MARKET STRUCTURE, STRATEGIC CHOICE AND BANK

PERFORMANCE: EVIDENCE FROM SRI LANKA

A DISSERTATION

Submitted to the

DEPARTMENT OF FINANCE

FACULTY OF COMMERCE AND MANAGEMENT STUDIES

In partial fulfillment of requirement of the

BACHELOR OF BUSINESS MANAGEMENT (SPECIAL) DEGREE IN

FINANCE

November 2014

Piyumi Chanika Amarakoon

BM/2009/012

Department of Finance

University of Kelaniya

Sri Lanka

ii

Certificate of Declaration

I, Piyumi Chanika Amarakoon, declare that this dissertation title “Market structure,

strategic Choice and Bank Performance is entirely my own work and has not

previously been submitted for a degree in any university. To the best of my

knowledge and belief, the dissertation contains no material previously published or

written by another person except where due reference is made in the dissertation

itself.

…………………………….

Piyumi Chanika Amarakoon

BM/2009/012

22/11/2014

Countersigned

Supervisor

Name : Ms. J.M.R. Fernando

Signature :

Date : 22/11/2014

iii

Recommendation

Hereby I recommend that the dissertation on “Market Structure, Strategic Choice and

Bank Performance by Piyumi Chanika Amarakoon (BM/2009/012) prepare under my

supervision can be accepted in partial fulfillment of the requirements of the Bachelor

of Business Management (Finance) special degree programme.

……………………….

Supervisor

Name : Ms. J.M.R. Fernando

Signature :

Date : 22/11/2014

iv

ACKNOWLEDGEMENT

I would like to take this opportunity to express my profound gratitude and deep regard

to Dr. D.M.Semasinghe, Dean of the Faculty of Commerce and Management Studies,

University of Kelaniya, Dr. P.N.D.Fernando, Head of the Department of Finance for

the opportunity that they have given for me as an undergraduate of the Department of

Finance to complete an important study about banking industry, which is vital

industry in the economy of Sri Lanka.

I am heartily thankful to my supervisor, lecturer Ms. J.M.R.Fernando, whose

encouragement, guidance and support from the initial point until the end. Her

insightful advices and expertise were very valuable to complete this research.

The accomplishment of this research would not have been possible without the

support of many others who also deserve acknowledgement and I would like to

appreciate all the lecturers of the Department of Finance for their support and advices

throughout the success of this study.

I should also offer my sincere thanks to my parents, who given me their blessing in

every moment and for all my friends and other persons who helped me with all the

ways that they can to complete the research and for giving me their encouragement

and thoughtful comments at the necessary situations.

v

Market Structure, Strategic Choice and Bank Performance:

Evidence from Sri Lanka

Piyumi Chanika Amarakoon

Department of Finance, University of Kelaniya, Sri Lanka

Abstract

The effect of market structure and performance of banking industry has been studied

extensively for American banks and for European banks. In contrast, little work has

been done to study this effect for Asian banks. Some of researchers in Sri Lanka have

identified the effect of market structure on performance of the banks. Even though

the market structure or market concentration has a direct effect to the performance,

the performance is also affected by the strategies that are followed by the banks and

those strategies such as risk taking strategy, cost efficiency and diversification create

an indirect effect of market structure to the bank performance. Hence, based on

structure conduct performance paradigm this paper has developed and tested the

performance of the banks in Sri Lanka.

As per the analysis, there is a significant positive effect of market concentration on

bank performance where as significant negative effects of risk taking strategy and the

cost efficiency strategy and insignificant negative effect from diversification strategy.

Furthermore, the paper has identified when there is a low market concentration the

performance of the banks, credit risk and cost efficiency is also low whereas with

high market concentration the performance of the banks and diversification is high,

but the credit risk and cost efficiency are low.

Keywords: Market structure, Operational Efficiency, Diversification, Credit Risk,

Bank performance

vi

CONTENTS

1. INTRODUCTION.................................................................................... 1-5

1.1. Background of the Study .............................................................................. 1-2

1.2. The Research Problem.................................................................................. 2-3

1.3. The objectives of the study ........................................................................... 3-4

1.4. Significance of the Study..................................................................................4

1.5. Scope and Limitations of the Study..................................................................5

1.6. Chapter Organization........................................................................................5

2. LITERATURE REVIEW ........................................................................ 6-17

2.1. Chapter Introduction.........................................................................................6

2.2. Review of Literature ................................................................................... 6-12

2.3. Chapter Summary ..................................................................................... 12-17

3. RESEARCH METHODOLOGY ............................................................ 18-27

3.1. Chapter Introduction.......................................................................................18

3.2. Research design ..............................................................................................18

3.3. Population and Sample Selection ............................................................. 18-19

3.4. Conceptual Framework............................................................................. 19-20

3.5. Operationalization..................................................................................... 20-22

3.6. Hypotheses of the Study ........................................................................... 23-26

3.7. Data Collection Techniques............................................................................26

3.8. Data Analysis and Model Specification ................................................... 26-27

3.9. Chapter Summary ...........................................................................................27

vii

4. RESULTS AND DISCUSSION ............................................................. 28-48

4.1. Chapter Introduction.......................................................................................28

4.2. An Overview of the Analysis ................................................................... 28-29

4.3. Data Analysis Method Used ...........................................................................29

4.4. Descriptive Statistics ................................................................................ 29-31

4.5. Testing the Normality .....................................................................................31

4.6. Testing the Ordinary Least Square Assumption....................................... 31-33

4.7. Correlations............................................................................................... 33-34

4.8. Regression Analysis.................................................................................. 34-40

4.9. Hypotheses Testing................................................................................... 40-47

4.10. Chapter Summary ...........................................................................................48

5. SUMMARY AND CONCLUSION ..................................................................49-54

5.1. Chapter Introduction.......................................................................................49

5.2. Summary of Results.................................................................................. 49-54

5.3. Conclusion ......................................................................................................54

REFERENCES ........................................................................... 55-56

APPENDIXES............................................................................ 57-61

viii

LIST OF FIGURES

Figure 01 Conceptualization.......................................................................................20

Figure 02 Summary of Direct and Indirect Effect ......................................................40

LIST OF GRAPHS

Graph 01 Testing Homoscedasticity..........................................................................32

LIST OF TABLES

Table 01 Table of Literature ............................................................................... 13-17

Table 02 Descriptive Statistics..................................................................................30

Table 03 Correlations between the Variables ...........................................................32

Table 04 Model Summary ........................................................................................33

Table 05 ANOVA Table...........................................................................................35

Table 06 Coefficients.......................................................................................... 36-37

Table 07 Summary of causal effects................................................................... 39-40

Table 08 Categorization of banks based on HHI ......................................................41

Table 09 Correlations (Banks with low HHI)...........................................................43

Table 10 Correlations (Banks with moderate HHI)..................................................43

Table 11 Correlations (Banks with high HHI)..........................................................44

ix

Table 12 Summary of Results...................................................................................50

Table 13 Relationship between market concentration and bank performance .........51

Table 14 Relationship between market concentration and risk taking strategy........52

Table 15 Relationship between market concentration and cost efficiency...............53

Table 16 Relationship between market concentration and diversification ...............53

LIST OF ABBREVIATIONS

ROA Return on Assets

ROE Return on Equity

MC Market Concentration

CR Credit Risk

CEff Cost Efficiency

DIV Diversification

1

CHAPTER I

INTRODUCTION

1.1 Background of the Study

The center of development in an economy is the financial markets and the institutions. From

all the financial institutions, the banks are playing a major role as a financial intermediary.

When considered the Sri Lankan economy, during past few years banking industry has

experienced a huge transformation due to tighten in the regulations mainly in risk

management framework, development in information and communication technology and

globalization of the banking industry.

The banking industry is the main intermediary in the financial services sector in Sri Lanka

which holds approximately 69% of the total financial assets (Central Bank of Sri Lanka,

2013). Therefore efficiency and performance of the banking industry are the key

requirements for the development of the sector. After more than thirty years of narrow

economic policies and financial control, the economic policy changes package was

introduced in 1977 which covered the way for structural translation of the overall economy

(Dunham & Kelegama, 1996). The policies included some drastic policy changes in relation

to deregulation of the financial services sector, along with the other economic modifications.

Financial restructurings in Sri Lanka commenced in past decades aimed to improve the

performance of banks through enhancing competitiveness and efficiency of the industry.

Initial structural changes in financial services sector were mainly focusing on giving greater

freedom to the private sector. So the government encouraged new entrants to the financial

services market. Those changes were affected to expand the scope of the banking industry as

well as to increase the number of firms in the banking industry. Structural changes in the

industry aimed to enhance competition expecting productivity and efficiency enhancements

2

in banks. Ultimately the policy makers aimed to improve the performance of overall banking

industry.

1.2 The Research Problem

Widen of the scope of the operations of the banks, increase in the number of banks and

branches, enhancing the quality of the human resource of the banks and increase in the

efficiency of the operations due to use of new technology has been affecting to the

performance of the banks. Even though these are observable, it is necessary to quantify how

far the performance of the banks is affected by the above mentioned factors. This research

focuses on identifying the direct and indirect effect of market structure, strategic choices such

as risk taking strategy/ credit risk, cost efficiency and diversification strategies on bank

performance and the relationship between market structure, strategic choices and the

performance of the banks in Sri Lankan context.

There are several strategies that the banks are used in order to increase the performance of the

banks. The first one lies in limiting the number of banking units in the market through

encouraging mergers among existing banks (Byeongyong, Choi and Weiss, 2005; Williams,

Molyneux and Thornton1994; Molyneux 1999; Moore, Robert, 1998). This helps to increase

the bank size for perusing scale of economics. The second strategy is the sharing common

facilities such as ATM with other banks in the industry. Both strategies are useful in

enhancing the competition in the market and improving the overall productivity and

efficiency of the market.

In Sri Lankan context, there is a continuous increase in the gross loans, deposits and also the

return on assets of the banks from 2009 onwards (Sri Lankan Banks, outlook 2012).

According to that, even during the world financial crisis situation these banks were

performing well when compared to the banks in world economy. The main reasons for that

3

were the several strategies followed by the Sri Lankan banks under the supervision of Central

Bank of Sri Lanka. A research conducted by Seelanatha (2010), identified the relationship

between market structure and the performance of the banks in Sri Lanka. But assessing the

strategies emphasized earlier is on the banks performance and identifies the relationship

between low, medium and high market concentration and bank performances are the current

necessities of the country.

In order to evaluate the consequences of these strategies, it is necessary to examine the

current market structure of the banking industry, to determine the degree of competition, and

to investigate the impact the concentration is likely to have on the market structure and the

behavior of banks. A greater level of competition and efficiency in the banking system can

contribute to better financial stability, product innovation, and access by households and

firms to financial services, which in turn can expand the prospects for economic growth.

Setting the point departure, this study would like to address “Whether the bank performances

are affected by the market structure, strategic choices such as risk taking strategy, cost

efficiency and diversification strategies.

1.3 Objectives of the Study

The purpose of this paper is to examine the direct and indirect effects of strategic choice and

market structure on bank performance. This research covers the study on market structure,

strategic choice and bank performance in several important ways. Therefore the objectives of

the study are;

i. To identify the direct and indirect effect of market concentration on bank

performance.

ii. To identify the effect of strategic choices (Risk taking strategy, cost efficiency

strategy and diversification strategy).

4

iii. To measure the relationship between market concentration and bank

performance.

iv. To measure the relationship between strategic choices (Risk taking strategy,

cost efficiency strategy and diversification strategy) and bank performance.

v. To measure the relationship between market concentration and strategic

choices (Risk taking strategy, cost efficiency strategy and diversification

strategy).

vi. To identify the effect of market concentration on strategic choices.

1.4 Significance of the Study

This study focuses to identify how the market structure and the strategic choices of the banks

finally affect to the performance of those banks. The research will help for the improvement

of the banking industry since this provides an idea of the best strategy that should be followed

by the banks. The strategies include risk taking strategy, cost strategy and diversification

strategy. Hence, the study assists the banks to select the best strategy in order to increase the

performance of the banks and to be competitive within their industry.

Thus the banks will be able to identify the relationships of the performance of the banks with

those strategies and how to manage those strategies within the competitive environment.

When acquiring the new technology to their operations, the banks can select the best

technology which is aligning with their strategy. The policy makers of the country will be

able to make the policies while generating the more advantages over the banking industry and

to the economy of Sri Lanka. The regulatory bodies can focus on putting the regulations

which will enhance the performance of the industry while increasing the growth of the

economy.

5

1.5 Scope and Limitations of the Study

However there are some problems when determining the sample and also determining the

model for the study. When determining the model for the study, there can be multi-co-

linearity situations, autocorrelation and hetroscedasticity.

The sample of the study should represent the whole population. Since the banks are having

different efficiency levels and also different performance levels, if the research concerns only

one to two categories it is difficult to give a suitable conclusion for the study. Thus it is

necessary to choose the reliable data sources in order to obtain the accurate inputs to the

research.

1.6 Chapter Organization

This paper is organized as follows. The next section presents a brief review of literature

related with market structure, bank operational efficiency, credit risk and diversification

giving special reference to the banking industry and hypothesis development. The third

section detailed the empirical framework used. The fourth section presents results and

implication of the study. The last section presents conclusions of the study.

6

CHAPTER II

LITERATURE REVIEW

2.1 Chapter Introduction

Literature review is an analysis of definition and the researches done by previous researchers.

The literature review can be explained as of the published work from secondary sources of

data in area of specific interest to the researcher. This research will focus on how the market

structure, strategic choices such as risk taking strategy or credit risk strategy, cost efficiency

strategy and diversification strategy affect to the performance of the banks. Hence, the

paragraphs below will discuss the previous literatures carry out with relate to the variables

such as market structure, cost efficiency, credit risk, diversification and measuring

performance of banks.

2.2 Review of Literature

The earlier studies as in the table 01 have used various methods such as structural and non-

structural approaches to measure the performance of banks with relate to different market

structures and different efficiency levels. Structural approaches are grounded on the

traditional industrial organization theory which concentrates on the structure conduct

performance (SCP) paradigm and on the efficient structure paradigm. Those literatures

mainly focused on the level of competition and how this is linked to concentration, and

whether the structure of the banking system does affect profitability. But non-structural

approaches assume that factors other than market structure and concentration may affect

competitive behavior, such as entry or exit barriers and the general contestability of the

market.

As per the past study conducted using structure conduct performance (SCP) paradigm, the

efficiency hypothesis and the P-R model (Mugume, 2006) there was a positive relationship

7

between profitability and market concentration according to the structure-conduct-

performance paradigm, but the efficient structure hypothesis interprets that the positive

relationship is not a consequence of market power but of the greater efficiency of firms with

larger market share. In other words, higher efficiency creates both higher concentration and

greater profitability. These two theories observed that there is a positive relationship between

the market concentration and the performance of banks. But the way of interpretation of the

relationship was different in those theories as efficient structure hypothesis explains an

indirect relationship of market concentration with the performance of the banks.

The relative market power hypothesis (RMP), which is a special case of structure conduct

performance states that the firms with large market shares and well differentiated product

lines have ability to exercise market power to obtain greater profit on non-competitive price

setting behavior, not directly but indirectly by interacting with other key determinants such as

bank age, bank ownership status and regulation (Mirzaei, Moore & Liu, 2001). They argued

that there is a positive relationship between profitability and market share in advanced

economies but not in emerging economies. Further they have found that the market power is

not directly influences bank performance. It is indirectly affect to performance by interacting

with other key determinants, such as market power, bank age, bank ownership status and

regulation. This study rebutted the direct positive relationship explained by Mugume, (2006).

The study conducted to identify the most powerful variable from market power and the

market efficiency that was having a major influence on the performance of the banks (Jeon &

Miller, 2005) concluded that there was a robust positive correlation between bank

concentration and the average return on equity and most powerful variable was the market

power not the market efficiency. Even though the increasing market concentration leads to

increase the profitability of the banks decreasing market concentration does not directly affect

the decrease in the profitability of banks. This research has confirmed the finding of

8

Mugume, 2006 which explains the positive relationship between market concentration and

the performance of banks.

According to the study carry out by Gldbreg and Rai (1995), the structure conduct

performance (SCP) hypothesis has emphasized that banks were able to extract monopolistic

charges in concentrated markets by their ability to offer lower deposit rates and charge higher

loan rates and the efficient-structure (EFS) hypothesis has stated that efficient firms increase

in size and market share because of their ability to generate higher profits which usually leads

to higher market concentration. Gldbreg and Rai (1995) has emphasized that the government

controlled banks are run less efficiently and consequently are less profitable also they have

not found a positive relationship between market concentration and profitability of banks in

European countries. The findings of the study are contrast to the research conducted by Jeon

& Miller, 2005 who have found the robust positive relationship.

Some of the researches emphasized that the market concentration was shown to be

insignificant in bank performance (Maudos, 1998). These findings suggested that bank

regulatory decisions based on concerns for their impact on changes in concentration may be

inappropriate and should focus instead on bank efficiency. Market share is used as

representative of the market structure, and has a statistically significant positive effect on

profitability. Thus the results show that efficiency is highly significant and positive when

determining the performance of banks. However market power has the moderate relationship

with bank performance. As per the literature, market power has considered as the market

power and rebutted the robust positive relationship explained by Jeon & Miller, 2005 and

accepted the results of the research carry out by Mirzaei, Moore & Liu, 2001.

Atemnkeng and Joseph (1999) found that there was a positive relationship between market

structure and banks profitability within the institutional context of the banking system and the

9

role of market concentration in the determination of bank profitability was very much

important. Further the overall result indicates that bank size, loan-deposit ratio and

devaluation were directly contributed to the profit rate of the banks while the loan-asset ratio

and operation expenses contrariwise affects banks profitability. The major theories applied

by this study were the structure conduct performance (SCP) hypothesis and the relative

market power (RMP) hypothesis. Corporate performance of the banks which is calculated by

using return on assets, return on capital and return on equity was the dependent variable and

the independent variables were the market concentration, management of capital of the bank,

loan portfolio of the bank, total advances to total deposit, bank size measure, expense control

and compositions of deposits of the bank. Still the research emphasized that the market

power is vital when measuring the performance of the banks rather than the relationship with

other variables.

Muharrami, Saeed, and Kent (2009) have analyzed the relationship between market structure

and bank performance. For that purpose they have employed four hypotheses to test the

relationship between efficiency, market structure and profitability the main hypotheses used

by them were the structure conduct performance (SCP) hypothesis and the relative market

power (RMP) hypothesis. The research has found that there was positive relationship

between profits of the banks and market structure and the presence of an efficiency measure

provides support for the traditional structure conduct performance (SCP) rather than relative

market power (RMP) hypothesis. The evidence presented in the study clearly supports the

view that concentration is the principal structural determinant of profitability and not market

share. It has again proved the findings of Mirzaei, Moore & Liu, 2001.

Some literatures aimed to evaluate the role of market structure in the pricing behaviour and

profitability (More and Marton, 2003). A simple Cornet model has developed by them in

order to determine the most important variables related to the pricing behaviour of the banks

10

and profitability of the banks. The major theories applied by this study also were the

structure conduct performance (SCP) hypothesis and the relative market power (RMP)

hypothesis. One of the most important findings of this study lies in showing that the tests

could not confirm the SCP, as market concentration was found to have no positive correlation

with either the net interest margin or ROA. This research implied that banks did not earn

higher profits by means of conspiring with other banks to apply higher margins in more

concentrated markets. And the empirical results provided support for the RMP hypothesis.

Furthermore the results of the research have proved that cost and risk levels and the size of

reserve requirements have become incorporated into pricing decisions. According to the

literature, there appears to be a close negative correlation between the relative size of the

banking sector and pricing and the profitability. This is more against the conclusions

provided by most of the researches discussed in the literature as the positive relationship

identified in between market structure and profitability of banks.

The research conducted by Belkhaoui, Lakhal, Faten and Hellara (2014) has shown that

market structure has a positive and indirect effect on bank performance and that market share

has a positive and direct effect on bank performance. Strategic variables related to risk

taking and diversification affect directly and indirectly bank performance and the indirect

effect occurs via market share. The results suggested that the mediating role played by the

strategic choice in the relationship between market structure and performance is complete.

In order to identify the relationship between market structure, strategic choice and the

performance of the banks they have built a model using path analysis. To measure bank

performance they have used the present value of expected future profits, not the return on

equity or return on assets and market structure was calculated using the market concentration.

Several types of strategic choices were observed by them called risk taking strategy and

diversification strategy and cost leadership strategy. Belkhaoui, Lakhal, Faten and Hellara

11

(2014) have identified a gap which is not identified by other researchers, that is to consider

the strategies followed by different kind of banks in different nations. It leads to get an

understanding of the best strategy which should pursue by the banks in order to increase the

performance of the banks.

The study conducted by Seelanatha (2010) has studied main structural and performance

features of banking industry in Sri Lanka. The study used the hypotheses proposed by Berger

and Hannan (1997) called structure conduct performance (SCP) hypothesis, the relative

market power (RMP) hypothesis and relative market power (RMP) hypothesis and two

performance measures namely return on assets (ROA) and net interest margin (NIM).

Empirical results are not consistent with both market power hypothesis and structure conduct

performance hypothesis. It is appeared that high market concentration with small number of

large banks in the industry has intensified the competition. Confirming the major arguments

against the profit concentration relationship, this study totally rejected the traditional SCP

hypothesis. However the findings of the study rejected significant profit market power

relationship. Empirical results pointed out that efficient operation of banking firms are vital

for having higher profitability with better net interest margin. This study has established the

view of Mirzaei, Moore & Liu, 2001 that there is not having a positive relationship between

market powers or the market concentration and the performance of banks in the emerging

countries.

Consequently, some researchers argued that there is a vigorous positive relationship between

market structure and bank performance while some have found that there is a positive

relationship in the banks in advanced economies rather than the banks in the emerging

countries. Several researches emphasized that the market structure is the main determinant of

the performance of banks than the market share. But accordingly there are few factors such

as bank age, bank ownership status and regulation which are supported to be interacted with

12

the market power when agree on the positive relationship with the performance of the banks.

The little number of researches has concluded the negative relationship between market

structure, market power or market concentration and the profitability of banks.

2.3 Chapter Summary

Since in an emerging economy, the concentration on the finance institutions mainly on the

banks are very significant it is necessary to judge what would be the best strategy that should

follow in order to achieve the competitive advantage. Having considering strategic choices,

some of the researchers conducted their researches and have found a positive relationship

between market structure and the performance of banks with direct and indirect relationships.

Even though the research carry out in the Sri Lankan context concluded that there is not

having a positive relationship between market structure and performance, emphasized that

efficiency and performance of the banks in Sri Lanka is having direct relationship.

13

Table 01: Table of Literature

Title Authors Problem Objectives Methodology Findings

Market

Structure

and

Performance

in Uganda's

Banking

Industry

Adam

Mugume

The level of competition

and how this is linked to

concentration, and

whether the structure of

the banking system does

affect profitability

To examine the competitiveness of

Uganda’s banking industry.

To examine Uganda’s banking industry

market structure and its impact on banks’

profitability.

To examine bank efficiency and its

possible impact on the market structures

To empirically ascertain the relative

strength of market power and efficiency

in explaining the banks’ profitability.

The P-R Model A positive relationship

between profitability

and market

concentration according

to the SCP paradigm.

A higher efficiency

creates both higher

concentration and

greater profitability

according to efficient

structure hypothesis.

Does Market

Structure

Matter on

Banks’

Profitability

and Stability

Ali

Mirzaei,

Tomoe

Moore &

Guy Liu

Can the market power

hypothesis be applied to

the emerging market

banking system?

Why are banks operated

in the emerging

economies more

profitable than their

counterparts in advanced

economies?

To what extent are

discrepancies in

determinants of bank risk

and returns due to

Investigate the effect of market structure

in banks on profitability and stability, in

particular whether banks, who are

operating in concentrated markets

generate more profit or not, whilst taking

into account of the bank-specific

characteristics; whether banks are

efficiently managed.

Examine overall effect of financial

structure and macroeconomic conditions;

whether financial development and

business cycles affect bank risk and

returns.

Profitability – ROA

Market structure -

market share and market

concentration (Lorenz

Curve for market share)

A positive relationship

between profitability

and market share in

advanced economies.

Market power not only

influences bank

performance directly,

but also indirectly by

interacting with other

key determinants.

14

variations in factors

under the control of bank

management and/or

factors relating financial

structures?

Market

structure,

strategic

choices and

bank

performance

Samir

Belkhaou,

Lassaad

Lakhal,

Faten

Lakhal &

Slaheddie

Hellara

Whether the market

structure, strategic choice

(risk taking,

diversification and cost

leadership) affect to the

performance of the

banks?

Develop and test a conceptual model of

bank performance.

Use of the path analysis method to

estimate the direct and indirect

relationships.

Bank Performance -

Present value of

expected future profits,

Market structure -

Market Concentration,

Bank strategic choice

(Risk-taking,

diversification

strategy and cost

leadership strategies)

The market structure has

a positive and indirect

effect on bank

performance, and that

market share has a

positive and direct effect

on bank performance.

Strategic variables

related to risk taking and

diversification affect

directly and indirectly

bank performance. The

indirect effect occurs via

market share.

Bank

Performance

: Market

Power or

Efficient

Structure?

Yongil

Jeon &

Stephen

M.

Miller

Why are more

concentrated markets

more profitable?

The paper considers the market-power

versus the efficient structure theories of

the positive correlation between banking

concentration and performance on a

state-by-state basis.

Market structure -

Market Concentration &

Profit-Structure

Relationships - market

power and efficient

structure theories

Robust positive

correlation between

bank concentration in a

state and the average

return on equity within

that state.

15

The

structure

performance

relationship

for European

banking

Lawrence

G.

Gldbreg

& Anoop

Rai

The structure

performance relationship

for European banking is

also positive as the

American banks?

Measure the performance of the

European banks.

The Berger and Hannan

(1993) model

Government controlled

banks are run less

efficiently and

consequently are less

profitable.

Market

structure and

performance

in Spanish

banking

using a

direct

measure of

efficiency

Joaquin

Maudos

Does the market structure

of Spanish banks affect

to the performance of

those banks?

Paper analyses the relationship between

market structure and performance within

the Spanish banking industry.

Performance - ROA,

ROE, Efficiency - data

envelopment analysis

Market share is used as

representative of the

market structure, and

has a statistically

significant positive

effect on profitability

Market

Structure

and

Profitability

Performance

in the

Banking

Industry of

CFA

Tabi

Atemnkeg

J. &

Nzongang

Joseph

Does the market structure

affect to the performance

of the banking industry

of CFA?

The main objective of this study is to test

empirically the Structure - Performance

(S- P) hypothesis within the context of

the Cameroonian Commercial banking

system.

Corporate Performance -

ROA, ROC, ROE

Independent variables –

market concentration,

Management of bank’s

capital, Bank’s loan

portfolio, Total

advances to total

deposit, Bank size

measure, Expense

control, Compositions of

The relationship

between commercial

bank profits and

concentration or market

power is positive and

the coefficient is

statistically significant

at the 5 percent and 10

percent level in the

specifications

16

the bank’s deposits

Market

Power

versus

Efficient-

Structure in

Arab GCC

Banking

Al-

Muharrai,

Saeed,

Matthews

& Kent

What is the factor from

market power and

efficient structure which

is affecting to the

performance of the Arab

banks?

Assess the relevance of the Structure-

Conduct-Performance (SCP), the

Relative-Market-Power (RMP) and the

Efficient- Structure (ES) hypotheses in

the GCC banking industry.

Examine the evidence for the Hicks

(1935) Quiet Life Hypothesis (QL).

Performance - ROA,

ROE

Efficiency - Berger and

Hannan (1993) model

Concentration – HHI

The evidence presented

here clearly supports the

view that concentration

is the principal structural

determinant of

profitability and not

market share

Relationship

Between

Market

Structure

and Bank

Performance

Csaba

Móré &

Márton

Nagy

Do the changes in the

operating environment

also exert a substantial

impact on the structure of

banking markets and the

degree of competition?

Do the dominance of

private (foreign)

ownership and stable

financial systems in

place, banks'

performance and pricing

behaviour have become

increasingly market-

based.

The study aims to assess the role of

market structure in the pricing behaviour

and profitability of Central and Eastern

European banks.

Price of a product-

average loan rates

Performance -

ROA,ROE

Market structure -

Market Concentration

The tests could not

confirm the SCP

hypothesis in Central

and Eastern Europe, as

market concentration

was found to have no

positive correlation with

either the net interest

margin or ROA. This

implies that in more

concentrated markets,

banks did not earn

higher profits by means

of colluding with other

banks to apply higher

margins.

17

Market

structure,

efficiency

and

performance

of banking

industry in

Sri Lanka

Lalith

Seelanata

How the banks’ market

structure and banks’

efficiency have

influenced the

performance of the

banking firms?

This paper reviewed how the banks’

efficiency and market structure affect the

overall performance of the banking firms

measured in terms of profitability and net

interest margin using structure conduct

performance literature.

Performance - ROA,

ROE

Efficiency - Berger and

Hannan (1993) model

Concentration – HHI

The traditional structure

conduct performance

argument is not held in

the banking industry in

Sri Lanka and the banks

performance does not

depend on either market

concentration or market

power of individual

firms but on the level of

efficiency of the

banking units.

18

CHAPTER III

RESEARCH METHODOLOGY

3.1 Chapter Introduction

This chapter discusses the methodology for the study which includes the research

design, population and sample selection, operationalization, conceptualization,

hypothesis development, data collection techniques and model specification to

facilitate the study to achieve the established objectives.

3.2 Research Design

The research focuses on identifying the effect of market structure, strategic choices

such as risk taking or credit risk, operational efficiency and diversification and the

performance of Sri Lankan Banks and the relationship between those variables. This

is a descriptive and deductive study which is to identify the effect and the relationship

between each of the variables. The research quantifies the data and generalizes the

results from the sample to the population of interest while testing the hypothesis

generated with relate to the objectives of the study.

3.3 Population and Sample Selection

The focused population consists of Licensed Commercial Banks in Sri Lanka for five

years starting from 2009 to 2013. From those banks, the research concern is all the

licensed commercial banks in Sri Lanka except Union bank of Colombo and Amana

Bank due to unavailability of sufficient information throughout the research period as

both banks have started those operations on 2010, since therefore it is unable to obtain

the financial information for year 2009. The licensed specialized banks have been

19

ignored from the sample since the financial position, financial performance,

efficiency, market concentration and also the risk management system are not same as

the licensed commercial banks and therefore it is unreasonable to include in the same

sample as to analyze the effect and relationship between market structure, strategic

choice and bank performance.

Therefore the sample includes all the licensed commercial banks excluding Union

bank of Colombo and Amana Bank for five years begins with 2009 to 2013 which

represents almost all the banks in population. The sample is selected based on the

convenience and considering the availability of the information.

3.4 Conceptual Framework

The conceptual framework of the study is based on the Structure Conduct

Performance (SCP) paradigm developed by Joe S. Bain in Industrial Organization

Economics which offers a causal theoretical explanation for firm performance through

economic conduct on incomplete markets and it is published by Edward Chamberlin

and Joan Robinson. The market concentration can be identified as the structure, the

strategic choices as the conduct and the return on equity and return on assets as the

performance. According to that the conceptualization of the study can be developed

as follows.

Market Structure Strategic Choices Bank Performance

Figure 01: Conceptualization

3.5 Operationalization

As this study is about the market structure, strategic choices including risk taking or

credit risk, cost efficiency and diversifications and the performance of the banks it is

necessary to identify the operationalization of the selected variables.

Bank Performance

Here the performance of the banks is the financial performance which can be simply

expressed as the profitability of banks. It can be measured using Return on Assets

(ROA) or Return on Equity (ROE). The equations are as follows,

N

a

b

Diversification

Cost Efficiency

Credit Risk

Market

Concentration

ROA and

ROE

ROA = Net Income

Total Average Assets

et income is identified based on the n

ssets and average equity are obtained

alances by two.

ROE = Net Income

Total Average Equity

20

et profit after tax of the bank. Total average

from dividing opening balances plus closing

Market Structure/ Market Concentration

The market structure can be explained as the relative market share of each bank.

This is also known as the market concentration. Market concentration can be

measured using the Herfindahl-Hirschman index (HHI) which is widely used in the

past literatures (Seelanatha, 2010 and Belkhaoui, Lakhal, Faten & Hellara, 2014).

I

s

S

d

o

e

C

C

c

m

HHIt = ∑ ܵܯ)ୀଵ it)

2

n the HHI index, t means the end of the particular period, n means the number of

ectors that the bank is focusing on and the i means the particular bank of the sample.

ince the HHI index is used in two independent variables, market structure and

iversification there can be occurred a multicollinearity problem. So the market share

f each bank is eliminated from the index. Market share of bank i measured at the

nd of each year t, by using the ratio below.

redit Risk

redit risk is the potential for losses due to failure of a borrower to meet its

ontractual obligation to repay a debt in accordance with the agreed terms. It can be

easured as follows;

CR = Non Performing Loans

Total Bank loans

MSit = Deposits of the bank i

Total deposits of the banking sector

21

Managing the credit risk can be identified as a risk taking strategy that can be used by

the banks in order to mitigate the risk of reducing the quality of assets of the banks.

Diversification

Another strategy that can be used by banks is the diversification strategy. This

reflects the variety of assets included in statement of financial position of the banks

such as advances and loans, other assets and the fixed assets of the banks.

Diversification of assets is measured by using Herfindahl-Hirschman index (HHI) of

assets.

I

s

p

a

i

C

I

t

T

c

HHIit = ∑n(Assetk/Total assets of the bank)2

k=1

n the HHI index, t means the end of the particular period, n means the number of

ectors that the bank is focusing on, k means the type of the assets and the i means the

articular bank of the sample. The main assets types are loans & advances, fixed

ssets, other interest earning assets and non interest earning assets. According to the

ndex, a high index value indicates a low diversification of the banks.

ost Efficiency

n terms of banks the cost efficiency means, how far the revenue can be generated by

he bank while minimizing the operational cost of the bank.

CEff = Total expenses – Finance CostRevenue

22

his strategy will helps to discover the banks’ ability to move with market

ompetition as cost leaders while enhancing the profitability level of the banks.

23

3.6 Hypotheses of the Study

The relationship between market structure, strategic choices and bank performance is

basically based on the structure-conduct-paradigm. According to Muharrami, Saeed,

and Kent (2009), market structure is the principal determinant which is positively

affect to the performance of banks which is significant. Belkhaoui, Lakhal, Faten and

Hellara (2014) also explained that there is a positive relationship between market

structure and bank performance. As per the study conducted by Mugume (2006) there

was a positive relationship between profitability and market concentration according

to the structure-conduct-performance paradigm. These literatures lead to following

hypothesis;

H1 – Market Concentration positively affect to the bank performance

According to Hicks’s (1935) “Quiet Life Hypothesis” firms trying to secure their

operations if the firm is more concentrated. With relate to banks, it would increase

the risk of assets portfolio which would finally increase the credit risk. Then the

banks may try to focus on more supervision and monitoring process and it would

cause to go away from the risk taking strategy (Belkhaoui, Lakhal, Faten and Hellara,

2014). Therefore there is a negative relationship between market concentration and

risk taking strategy where the effect of market concentration on risk taking strategy is

significant. This can be concluded as the hypothesis below.

H2 - Market Concentration negatively affect to the risk taking strategy

The effect of market structure on the cost efficiency has discussed in few literatures

(Belkhaoui, Lakhal, Faten and Hellara, 2014). When there is a more concentration on

a particular industry, then it is caused to an increase in competition and finally to

24

increase in the operational expenses. As per above study there is a significant effect

of market concentration on the cost efficiency strategy. But due to more competition

within a particular industry, income generation is becoming low and it would grounds

to decrease in efficiency. The hypothesis developed for the concept as follows;

H3 - Market Concentration negatively affect to the cost efficiency strategy

The research conducted by Christensen and Montgomery (1981) shows that the

increase in market structure will cause to a decrease in the degree of diversification of

the banks. In addition to that a few previous researches show that banks adopt a

strategy of strong diversification when the market is more competitive, that means

when there is a low concentration (Belkhaoui, Lakhal, Faten and Hellara, 2014).

Since the increased competition generally destroys the profitability of banks, the

banks adopt a diversification strategy to maintain profitability. Under these

conditions it is expectable that in case of market concentration banks are likely to

specialize in a limited number of activities, in general terms low diversification of

assets of the bank. So the research will test following hypothesis;

H4 - Market Concentration negatively affect to the diversification strategy

Some authors (Hellmann et al., 2002; Beck et al., 2006) show that the relationship

between risk-taking-strategy on the other hand credit risk and profitability of the

banks are unstable. But with regard to banking industry, the decrease in the

performance of the banks is mainly due to the increased in credit risk as failure of

borrower to meet its contractual obligations in a timely manner. So this will lead to

following hypothesis;

25

H5 – Risk taking strategy negatively affect bank performance

As explained in efficient structure theory, effective cost management will direct to

increase in the profitability level, because of reducing the cost incurred. Cost

efficiency is one of the strategies that can be followed by the banks in order to

enhance the performance of banks while focusing on taking the best advantages from

the products and services provided. According to Belkhaoui, Lakhal, Faten and

Hellara, 2014; Mugume, 2006 there is a positive relationship between cost efficiency

and bank performance. Therefore the following hypothesis is formulated;

H6 – Cost efficiency strategy positively affect bank performance

Generally, diversification is needed when gain from such strategy offset the cost

incurred for implementation. Notwithstanding the fact that it may wipe out the value

of the firm, diversification is a vital strategic choice which is taken by managers.

Banks are permitted to enlarge the scope of their activities beyond the traditional role

of financial intermediation. They are then able to decrease the average financing cost

through a combination of several different funds. Diversification could destroy firm

value (De Long, 2001). The negative effect of diversification on firm performance

can be explained through the agency costs associated with debt (Hadlock et al., 2001).

It should be noted that regardless of the lack of a compromise on the effects of

diversification the general trend in the literature suggests that diversification destroys

firm value (Belkhaoui, Lakhal, Faten and Hellara, 2014). So the study formulates the

following hypothesis;

H7 – Diversification strategy negatively affect bank performance

3.7 Data Collection Techniques

The research data are collected from the secondary sources such as annual reports of

the banks. Financial information for five years begins with 2009 to 2013 is extracted

from the annually audited financial statements and other required information is

collected from the websites of banks.

3.8 Data Analysis and Model Specification

The study basically focuses on identifying the direct and indirect relationship between

market structure and bank performance, effect of the market concentration on the

strategic choices such as risk taking strategy, cost efficiency and diversification and to

identify the relationship between those strategies with the bank performances. For

that purpose following regression models has been specified.

I

f

ROAit = ß1 + ß(mc)MCt+ ß(cr)CRit + ß(eff)CEffit + ß(div)DIVit + Uit

n order to identify the effect of market concentration on the strategic choices, the

ollowing models have been developed.

CRit = ß2 + ß(mc)MCt+ Uit

CEffit = ß3 + ß(mc)MCt+ Uit

DIVit = ß4 + ß(mc)MCt+ Uit

ROEit = ß1 + ß(mc)MCt+ ß(cr)CRit + ß(eff)CEffit + ß(div)DIVit + Uit

26

27

Where ROA is the ratio of bank i at the end of the year t; MC is the market

concentration at the end of year t; CR is the credit risk at the end of year t; CEff is the

cost efficiency at the end of year t; DIV is the diversification at the end of year t of

bank i. The direct effect can be identified as the effect of market concentration and

strategic choices (Credit risk, cost efficiency and diversification) on bank

performance. The indirect effect is the effect of market concentration on bank

performance via the strategic choices, which are initially identified using the effect of

market concentration on strategic choices and then multiply those effects with the

strategic choices on bank performance.

3.9 Chapter Summary

The methodology chapter is developed to attain the research objectives in order to

address the research problems. This chapter discussed the research design,

operationalization, population and sample selection, conceptualization, hypothesis of

the study, data collection techniques and the model specification and data analysis

techniques. Results and conclusion of the study will be discussed under the next

chapters.

28

CHAPTER IV

ANALYSIS AND DISCUSSION

4.1 Chapter Introduction

This chapter focuses on the collection of data, data analysis and also discusses the

findings from the analysis. In addition to that this chapter includes assessing the

assumptions with relate to the ordinary least square method and testing of the

hypotheses of the study while achieving the mentioned objectives as in the chapter

one.

4.2 An Overview of the Analysis

The required data for the study obtained from the annual reports of each bank and

covering five years. To measure the performance of the banks the research has used

the return on assets ratio (ROA) and return on equity (ROE) where those are

calculated using the profit after tax and average total assets or average total equity of

each bank.

Credit risk is calculated by using the non-performing loans and advances (NPL) ratio

and to obtain the non-performing loan ratio, the research has obtained non-performing

loans of each bank and the total loans and advances of the banks and then dividing the

non-performing loans from the total loans and advances.

Market structure of banks can be identified as the market concentration of the banks.

The market concentration is calculated by using the Herfindahl Hirschman Index

(HHI), eliminating the effect of market share. To come up with the ratio, obtained the

percentages of loans and advances of each bank are divided among the various

29

industries and that is multiplied by the market share which is arrived by dividing the

total deposits of the bank by the total deposits of the banking industry.

The cost efficiency is the ratio between operating expenses and the income of the

banks. So collected the data with relate to the revenue, total expenses and interest

expenses and arrived with the cost efficiency ratio.

To calculate the diversification the research has used the Herfindahl Hirschman Index

of assets and to arrive at the figure, obtained the combination of the assets of the bank

and split among the assets relate to the loans and advances, fixed assets, other interest

earning assets and non-interest earning assets and obtained the HHI of assets.

4.3 Data Analysis Method Used

To find the relationships, study has used the correlation and to measure the direct and

indirect effect of the independent variables to the dependent variables study used

regression analysis.

4.4 Descriptive Statistics

Descriptive statistics is the discipline of quantitatively describing the main features of

a collection of information, or the quantitative description itself (Dodge, 2003). In

descriptive statistics central tendency and dispersion measures are used to describe the

dataset. Central tendency include mean, median and mode, while the measures for

dispersion include standard deviation, variance, and distribution measures includes

skewness and kurtosis. Table 02 represents the descriptive statistics for the sample.

30

Table 02: Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

ROA 80 0.0001 0.0213 0.0126 0.0051

ROE 80 0.0054 0.4292 0.1768 0.0735

CR 80 0.0025 0.3352 0.0516 0.0550

CEff 80 0.1487 1.1091 0.3598 0.1715

MC 80 0.0010 0.6630 0.0755 0.1492

DIV 80 0.3704 0.6164 0.4744 0.0568

As in the table above (Table 02) the number of observations included in the regression

analysis is eighty observations with two dependent variables; return on assets and

return on equity and four independent variables; market concentration, credit risk,

cost efficiency and diversification. The minimum value is the lowest value with relate

to the variables and maximum is the highest value of mentioned variables. The mean

value is the measurement of central tendency where it represents the average value of

the above variables. According to the statistics it can be observed that the minimum

return on assets is 0.01% whereas the maximum is 2.13%. But compare to the return

on assets, return on equity of the banks is having the higher ratio and the average is

also indicates a higher value of 17.68%. The credit risk, market concentration and

diversification respectively are having the ratio of 5.16%, 7.55% and 47.44%. Even

though the maximum value of the cost efficiency is 110.91%, due to the lower ratio of

one of the bank the mean has decreased to 35.98%.

The standard deviation measures the spread of the observations. The higher the value

of standard deviation, the spread of the observations is also higher. Except cost

efficiency and market concentration ratio, the return on equity, credit risk and

31

diversification are having smaller spread whereas the return on assets is having the

smallest variance of 0.0051 in the observations.

4.5 Testing the Normality

In order to identify the observations that have the unusual values in the dependent

variables, the study has tested the normality and according to the testing, identified

that the return of assets of some of the banks has the abnormal ratio when compared

to the return of assets of the other banks. After removing the unusual ratios related to

return on assets, again tested the normality of the observations in the sample. The

sample is normally distributed means the Shapiro-wilk value should be approximately

one and the Shapiro-wilk value for return on assets of this model is 0.96 which

indicates that the sample is normally distributed.

4.6 Testing the Ordinary Least Square Assumptions

There are several assumptions that should be satisfied in order to have better results in

the analysis. Such as parameters of the regression should be linear, homoscedasticity

of the error term, no perfect multicollinearity, no autocorrelation between disturbance

terms, zero covariance between error term, variability in the independent variables,

number of observations should be greater than the number of parameters etc.

When considering the regression model of the study, there are eighty variables which

are more than the number of parameters. The correlation table (Table 03) shows that

there are no significant correlations among the independent variables. Therefore it

can be concluded that there is no perfect multicollinearity in this model.

32

Table 03: Correlation between the Variables

ROA ROE CR CEff MC DIV

ROA 1

ROE 0.69512 1

CR -0.16674 -0.25851 1

CEff -0.60417 -0.56083 -0.09652 1

MC 0.07165 0.16112 -0.00733 -0.02376 1

DIV 0.29658 0.32020 -0.18733 -0.42335 -0.09392 1

To test the homoscedasticity of the error term, performed the park test and ensured

that the disturbance term is normally distributed. The graph (Graph 01) below shows

that the disturbance term is normally distributed and there is the homoscedasticity in

the regression model.

Graph 01: Testing Homoscedasticity

33

Next assumption is to ensure that there are no any correlations between the

disturbance terms of the model. To test the assumption of autocorrelation, this study

has used the Durbin Watson value. As in the model summary (Table 04) the Durbin

Watson value in the model one, ROA model is 1.695 and in the model two, ROE

model the Durbin Watson value is 2.043 which very close to the benchmark value 2.

Table 04: Model Summary

ModelDependent

VariableR R Square

Adjusted R

Square

Std. Error of

the Estimate

Durbin-

Watson

1 ROA 0.64735 0.41906 0.38808 0.00400 2.04334

2 ROE 0.65956 0.43502 0.40489 0.05668 1.69532

4.7 Correlations

Correlation measures the relationship between two variables. Generally the results of

correlation explain using correlation coefficient. Correlation coefficient is a measure

of the linear correlation between two variables, giving a value between +1 and −1

inclusive, where 1 is total positive correlation, 0 is no correlation and −1 is total

negative correlation. As explained earlier in this study, correlation analysis has used

to find out the interrelationships between the variables such as return on assets,

market concentration, credit risk, cost efficiency and diversification. The results

obtained from statistical analysis are presented in the correlation table (Table 03).

As in the table 03, there is a negative relationship between return on assets and credit

risk and cost efficiency. The relationships show that there are weak negative

relationships between return on assets and credit risk whereas medium negative

34

relationship between cost efficiency. The relationship between return on equity and

credit risk also shows a weak negative relationship whereas with cost efficiency there

is a medium negative relationship.

Cost efficiency and credit risk show that there is a weak negative relationship of the

banks. And also there are weak negative relationships between market concentration

& credit risk, market concentration & cost efficiency and market concentration &

diversification. According to the correlation table, it shows that there is a weak

negative relationship between diversification & credit risk, a medium negative

relationship between diversification & cost efficiency and a weak positive relationship

between diversification and bank performance in both ROA and ROE models.

4.8 Regression Analysis

This paper has performed a multiple regression analysis as discussed in the previous

chapters for the data collected for five years from 2009 to 2013 to analyze the direct

and indirect effect of market structure and strategic choices; credit risk, cost

efficiency and diversification to the bank performance. The results obtained from the

analysis are given below.

As per the model summary table 04, in the model one R square is 0.419 which

indicates the explanatory power of the independent variables to the dependent

variable. It indicates that 42% variation of the performance of the banks as measured

using return on assets, is explained by the selected independent variables; market

structure, credit risk, cost efficiency and diversification. The model two is having the

R square of 0.435 and it indicates that the 44% variation of the performance of the

banks as measured using return on equity is explained by the independent variables

mentioned earlier.

35

The adjusted R square from model one and two respectively are 0.388 and 0.405

which indicate how far the independent variables will explain the dependent variable

when another variable is added to the model. Standard error of the estimate is simply

the standard deviation. This explains how far the mean of the selected sample

deviates from the actual mean of the population. According to table 04, the standard

errors of the estimate respectively from two models are 0.004 and 0.056 which

represent a minimum value. That means the actual mean only have variance of 0.4%

from the sample mean in the model one, return on assets model and when it comes to

the model two 5.6% variance of sample mean from the actual mean.

Table 05: ANOVA Table

Model F Value Significant Level

ROE 14.43690 0.00000

ROA 13.52533 0.00000

The regression sum of square or explained sum of square explains how much

variability is accounted for by the regression model which is the fitting of the least

squares line. According to the results obtained from the regression models developed

in this paper it is found that that the regression-sum of square is 0.186 in the ROE

model and 0.0009 in the ROA model. Hence, it can be identified that the ROE model

is more reliable that ROA model since it has explained more variability. The residual

sum of square tells how much variability is unexplained for by the regression model

used. The residual sum of square of these models respectively in ROE and ROA

models are 0.241 and 0.0012. Total sum of square is the summation of both

regression sum of square and residual sum of square. According to the results, it can

be identified that the percentage that can be explain by using the independent

variables is somewhat low in two models.

36

Degree of freedom of regression is four which is equal to the number of predictors in

the model, degree of freedom of residual is one hundred five which is the amount

obtained from deducting number of predictors and intercept from the number of total

observations. When it comes to the mean squares, those are arrived by dividing sum

of squares from the degree of freedom.

F value is the measure of the overall significance of the model that is obtained by

dividing the regression mean sum of square from the residual mean sum square. It is

found that the F value of ROE regression model is 14.437 and the significant level is

1% and ROA regression model is 13.525 and the significant level is 1%. So it can be

mentioned as the overall models are significant at 1% level.

The coefficient of each of the variable in the model with beta value and the standard

error value is mentioned in the coefficient table (Table 06). Regression model

coefficients matrix contain essential information for interpreting the regression

analysis. Because of the matrix includes the significant levels of the dependent and

independent variables of the model. The interpretation has indicated as below.

Table 06: Coefficients

Model Beta Std. error t - ValueSignificant

Level

ROA

ROA – Constant 0.02056 0.00510 4.03371 0.000

CR -0.02123 0.00852 -2.49187 0.015

CEff -0.01872 0.00297 -6.30916 0.000

MC 0.00189 0.00304 0.62171 0.536

DIV -0.00052 0.00912 -0.05666 0.955

37

ROE

ROE – Constant 0.25941 0.07215 3.59525 0.001

CR -0.40946 0.12061 -3.39482 0.001

CEff -0.24521 0.04201 -5.83742 0.000

MC 0.07312 0.04308 1.69724 0.094

DIV 0.04466 0.12913 0.34585 0.730

According to the above table (Table 06), in the ROA model the constant is 0.0206

which shows that the least square line touches the ordinate axis at a value of 0.0206

and in ROE model it is 0.259. Further it says that the given the value of independent

variables zero, the value of expected return on assets is 0.0206 and with relate to the

return on equity it is 0.259.

Beta in the un-standardized coefficient of each of the variable is the slope of those

variables. Further, it can be explained as in model one, for one unit of increase in the

independent variables; credit risk, cost efficiency and diversification the return on

assets that mean the performance of the banks has reduced by respectively by 0.0212,

0.0187 and 0.0005 whereas for one unit increase in the market concentration will

CRCR - Constant 0.05183 0.00694 7.46929 0.000

MC -0.00270 0.04171 -0.06478 0.949

CEffCEff - Constant 0.08291 0.03920 2.11478 0.038

MC -0.02067 0.09848 -0.20989 0.834

DIVDIV - Constant 0.47714 0.00714 66.85931 0.000

MC -0.03575 0.04290 -0.83319 0.407

38

cause to increase the performance of the banks by 0.0018. According to the model

two, one unit of increase in credit risk and cost efficiency have caused to reduce the

performance of the bank which is calculated by using return on equity respectively by

0.409 and 0.245 whereas increase in the market concentration and diversification have

resulted in the increase in the return on equity correspondingly by 0.073 and 0.045.

According to the model three; one unit increase in the market concentration has

caused to decrease the credit risk by -0.0027 and model four; cost efficiency model

shows that one unit increase in the market concentration will decrease the cost

efficiency by 0.02067 and as per model five; diversification model, it is clear that one

unit increase in the market concentration will decrease the diversification by 0.03575.

Standard errors provide a measure of how much should expect the given the sample

coefficient to vary under the assumption of the null hypothesis. According to the

standard errors mentioned in the table (Table 06), correspondingly in model one and

model two, the credit risk was vary in the repeated sampling only 0.85 percent & 12

percent, cost efficiency was 0.29 percent & 4.2 percent, market concentration was

0.30 percent & 4.31 percent and diversification 0.91 percent & 12.91 percent. The

results show that the standard errors are very smaller as it indicates smaller variance

in the repeated samples.

‘t–value’ indicates the individual significant to the regression model from the

independent variables. Credit risk is having absolute t-value of 2.492 in ROA model

and in ROE 3.395 in ROE model, which is significant at 1% level to the regression

model. The cost efficiency is having the absolute t-value of 6.309 in the ROA model

and 5.837 in the ROE model, where it is more than two which is the benchmark value

and it is significant at 1% level. When it comes to the market concentration, it is

having the absolute t-value respectively of 0.622 and 1.697 in ROA model and ROE

39

model. There in ROE model the t-value is closer 2 of benchmark value and it is

significant to the regression model at 10% level. The diversification variable is

having correspondingly in ROA model and in ROE model 0.057 and 0.346 of

absolute t-value that indicates lower value than the benchmark value and it is not

significant to the regression model.

In order to identify the direct and indirect effect of market concentration on each

strategy, the study has run a regression and identified the effect of market

concentration on risk taking strategy, cost efficiency strategy and diversification

strategy (Table 06) and again the study has run a regression to identify the direct

effect of market concentration on strategic choices (Credit risk, cost efficiency and

diversification) and then identify the indirect effects of market concentration on the

bank performance (Table 07). Even though the market structure is not significant to

the strategic choices model, there are negative effects of 0.0027, 0.0207 and 0.0358

respectively to the risk taking strategy, cost efficiency strategy and diversification

strategy from market concentration.

The summary of results from regression analysis and the conceptual framework with

the direct and indirect effects are given below.

Table 07: Summary of Causal Effects

Model Direct Effect Indirect Effect Total Effect

MC – ROA 0.00187 -0.00001 0.00186

MC – ROE 0.07316 -0.00002 0.07314

MC – CR -0.00270 0.00000 -0.00270

MC – CEff -0.02067 0.00000 -0.02067

MC – DIV -0.03575 0.00000 -0.03575

40

CR – ROA -0.02123 0.00000 -0.02123

CR – ROE -0.40946 0.00000 -0.40946

CEff – ROA -0.01872 0.00000 -0.01872

CEff – ROE -0.24521 0.00000 -0.24521

DIV – ROA -0.00052 0.00000 -0.00052

DIV – ROE 0.04466 0.00000 0.04466

Market Structure Strategic Choices Bank Performance

Figure 02: Conceptual Framework with direct and indirect effect

4.9 Hypotheses Testing

H1 – Market Concentration positively affect to the bank performance

As per the analysis (Table 07), there is a positive effect of market concentration on

bank performance in both models; return on assets and return on equity respectively

0.00186 and 0.07314. Market concentration is not a significant variable in ROA

model, but it is a significant variable in the ROE model. Thus the results of the

41

analysis have caused to accept the alternative hypothesis based on the results obtained

from return on equity model.

The correlation table (Table 03) of the overall model shows that there is a positive

relationship (0.0717 and 0.1661) between market concentration and the performance

of the banks, which is arrived from assessing the relationship between Herfindahl-

Hirschman Index and the return on assets and return on equity. To achieve the

objectives stated in the previous chapters it is important to identify the relationship

between the bank performance and the banks with low concentration, moderate

concentration and high concentration separately. The value below 0.1 represents the

low concentration, 0.1 to 0.18 indicates the moderate concentration and more than

0.18 shows the high concentration according to the index.

The following table (Table 08) shows the categorization of the banks in the selected

sample based on the market concentration.

Table 08: Categorization of banks based on HHI

Low

Concentration

Moderate

Concentration

High

Concentration

Sampath Bank Commercial Bank People's Bank

DFCC Wardhana Bank Deutsche Bank

Hatton National Bank Axis Bank

Seylan Bank Nations Trust Bank

Habib Bank Limited Pan Asia Bank

Bank of Ceylon Standard Chartered Bank

Indian Bank State Bank of India

Public Bank

42

From the analysis it was found (Table 09, 10 and 11) that there is a medium positive

relationship (-0.5677) between market concentration with low market concentration

and a weak positive relationship (0.3051) between market concentration with high

concentration and the bank performance whereas negative relationships between bank

performance and market concentration with moderate market concentration (-0.5427),

when the performance is measured using return on assets. The relationships with

return on equity show a medium positive relationship (0.6228) with low

concentration, a weak negative relationship (-0.4133) with medium concentration and

a weak positive relationship (0.1103) with high concentration.

H2 - Market Concentration negatively affect to the risk taking strategy

As per the regression analysis (Table 07), there is a negative effect (-0.0027) of the

market concentration on the risk taking strategy which is not significant and since

there is a negative effect, it has caused to reject the null hypothesis and accept the

alternative hypothesis developed using the previous literatures.

Further, this paper has identified the relationship of market concentration with low

HHI, Moderate HHI and high HHI with the risk taking strategy that means with the

credit risk. When it comes to the banks with low concentration (Table 09, 10 and 11),

there is a weak positive relationship of 0.1199 with credit risk. And also there was a

strong positive relationship which is 0.7719, between market concentration with

moderate HHI and the risk taking strategy of the banks. But with the high market

concentration, there is a negative relationship of 0.3691 (Table 11) between risk

taking strategy and market concentration.

In Sri Lankan context, with low and moderate market HHI, there is a positive

relationship between market concentration and the risk taking strategy because the

43

banks are not focusing mainly on few industries instead they are focusing on

developing industries such as tourism and agricultural industries. Therefore the credit

risk is somewhat high as if those industries are in a recession. But when there is a

high concentration, the credit risk is low because the banks provide the loans and

advances to the well-known customers.

Table 09: Correlations (Banks with low HHI)

ROA ROE CR CEff MC DIV

ROA 1

ROE 0.993376 1

CR -0.638338 -0.548652 1

CEff 0.592599 0.629520 0.029459 1

MC 0.567683 0.622828 0.119852 0.898853 1

DIV -0.110637 -0.219580 -0.693234 -0.599590 -0.669748 1

Table 10: Correlations (Banks with moderate HHI)

ROA ROE CR CEff MC DIV

ROA 1

ROE 0.637115 1

CR -0.571563 -0.583318 1

CEff -0.299130 -0.507041 0.469279 1

MC -0.542698 -0.413270 0.771916 0.391291 1

DIV 0.322248 0.270456 -0.371209 -0.592071 -0.190561 1

44

Table 11: Correlations (Banks with high HHI)

ROA ROE CR CEff MS DIV

ROA 1

ROE 0.745024 1

CR 0.011463 0.112076 1

CEff -0.671017 -0.664229 -0.324505 1

MS 0.305085 0.110268 -0.369146 -0.354224 1

DIV 0.218385 0.352055 -0.086904 -0.355831 0.341865 1

H3 - Market Concentration negatively affect to the cost efficiency strategy

The table 07 emphasis there is a negative effect of market concentration on the cost

efficiency strategy which is significant (-0.02067) to the model and therefore the

alternative hypothesis also can be accepted since it is said that the market

concentration has a negative effect to the cost efficiency strategy.

According the correlations of the overall model (Table 03), there is a weak negative

relationship (-0.0237) between market concentration and the cost efficiency strategy

of the banks in Sri Lanka. Since it is not much accurate to consider all the banks in

the sample as one when there are different concentrations levels, this paper basically

identified three relationships between market concentration and cost efficiency

strategy. As per the study, the research has identified there is a significant positive

relationship (0.8989 – Table 09) between the banks with low concentration and the

cost efficiency strategy of those banks. The banks with moderate concentration also

show a weak positive relationship (0.3913) between the market concentration and cost

efficiency strategy (Table 10). The main reason for that is, when the bank is not

45

focusing more on a particular industry to provide the loans and advances then the

operating expenses have reduced where they should not follow up the customers to

pay the installments.

But for the banks with high concentration the relationship (Table 11) with the cost

efficiency is weak negative (-0.3542) because when the banks were focusing more on

a specific industry, the bank should pay more attention collect the loan installments

and the interest income since the banks are depending only on that particular industry.

Therefore the high level of market concentration negatively affect to the cost

efficiency strategy with relate to the Sri Lankan scenario whereas the banks with low

and medium concentration positively affect the cost efficiency strategy of the banks.

This has proven the established hypothesis in the past literatures.

H4 - Market Concentration negatively affect to the diversification strategy

As per the direct and indirect effects (Table 07), there is a negative effect of market

concentration to the diversification strategy (-0.03575) whereas it is not significant to

the model. Even though the effect is not significant, since there is a negative effect

the hypothesis can be accepted under this scenario.

The correlations (Table 03) show that there is a weak negative relationship (-0.0939)

between the market concentration and diversification strategy of the banks in Sri

Lanka. As it is not concern about the level of market concentration of the banks, this

paper has again identified the relationship between low, medium and high market

concentration with the diversification strategy of the banks in Sri Lanka using the

selected sample (Table 09, 10 and 11).

46

According to that analysis, there is a negative relationship between the banks with low

and medium market concentration and diversification strategy respectively -0.66975

of medium negative relationship and -0.1906 of weak negative relationship where it

proves that the market concentration has the negative effect on the diversification

strategy of the banks. But when it comes to the banks with high level of market

concentration, it is somewhat different because there is a medium positive relationship

of 0.3419 with the diversification strategy of the banks in Sri Lanka. But when

considering the overall relationship, that indicates a negative relationship between the

market concentration and the diversification strategy.

H5 – Risk taking strategy negatively affect bank performance

The results of the study (Table 07) show that there is a significant negative effect of

risk taking strategy on bank performance in both models; return on assets (-0.02123)

and return on equity (-0.40946). Thus the results of the analysis have caused to reject

the null hypothesis where it proves the hypothesis developed using the past literatures.

When it comes to the relationship between credit risk and bank performance, it shows

(Table 03) that there is a weak negative relationship between the risk taking strategy

of the banks in Sri Lanka and the performance of the banks. According to the model

one which is developed using the return on assets, it is -0.1667 and while with return

on equity, the relationship is -0.2585 where it rejects the null hypothesis and accepts

the alternative hypothesis.

H6 – Cost efficiency strategy positively affect bank performance

Here also there is a negative effect of cost efficiency on bank performance in both

return on assets and return on equity models respectively -0.01872 and -0.24521

47

(Table 07) which is significant and where the results have affected to reject the

alternative hypothesis developed using past literatures.

According to the results of the study it is found that there is a medium negative

relationship of -0.6042 and -0.5608 (Table 03) between the cost efficiency strategy of

the Sri Lankan banks and the performances of those banks as it is measured

correspondingly using return on assets and return on equity. Since most of the banks

in Sri Lanka are having low to moderate market concentration, that means they are

focusing on the new customers to offer the loans and advances and even though the

profitability has been increased the operating cost is also increased. Therefore the

cost efficiency is having a negative relationship with the bank performance.

Thereby, the hypothesis was rejected from the study.

H7 – Diversification strategy negatively affect bank performance

Diversification strategy is also having a negative effect on the bank performance in

return on assets (-0.00052) and a positive effect on performance in return on equity

(0.04466) model (Table 07). But the effects for both models are not significant.

Thus the effect of diversification for return on equity is higher than the effect on

return on assets; it is suitable to reject the alternative hypothesis.

The correlations (Table 03) of the overall model shows that there is a weak positive

relationship of 0.2966 and 0.3202 between the diversification strategy of the banks in

Sri Lanka and the performance of the banks when the performance is measured

respectively by using return on assets and return on equity. Therefore the hypothesis

is rejected according to the results of the analysis.

48

4.10 Chapter Summary

This chapter explained how the data was collected and analyzed using regression and

correlation. Then the results of the testing the ordinary least square assumptions

including the normality assumption and discussed the results of the descriptive

statistics, results of the correlations, regression analysis and finally tested the

hypothesis developed. The summary of the results obtained are given in the table

(Table 12) below.

Table 12: Summary of Results

Hypotheses Accepted or

rejected

H1 – Market Concentration positively affect to the bank performance Accept

H2 - Market Concentration negatively affect to the credit risk strategy Accept

H3 - Market Concentration negatively affect to the cost efficiency Accept

H4 - Market Concentration negatively affect to the diversification Accept

H5 – Risk taking strategy negatively affect bank performance Accept

H6 – Cost efficiency strategy positively affect bank performance Reject

H7 – Diversification strategy negatively affect bank performance Reject

49

CHAPTER V

SUMMARY AND CONCLUSION

5.1 Chapter Introduction

The purpose of this study was to develop and analysis a conceptual model of bank

performance based on two different approaches. The first one is based on the market

power theory that suggests the market structure or market concentration affects

performance of the banks and the second one refers to theory of strategic management

which considers the strategic choices such as risk taking strategy, cost efficiency and

diversification as the determinants of the performance of the banks.

5.2 Summary of Results

In order to fulfill the established objectives this paper has performed a regression

analysis and a correlation using several models. The conclusions relating to the

objectives will be discussed in this chapter.

Objective 01 – To measure the direct and indirect effect of market concentration on

the bank performance

The results of the study demonstrate that there is a positive effect of the market

concentration on the bank performance where it indicates an insignificant effect to the

return on assets while a significant positive impact to the return on equity. As in the

past studies (Mirzaei, Moore & Liu, 2001 and Belkhaoui, Lakhal, Faten and Hellara,

2014), there was a significant positive effect of the market concentration on the bank

performance. Also in contrast to the Sri Lankan banks, there is a positive effect

which is significant because increase in the market concentration will focus on the

specific customers who are well known and wealthy. Then the banks have the ability

50

to lend more money and earn more interest income from them rather than focusing on

poor people.

Objective 02 – To identify the effect of strategic choices (Credit risk, cost efficiency

and diversification) on bank performance

As per the findings there is a negative effect of the credit risk on the bank

performance in Sri Lanka, because when there are defaults of the lending by the bank

it is finally affect to the profitability of the banks. The past studies (Belkhaoui,

Lakhal, Faten and Hellara, 2014) were also proved that there is a negative effect of

the risk taking strategy on the bank performance. So the banks must continuously

comply with the rules and regulations given by the Central Bank of Sri Lanka and

maintain the required rates to manage the credit risk.

The results indicate that there is a negative impact of the cost efficiency strategy on

the bank performance where it is statistically insignificant and it has proven the past

studies. Therefore the management of the banks should improve the cost efficiency

by having the competitive advantage by decreasing the interest rates and improve the

financial stability of the banks within the industry.

As per the analysis the effect of diversification strategy on the bank performance is a

negative effect which is insignificant where in the past literatures also have proven.

Normally the assets base of the banks should have well diversified among the various

types of assets such as loans & advances, fixed assets and other non-interest bearing

assets etc. It is necessary to have the required amount of fixed assets to run the

operations of the banks and the loans and advances should also well diversify among

the various industries.

51

Objective 03 – To measure the relationship between market concentration and the

bank performance

To identify a clear relationship between market concentration and the performance of

the banks, the study has focused on three types of concentration which includes low,

medium and high concentration. According to the findings it is obvious that there is a

positive relationship with low concentration and high concentration where as a

negative relationship with the banks with medium concentration. When there is a low

concentration that means the banks are focusing on most of the industries in a similar

manner. Therefore the profitability of the banks decreases due to a larger customer

base with low interest loans advances and due to the high operating cost. When there

is a high concentration, which means the banks are focused more on specific

industries. So the operating expenses attached with given loans are low and the banks

have the ability to charge the higher interest rate on those loans.

Table 13: Relationship between market concentration and bank performance

Market Concentration Relationship Supporting Literature

Low Concentration Positive Mugume. A. ,2006

Medium Concentration Negative More and Marton, 2003

High Concentration Positive Jeon & Miller, 2005

Objective 04 –To measure the relationship between strategic choices and bank

performance

There is a negative relationship between credit risk and bank performance and also

with cost efficiency also there is a negative relationship. But when it comes to the

diversification the relationship shows a positive with the bank performances.

52

Objective 05 –To measure the relationship between market concentration and

strategic choices (Credit risk, cost efficiency and diversification)

When considers the Sri Lankan banking industry as a whole, there is a negative

relationship between the market concentration and the risk taking strategy of the

banks. Further this paper has identified the relationship between market concentration

and risk taking strategy by isolating the banks as low concentration, medium

concentration and high concentration. According to the findings it is clear that there

is a positive relationship between the banks with low and moderate concentration

whereas a negative relationship with the banks with high concentration. When the

market concentration of the banks is increasing then the credit risk for them is

decreasing. With high concentration, the banks can provide the loans and advances to

the known customers rather than giving to the unknown customers with low

concentration. Hence the credit risk is low with high concentration.

Table 14: Relationship between market concentration and risk taking strategy

Market Concentration Relationship Supporting Literature

Low Concentration Positive No

Medium Concentration Positive No

High Concentration Negative Belkhaoui, Lakhal, Faten and Hellara,

2014

As per the findings of the study there is a negative relationship between the bank

performance and the cost efficiency strategy as a whole. But when consider the banks

separately as low, medium and high market concentration the results are significantly

different from the overall conclusion. It is with low concentration, there is a positive

relationship between market concentration while there is a negative relationship

between moderate and high market concentration and performance of the banks.

53

When the market concentration is increasing the cost efficiency decreases whereas

when the market concentration is decreasing the cost efficiency also decrease. The

main reason for that is the higher operating expense involve with the loans and

advances given to the customers of the banks. When there is a low market

concentration the number of loans is high and the operating cost is also high.

Table 15: Relationship between market concentration and cost efficiency

Market Concentration Relationship Supporting Literature

Low Concentration Positive No

Medium Concentration Negative No

High Concentration Negative Belkhaoui, Lakhal, Faten and Hellara,

2014

The results of the study show that there is a negative relationship between market

concentration and the diversification strategy as a whole. When the sample is

dividing as the low, medium and high market concentration, it can be identified that

there is a negative relationship between the diversification strategy with low and

medium concentration whereas a positive relationship between diversification and

high market concentration. Where the market concentration is increasing the

diversification is increasing and when the market concentration is decreasing the

diversification is increasing.

Table 16: Relationship between market concentration and diversification

Market Concentration Relationship Supporting Literature

Low Concentration Negative Belkhaoui, Lakhal, Faten and Hellara,

2014

Medium Concentration Negative Belkhaoui, Lakhal, Faten and Hellara,

2014

High Concentration Positive No

54

Objective 06 – To measure the effect of market concentration on strategic choices

(Credit risk, cost efficiency and diversification)

There is a direct effect of market concentration on strategic choices which are

negative but not significant. That means, when the market concentration is

increasing, it is not significantly affect in decrease of the credit risk, cost efficiency

and diversification strategies. Because of the market concentration is not the only

factor that affects to the strategies followed by the banks in Sri Lanka.

5.3 Conclusion

Finally, the results of the study are very much important to the banks in Sri Lanka, the

managers of those banks and the regulatory bodies also. The banks are very much

encouraged to pay more attention on their strategic choices to increase their

performances. In addition to that the banks must comply with the rules, regulations

and standards to reduce the credit risk and increase the cost efficiency. However the

findings show that the increasing market concentration is beneficial to the banks in Sri

Lanka because it allows banks to reduce the operating cost and reduce the default risk

while increasing their performances.

55

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Jeon, Y., & Miller, S. M. (2005). Bank Performance: Market Power or Efficient

Structure?

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Maudos, Joaquin;. (1998). Market structure and performance in Spanish banking

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MCB Bank Limited. (2009-2013). Annual Report. MCB Bank Limited.

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Móré, C., & Nagy, M. (2003). Relationship Between Market Structure and Bank

Performace.

Mugume, Adam;. (2006). Market Structure and Performance in Uganda's Banking

Industry.

Muharram, A., Matthews, S., & Kent. (2009). Market Power versus Efficient-

Structure in Arab GCC Banking.

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Nations Trust Bank. (2009-2013). Annual Report. Nations Trust Bank.

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People's Bank. (2009-2013). Annual Report. People's Bank.

Public Bank. (2009-2013). Annual Report. Public Bank.

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Seelanatha, Lalith;. (n.d.). Market structure, efficiency and performance of banking

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State Bank of India. (2009-2013). Annual Report. Standard Chartered Bank.

57

APPENDIXES

Data Set of the Analysis

Year Bank ROA ROE CR CEff MC DIV

2009 Commercial Bank 0.0143 0.1583 0.0536 0.2980 0.0245 0.4134

2009 DFCC Wardhana 0.0106 0.0975 0.0808 0.4023 0.0045 0.4320

2009 HNB 0.0162 0.1957 0.0403 0.3408 0.0056 0.4153

2009 People's Bank 0.0076 0.1973 0.0670 0.2856 0.0094 0.4269

2009 Sampath Bank 0.0142 0.1941 0.0802 0.3202 0.0134 0.4384

2009 Deutsche Bank 0.0027 0.1419 0.0276 0.7465 0.2430 0.3709

2009 HBL 0.0160 0.1856 0.0979 0.3011 0.0541 0.4302

2009 BOC 0.0060 0.1285 0.0586 0.2467 0.0106 0.4005

2009 Indian Bank 0.0161 0.2026 0.0380 0.3049 0.0090 0.4828

2009 Seylan Bank 0.0038 0.0617 0.3352 0.3742 0.0389 0.4163

2009 NTB 0.0074 0.1236 0.1073 0.3149 0.0683 0.4024

2009 PAB 0.0191 0.2172 0.1004 0.2874 0.1487 0.3746

2009 Public Bank 0.0127 0.2200 0.0425 0.4025 0.0058 0.5438

2009 Standard Chatered 0.0080 0.1374 0.0084 0.6152 0.0068 0.4083

2009State Bank of

India0.0108 0.1705 0.0168 0.3196 0.0038 0.4407

2009 Axis Bank 0.0141 0.1913 0.0035 0.3472 0.0151 0.4724

2010 Commercial Bank 0.0160 0.1787 0.0308 0.3342 0.6280 0.4263

2010 DFCC Wardhana 0.0095 0.0924 0.0776 0.3673 0.0476 0.4491

58

2010 HNB 0.0150 0.1745 0.0293 0.3976 0.0020 0.4376

2010 People's Bank 0.0102 0.2696 0.0528 0.3407 0.0248 0.4828

2010 Sampath Bank 0.0194 0.2459 0.0390 0.4060 0.0032 0.4918

2010 Deutsche Bank 0.0014 0.0528 0.0192 0.8102 0.0032 0.3861

2010 HBL 0.0183 0.2040 0.1073 0.2990 0.2195 0.4332

2010 BOC 0.0102 0.2401 0.0339 0.2537 0.0058 0.4183

2010 Indian Bank 0.0168 0.2018 0.0189 0.3236 0.0328 0.4882

2010 Seylan Bank 0.0087 0.1084 0.2436 0.4710 0.0411 0.3978

2010 NTB 0.0131 0.1942 0.0692 0.3835 0.0081 0.4229

2010 PAB 0.0137 0.1519 0.0360 0.3885 0.0437 0.4604

2010 Public Bank 0.0162 0.2578 0.0507 0.1903 0.3240 0.5398

2010Standard

Chartered Bank0.0093 0.1322 0.0148 0.6684 0.0055 0.4061

2010State Bank of

India0.0091 0.1480 0.0172 0.3429 0.0047 0.4855

2010 Axis Bank 0.0153 0.1915 0.0036 0.4130 0.0010 0.4845

2011 Commercial Bank 0.0198 0.2076 0.0236 0.4319 0.0066 0.4265

2011DFCC Wardhana

Bank0.0141 0.1367 0.0467 0.3615 0.0115 0.5110

2011 HNB 0.0161 0.1731 0.0306 0.3535 0.0278 0.4515

2011 People's Bank 0.0168 0.4292 0.0357 0.2957 0.6539 0.5102

2011 Sampath Bank 0.0178 0.2260 0.0380 0.3386 0.0660 0.5194

2011 Deutsche Bank 0.0021 0.0824 0.0164 0.6687 0.0153 0.4006

59

2011 HBL 0.0213 0.2367 0.1123 0.2865 0.0456 0.4432

2011 BOC 0.0149 0.3374 0.0210 0.2368 0.0389 0.4848

2011 Indian Bank 0.0154 0.1927 0.0212 0.3323 0.0521 0.4922

2011 Seylan Bank 0.0064 0.0677 0.2504 0.4847 0.1507 0.4461

2011 NTB 0.0150 0.1972 0.0381 0.3687 0.0077 0.4515

2011 PAB 0.0211 0.2578 0.0257 0.3323 0.0859 0.4843

2011 Public Bank 0.0167 0.2494 0.0483 0.1731 0.0040 0.5519

2011Standard

Chartered Bank0.0088 0.1230 0.0112 0.5980 0.0114 0.3704

2011State Bank of

India0.0073 0.1262 0.0163 0.4123 0.0075 0.4757

2011 Axis Bank 0.0160 0.1934 0.0026 0.3945 0.0137 0.4861

2012 Commercial Bank 0.0212 0.2086 0.0165 0.2135 0.0062 0.5661

2012DFCC Wardhana

Bank0.0116 0.1248 0.0459 0.2359 0.0094 0.5340

2012 HNB 0.0187 0.1844 0.0370 0.2654 0.6064 0.5060

2012 People's Bank 0.0142 0.3912 0.0280 0.2292 0.0048 0.5813

2012 Sampath Bank 0.0186 0.2341 0.0233 0.2422 0.0072 0.5470

2012 Deutsche Bank 0.0001 0.0054 0.0226 0.9876 0.0010 0.4541

2012 HBL 0.0167 0.2104 0.1101 0.2588 0.0941 0.4968

2012 BOC 0.0153 0.3164 0.0168 0.1895 0.0439 0.4998

2012 Indian Bank 0.0133 0.1719 0.0529 0.2899 0.1986 0.5014

2012 Seylan Bank 0.0117 0.1123 0.1492 0.3208 0.0440 0.5087

60

2012 NTB 0.0161 0.2112 0.0250 0.3157 0.0376 0.4546

2012 PAB 0.0167 0.2194 0.0329 0.2559 0.0352 0.6164

2012 Public Bank 0.0173 0.2440 0.0348 0.1487 0.0198 0.5655

2012Standard

Chartered Bank0.0081 0.1140 0.0146 0.5968 0.0216 0.3978

2012State Bank of

India0.0091 0.1572 0.0210 0.3800 0.3357 0.5008

2012 Axis Bank 0.0161 0.2029 0.0025 0.3354 0.0049 0.4890

2013 Commercial Bank 0.0187 0.1840 0.0388 0.1988 0.0034 0.5285

2013DFCC Wardhana

Bank0.0090 0.0956 0.0472 0.2258 0.0343 0.5324

2013 HNB 0.0147 0.1432 0.0428 0.2272 0.0065 0.5327

2013 People's Bank 0.0083 0.2278 0.0530 0.1727 0.0044 0.5969

2013 Sampath Bank 0.0099 0.1282 0.0560 0.2286 0.0067 0.5523

2013 Deutsche Bank 0.0004 0.0125 0.0228 1.1091 0.0132 0.5556

2013 HBL 0.0138 0.1845 0.0859 0.2860 0.0369 0.4762

2013 BOC 0.0108 0.2225 0.0320 0.1858 0.3264 0.4529

2013 Indian Bank 0.0104 0.1389 0.0898 0.2787 0.0442 0.5076

2013 Seylan Bank 0.0116 0.1137 0.1202 0.2601 0.0758 0.4735

2013 NTB 0.0162 0.2127 0.0357 0.3245 0.0420 0.4520

2013 PAB 0.0019 0.0277 0.0650 0.2421 0.0056 0.5181

2013 Public Bank 0.0154 0.2079 0.0334 0.1640 0.0033 0.5697

61

2013 Standard

Chartered

0.0064 0.0904 0.0122 0.5794 0.6630 0.3992

2013State Bank of

India0.0097 0.1543 0.0182 0.3409 0.0038 0.5185

2013 Axis Bank 0.0165 0.1853 0.0032 0.3272 0.0431 0.4851