM
beta (market risk factor) is the slope coefficient of the model. If β is less than 1 then firm or
industry return is less volatile compared to market and therefore, risk premium is less. If β is
higher than 1 it means individual asset return is more volatile than the market and therefore,
expected risk premium of investing in the stock is higher.
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3.7 Prior Observations on CAPM Based Approach
As per King (2009) researchers have found that CAPM beta estimates for individual stocks are
volatile and imprecise, and the residuals across firms may exhibit common sources of variation
due to omitted variables.
The CAPM model is most commonly estimated based on the realized excess returns. The
assumption is that historical returns are a good proxy for expected returns and monthly excess
returns are approximately independently and normally distributed through time. After the
calculation of Beta values the cost of equity can be calculated based on equilibrium relationship
in equation (1) above and analyzed for any observable behavioral patterns.
King has used 5 year rolling regression over each monthly return for each bank and averaged it
to obtain portfolio beta for each rolling period. This is because; beta is a time varying factor.
However, since decisions are made based on time bound data this analysis calculated beta on five
year rolling regression only at the end of the year from 5th year onwards. (i.e.2007). Thiripalraju
& Acharya (2011) has used the same approach in calculating cost of equity of Indian Banks from
2004 to 2009. The base for each estimation was made limited to past 5 years data. The
assumption is that estimations based on forward looking market model may not be realistic if the
data is outdated.
3.8 Stationarity Testing
All variables were tested for their stationarity using unit root test.(Table 2-Annexures) The
Augmented Dickey Fuller Test and Philip Perron tests were used to determine the stationarity of
individual variables. It was found that both the variables of average bank return and the ASPI
returns (Market return) are stationary at level, I(0) . Risk free interest rate (1 year treasury bill
rate) was considered as a stationary variable, I(0). As a result market risk premium (ASPI returns
– risk free interest) and banking sector risk premium (average bank return – risk free interest)
were found to be stationary at I(0) under Phillip Perron Test. Based on the test result & nature of
variable (return rate) it can be presumed that variable is a stationary variable. (Please refer Table
01)
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3.9 Testing for OLS Assumptions
After developing the model, OLS assumptions were tested for their validity. multicolinearity,
heteroscadasticity and the auto-correlation of the model are the most important assumptions.
Heteroscadasticity (variance of error terms are not constant) was tested using Breusch-Pagan test
using the following hypothesis (Table 3- Annexures). It was noted that model was free from
heteroscadasticity.
Ho = Model has heteroscadasticity
H1 = Ho is not true
P value 0.00<0.05, therefore, Ho is rejected. The model is free from heteroscadasticity.
3.14 Serial correlation (correlation of error terms) was tested using Durbin-Watson test.
Ho = Model has Serial Correlation
H1 = Ho is not true
No of observations = 120, No of independent variables =1
Value of Table Du=1.746 <2.06(DW statistic)<2.254
Therefore, model was found to be free from serial correlation
Testing for Multi-colinearity was not relevant since only one independent variable has been used
in the model.
3.10 Conclusion
In conclusion, model used satisfies all requirements expected of a model used in estimation of
future predictions.
ROE of government sector banks were not estimated, because it is a primary methodology of
estimating cost of capital which assumes returns equals cost. Further, results of ROE approach
are in anyway not comparable with cost of equity estimations derived using CAPM approach.
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Chapter Four
Empirical Results
4.1 Introduction
The table 3 to the annexures shows the extra-ordinary results of the research on investing in
equity in the Sri Lankan Equity Market. In all 5 years for which rolling average of ASPI returns
were calculated, the returns have been less than 3%. Comparatively, during the same period the
risk free rate (the 1 year treasury bill rates) has been a double digit number.
4.2 ASPI Returns
ASPI returns does not show a specific with a highest of 2.38% in 2010 and lowest of .79% in
2008. The average of the ASPI returns from 2003 to 2012 has been 1.92% whereas risk free rate
for the same period has been 11.26%. These drastic differences in the two returns could be
explained by the high demand by government for domestic debt during the peak of the global
financial crisis in 2007 & 2008. 1 year interest rate even exceeded 19% in that period.
4.3 Risk Free Rate, Market Risk Premium, Beta, Banking Risk Premium and Cost
of Equity
Cost of equity of a specific firm depends on three things. Those are market risk premium, risk
free interest rate and the firm specific beta.
The risk free rate has also behaved in the same trend with a 300 basis points increase in 2007
through 2009 and slight drops afterwards through 2012. As described earlier in 2009 risk free
rate reached its peak of 13.69% on 5 year rolling average and dropped slightly afterwards.
From 2007 to 2009 the market risk premium has been negative which has reached the peak and
dropped after 2009. This is mainly described by the behavior of the risk free rate.
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4From 2003 to 2012 the Banking Sector Beta has been 1.00 which shows that banking sector in
general, neither accepts more or less risk compared to overall equity market. However, during
the calculated period banking sector Beta has been on an increasing trend. From 0.87 in 2007 it
has increased to 1.1 in 2012. This shows the banking sector which was rather insensitive to
equity market changes have also become sensitive on a continuous scale. May be that resulted
from the financial crisis that took place in 2007 and financial turbulence that took place in the
local financial sector during the period.
Banking sector risk premium which is the product of the sector specific beta and market risk
premium is highest in negative terms in 2010 at -12% where beta is relatively high at 1.07 and
equity risk premium is also relatively high and negative at -11.28%. In negative terms it is lowest
in 2007 at -7.2% when market risk premium is relatively lower in negative terms at -8.3% and
beta is lowest at 0.87.
The cost of equity is steadily declining through 2007 to 2012 with highest being 3.28% in 2007
and lowest being 0.62% in 2012. This shows cost of equity of banks are coming down
continuously.
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Chapter Five
Conclusion and Recommendations
5.1 Introduction
This chapter tries to draw conclusions out of the empirical results in the previous chapter.
Correct interpretation of results is the most important task in the latter part of any study. Further,
making recommendations out of the conclusions made is also of vital importance. In summary,
the essence of the study is in this chapter.
5.2 Study in a Summary
The study provides estimates of real cost of equity of Sri Lankan private banks on a single factor
CAPM model which has been used by the Federal Reserve System. Cost of equity declined
steadily from 2007 to 2012. The behavior of both the risk free rate, equity market risk premium
and continuously increasing banking sector beta all three factors contributed to this behavior.
Most notable fact is for all 6 years equity market risk premium was negative primarily due to
ASPI returns being considerably lower than risk free interest rate. This is contradictory to theory
that equity market encompasses higher risk which should be compensated with higher risk
premium. Lack of informed decision making by investors in underdeveloped equity markets
might be the reason for this contrast. Kings study(2009) on banking sector cost of equity in 6
countries from 1990 to 2009 as well as study of Thiripalraju et al. (2011) on cost of equity of
Indian Banks from 2004 to 2009 all yielded positive annual bank risk premiums.
5.2 Results in Summary
The cost of equity is steadily declining through 2007 to 2012 with highest being 3.28% in 2007
and lowest being 0.62% in 2012. This shows cost of equity of banks are coming down. As a
result even with tax benefits associated with long term debt, banks will find it cheaper to expand
its equity capital. Further, these figures are considerably lower compared to figures revealed by
above two studies on India, Canada, France, Japan, UK and USA though time periods are not
exactly overlapping.
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5.3 Recommendations
Therefore, the banks can be recommended to expand their equity compared to long term debt
which would be beneficial for them in cushioning its deposits as well as cheaper in financial
terms.
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Chapter Six
Limitations of the Study
6.1 Introduction
Making aware of the readers of the limitations and weaknesses is of vital importance to any
research paper. It outlines the boundaries of the research in which validity of conclusions and
Recommendations would prevail.
6.2 Types of Limitations
The limitations of the study can be broadly divided under two headings. Those are the criticisms
put forward by academics on the theoretical basis of the model used and the practical limitations
of the study.
6.3 Prior Criticisms and Defences of the Model
The criticisms of the model have been highlighted by most of the researchers worked on the
subject. As cited by King, Fama & French (2004) group these shortcomings into two headings.
They are rational risk story and the behavioral story. Under the former, investors are rational and
forward looking and the financial markets are efficient. In this view the weakness of the model is
that investors think about only the mean and variance of the portfolio returns and other
dimensions of the risk have been ignored. The main empirical shortcoming as per King is that a
single market factor model is insufficient to capture the complexities in the cross section of the
realized returns. In the other view markets and the participants are said to be irrational and they
overreact to good and bad situations which swing asset prices out of the proportion of the
fundamentals. Therefore, systematic and predictable mispricing of assets occurs. However, Stein
(1996) has argued that whether expected return is rational or irrational they all form opportunity
cost of equity.
Further, the method used relies on five year rolling regressions. Overlapping windows imply that
beta changes slowly, with increases in the co-variance of banking sector returns relative to the
market only showing up over time. Alternatively, the regressions could be run on 12 months of
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returns which would definitely be noisier due to reduced number of observations. However, they
do not overlap and any change in covariance will appear more quickly.
6.4 Suitability of the Application
In view of the above weaknesses and consideration application of five year rolling regression
may be the most suitable in the given circumstances.
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List of References
King, M. R. (2009), “The cost of equity of global banks: a CAPM perspective from 1990
to 2009”, BIS quarterly Review, Sep 2009
Thiripalraju, M. & Acharya, R. (2011), “The cost of equity for Indian Banks: A CAPM
Approach”, Indian Institute of Capital Markets/Research, www.utiicm.com
Green, E. J., Lopez, J.A. & Wang, Z (2003), “Formulating the Imputed Cost of Equity
Capital for Priced Services at Federal Reserve Banks”, FRBNY Economic Policy Review /
September 2003, pp 55-81
Barnes M. L. & Lopez J. A. (2006), “Alternative measures of the Federal Rserve Banks’
cost of equity capital”. Journal of Banking and Finance, no 30, pp 1687-711
Damodaran, A.(2000). “Investment valuation: Tools and Techniques for Determining the
Value of Any Asset”, 2nd Ed. New York: John Wiley & Sons, Inc., pp 182
Fama, E. F. & French, K. R., (1997), “Industry cost of equity”, Journal of Financial
Economics 43 ( 1997) 153-193
Easton, P., (2007), “Estimating the Cost of Capital Implied by Market Prices and
Accounting Data∗”, Foundations and Trends in Accounting Vol. 2, No. 4 (2007) 241–
364
Baker, M. & Wulger, J. “Would Stricter Capital Requirements Raise the Cost of Capital?
Bank Capital Regulation and the Low Risk Anomaly”, http://people.stern.nyu.edu
McCauley, R. N. & Zimmer, S.A. (1991) “The cost of capital for securities firms in the
United States & Japan”, FRBNY Quarterly Review/ Autumn 1991
Zimmer, S.A & McCauley, R. N. (1991): “Bank cost of capital and international
competition”, FRBNY Quarterly Review/ Winter 1991, pp 33-59
MacCario, A., Sironi, A. & Zazzara, C. (2002), “Is Banks’ Cost of Equity Capital
Different Across Countries? Evidence from the G10 Countries Major Banks*”, Libera
Universita Internazionale degli Studi Sociali (LUISS) Guido Carli, Working paper, May.
xxii
Annexures
Table 01 – List of banks used for the study.
No. Bank Name
01 Commercial Bank
02 DFCC
03 Hatton National Bank
04 National Development Bank
05 Nations Trust Bank
06 Sampath Bank
07 Seylan Bank
08 Merchant Bank of Sri Lanka
Table 02 - Results of the Unit Root Test
Variable ADF (t statistic) P Perron (t statistic) I(0) or I(1)
Bank risk premium -2.896451 -9.090805 I(1)/I(0)
Market risk
premium
-2.604726 -7.929980 I(1)/I(0)
ASPI returns -9.470220 -9.602326 I(0)
Average bank
returns
-10.07972 -10.18152 I(0)
Table 3 – Results of Heteroscadasticity Test
Heteroskedasticity Test: Breusch-Pagan-Godfrey F-statistic 18.89475 Prob. F(1,118) 0.0000
Obs*R-squared 16.56287 Prob. Chi-Square(1) 0.0000
Scaled explained SS 61.44583 Prob. Chi-Square(1) 0.0000
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Table 4 –Results of the study
Year Risk Free
Rate
Bank risk
Premium
Cost of
equity
Equity risk premium
in the Market
Beta
2007 10.48 -7.2 3.28 -8.30 0.87
2008 12.65 -10.19 2.46 -11.85 0.86
2009 13.69 -11.80 1.89 -12.04 0.98
2010 13.60 -12.00 1.60 -11.22 1.07
2011 12.93 -11.96 0.97 -11.28 1.06
2012 12.03 -11.41 0.62 -10.37 1.1
2003-2012 11.26 -9.34 1.92 -9.34 1.00
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