Home > Financial Performance of the Malaysian Banking Industry: Domestic vs Foreign Banks

Financial Performance of the Malaysian Banking Industry: Domestic vs Foreign Banks

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Financial Performance of the Malaysian Banking Industry: Domestic vs Foreign Banks
Mamadou Lamarana Guisse
Submitted to the Institute of Graduate Studies and Research in partial fulfillment of the requirements for the Degree of Master of science in Banking and Finance Eastern Mediterranean University June 2012 Gazimağusa, North Cyprus

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Approval of the Institute of Graduate Studies and Research Prof. Dr. Elvan Yılmaz Director I certify that this thesis satisfies the requirements as a thesis for the degree of Master of Science in Banking and Finance. Assoc. Prof. Dr. Salih Katırcıoğlu Chair, Department of Banking and Finance We certify that we have read this thesis and that in our opinion it is fully adequate in scope and quality as a thesis for the degree of Master of Science in Banking and Finance. Assoc. Prof. Dr. Nesrin Özataç Supervisor Examining Committee 1. Assoc. Prof. Dr. Mustafa Besim 2. Assoc. Prof. Dr. Nesrin Özataç 3. Assoc. Prof. Dr. Salih Katırcıoğlu

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ABSTRACT
The aim of this study is to examine the performance of the Malaysian’s local banks and foreign banks, and compare their profitability in the financial sector. Profitability of commercial banks can be influenced by several factors, such as liquidity, credit, capital, operating expenses, and the size of the banks. Measuring the profitability in term of Return on Asset (ROA) and Return on Equity (ROE) for a panel of local and foreign banks can give a general idea about the effects of these factors to banking system. Some previous studies have been carried out in the same field such as the work of Sufian (2009) that investigates the factors influencing the profitability of the Malaysian banking industry. For this analysis, a panel regression methodology will be applied to investigate the performance of these commercial banks within Malaysian’s banking system empirically. Financial ratios are collected for a total of 8 (eight) local banks and 8 (eight) foreign banks, covering a period between 2005 and 2011. In addition, a comparative study will be carried out to show possible difference between the two categories of bank ownership from the perspective of performance and profitability. Keywords: Profitability, Asset-Liability management, Banking, Malaysia Bank Ownership.

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ÖZ
Bu çalışma, Malezya yerel ve yabancı bankaların finansal performanslarının karşılaştırılmasını amaçlamaktadır. Ticari bankaların karlılıkları bazı nedenlerden etkilenebilmektedir. Bu faktöreleri likidite, kredi, işletim harcamaları, banka b��y��kl��kleri diye sıralayabiliriz. Aktif getiri (ROA) ve sermaye ��zerinden getiri(ROE), Baz rasyolarını alarak bankacılık sistemine bu faktörlerin ne yönde etki ettiği araştırlımıştır.. Daha önce yaplılmış çalışmlarda örneğin Sufian(2009) banka karlılıkların etkileyen faktörler ��zerine çalışmalar yapmıştır. Analizde panel regresyon metodu kullanılarak ticari bankalrın ampirik olarak performansları incelenmiştir. Çalışmada 8 yerel 8 de yabancı banka kullanılmış bankalar sahiplik yapısı dikkate alınarak gloabal kriz ve performansları yön��nde bulgulara ulaşılmıştır. Anahtar kelimeler: Karlılık, Aktif-pasif yönetimi, bankacılık, Malezya Bankacılık sahiplik yapısı

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DEDICATION
To My Family and the Guinean Community in TRNC

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ACKNOWLEDGMENTS
First of all, I would like to thank God for assisting me in accomplishing this thesis, without him this study could not have seen the light of day. I also would like to thank Assoc. Prof. Dr. Nesrin Ozatac for her continuous support and guidance in the preparation of this study. Without her priceless supervision, all my efforts could have been limited. Besides that I extend my heartfelt thank to Assoc. Prof. Dr. Salih Katircioglu, Assoc. Prof. Dr. Mustafa Besim, Nigar Taspinar and to all other instructors in banking and finance department and my friends for their great support and help during my stay in Eastern Mediterranean University. I owe quite a lot to my family in particular to my Dad Thierno Mamadou Cire, my mom Aissata Diallo, my uncle Thierno Nabika Diallo and my brother EL. Mamadou Aliou Guisse who allowed me to travel all the way from Guinea to Cyprus and supported me all throughout my studies. I would like to dedicate this study to them as an indication of their significance in this study as well as in my life. .

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TABLE OF CONTENTS
ABSTRACT ......................................................................................................................iii ÖZ ..................................................................................................................................... iv DEDICATION………………………………………………………………………...…v ACKNOWLEDGMENTS ................................................................................................ vi LIST OF TABLES……………………………………………………………………....ix LIST OF ABBREVIATIONS…………………………………………………………....x 1 INTRODUCTION .......................................................................................................... 1 1.1 Historical Background ............................................................................................ 1 1.2 Aim of Study ............................................................................................................ 2 1.3 Research to find out .................................................................................................. 3 1.4 Structure of the Thesis ........................................................................................... 3 2 OVERVIEW OF MALAYSIAN BANKING SECTOR ................................................ 4 2.1 The 2008 Global crises ............................................................................................. 5 3 LITERATURE REVIEW ............................................................................................. 10 4 DATA AND METHODOLOGY .................................................................................. 15 4.1 Data ........................................................................................................................ 15 4.2 The Variables ......................................................................................................... 16 4.2.1 Dependent Variables ........................................................................................ 17 4.2.2 Independent Variables ..................................................................................... 18 4.3 Methodology .......................................................................................................... 20 4.3.1 Panel Unit root Test: ........................................................................................ 20

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viii 4.3.2 Proposed Model: .............................................................................................. 20 5 EMPIRICAL ANALYSIS AND RESULTS ................................................................ 22 5.1 Panel Unit Root Test Results: ................................................................................ 22 5.3.1 Regression Analysis Result of All Banks ........................................................ 26 5.3.2 Regression Analysis Result of Domestic Banks: ............................................ 28 5.2.3 Regression Analysis Result of Foreign Banks: ............................................... 28 5.4 Comparison between Domestic and Foreign Banks............................................... 29 CONCLUSION AND SUGGESTION ............................................................................ 32 REFERENCES ................................................................................................................ 34 APPENDICES ................................................................................................................. 38

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LIST OF TABLES
Table 2.1: List of licensed Malaysian commercial Banks…………….….….…….....7 Table 2.2: List of licensed Malaysian Islamic Banks……………………..…….……9 Table 4.1: Selected commercial banks and Ownership Structure…………………..16 Table 4.2: The variables measures and their notation…………………….…...……17 Table 5.1: Correlation matrix of variables: All Banks……...………………..……..24 Table 5.2: Correlation matrix of variables: Domestic Banks……………….………25 Table 5.3: Correlation matrix of variables: Foreign Banks………………….……...26

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x
LIST OF ABBREVIATIONS
BNM……………………………………….………..………….…Bank Negara Malaysia ROA………………………………………………….……………..……Return on Asset ROE………………………………………………….….………………Return on Equity CAR…………………………………………………..…………..…….Capital Adequacy ASQ……………………………………………….…………………..….…Asset Quality LQR……………………………………………………………....………..Liquidity Ratio EAR……………………………………………………………………………....Earnings LSIZE……………………………………………….…...Natural Logarithm of total asset E-VIEWS……………………………………………………………...Econometric views LLC………………………………………………………………..…Levin, Lin and Chu OLS………………………………………………………………..Ordinary Least Square VAR Model………………………………..…………….…Vector Autaregression Model

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Chapter 1
1 INTRODUCTION
1.1 Historical Background
The financial institution’s history is relatively close to that of the money, but trading started probably before the money has been invented. Therefore, the first form of transaction consisted of deposits of grain, goods and precious metal like gold that had to be kept in the Temples and other places that were considered as the ideal places for storing good items. The role played by financial institution is so important than that we cannot think about life without banks. The innovation and modernization of the banking sectors nowadays have made the banking system more secure and more comfortable for their customers, so that they can even do transactions through the internet and even their mobile phones. Commercial Banks as financial intermediaries accept deposits from savers and give loans to borrowers for investment and the spread between the interest rate paid to depositors and that charged to borrower is the profit or the interest income to the banks. They also provide some trading facilities like letter of credit, shipping guarantee, Banker’s acceptance, and so on. Faezah (2007) mentioned in his study that commercial banks have started being under the Central Bank of Malaysia, Bank Negara Malaysia ( BNM) control since 1959, two years after the Malaysian independence. With reference to the BNM (2012), Malaysian licensed financial institution has 25 commercial banks (constituted by 9 domestics banks and 16 foreign banks), 17 Islamic

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2 banks (constituted by 11 domestic banks and 6 foreign owned-banks), 5 International Islamic banks (all foreign owned), 15 investment banks (all domestic owned-banks), and 2 other financial institutions (also domestically owned-banks). According to the IMF (2004) report, over 90 percent of share of Malaysian banking in 1957 were held by foreign banks, but due to the some government policies against them, these percentages declined to 16.7 by 1997. In the last 3 decades, Malaysian banking sector has faced several financial crisis such as that of the period 1985-1986 in which some financial institutions went to bankruptcy because of default on loans, and 1987-1989 which are related to a high level of nonperforming loans of financial companies and small banks, in contrast, 1997-1998, and 2008 are the effect of the Asian crisis and Global financial crisis respectively. The Global financial crisis 2008 did not have its origin in Asia, but started in the United State, due to the lack of control of its financial downturn and transmitted to all financial institutions, Khoon and Mah-Hui (2010) studied the impact of the global financial crisis on the Malaysian economy which stated that the negative effect started in the last 3 months of 2008.
1.2 Aim of Study
A similar study was done by Sufian (2009) that examined the factors influencing bank profitability in developing Economy in the case of Malaysia, for the period 2000-2004 including 23 commercial banks (constituted by 10 domestically owned and 13 foreign owned banks).

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3 The present study aims to investigate the factors influencing bank profitability in Malaysia for the period 2005-2011 covering 16 major commercial banks (8 locally owned and 8 foreign owned). In order to examine these selected commercial banks profitability, we will use Return on Asset (ROA) and Return on Equity (ROE) which are considered as dependent variables. In the other hand, Capital Adequacy, Asset Quality, Management Efficiency, Liquidity and the Bank Size (Total Asset) are the independent variables.
1.3 Research to find out
The present study examines the profitability of 16 major commercial banks in Malaysia and the factors influencing their performance for the period 2005-2011. However, in order to figure out that, a number of questions have to be answered. Do local banks perform better than foreign banks in the above period or is it the inverse? During a period of financial crisis, which of the two kinds of owner banks is able to better deal with the crisis effect and perform more? If there is any difference between local and foreign banks performance, what is the reason? The response to these questions will be useful to Malaysian banking management, as well as to policies makers, in order to improve the financial institution performance.
1.4 Structure of the Thesis
From now till the end, this thesis will have the following structure: section 2 gives an overview of the Malaysian banking sector, section 3 focuses on the literature review related to previous studies, section 4 presents the selected data and methodology, section 5 explains the finding results, and at the end, section 6 will be the conclusion and suggestion for further study.

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Chapter 2 OVERVIEW OF MALAYSIAN BANKING SECTOR
Malaysian financial system has started since before its independence in 1957, however, in those periods, foreign banks were the only financial institution operating in the country. In contrast, domestic banks
1
waited until 1959 to start with the implementation of the Central Bank of Malaysia (Matthews and Ismail 2006). According to the BNM
2
, Malaysian financial institution is constituted by 25 commercial banks (9 domestically owned and 16 foreign owned banks), 16 Islamic banks, 5 international Islamic banks, 15 investment banks and 2 other financial institutions. Sufian (2009) pointed out in his study that, 10 domestic and 13 foreign banks constituted the commercial banks in 2004. Said and Tumin (2011) reported in their study that by 2008, Malaysian commercial banks were constituted by 9 local and13 foreign banks. The decline of the number of domestic banks is a result of banks merger in which they expect an improvement in their performance. For instance, the last bank merger is that between EON Bank and Hong Leong Bank on May 2011 (Ong, Teo, and Teh November 2011). Malaysian Financial institutions have experienced several crises since 1959, such as 1985-1986 and 1987- 1989 that were not brought from outside of the Malaysian banking system, in contrast, the Asian crisis 1997-1998, the dot.com bubble in 2001 and the Global Financial crisis in 2008 were brought from outside the country. In overall crises, Malaysian commercial
1 Domestic banks: public and private banks that are under the BNM control. 2 List of licensed Banking institutions in Malaysia:
http://www.bnm.gov.my/microsites/financial/0201_fi_list.htm

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5 banks suffered more deeply from, firstly, the Asian crisis which started in Thailand and the worst crisis in the Malaysian banking history (Khoon and Hui 2010), and secondly, the Global Financial crises in 2008 for which this study will focus in more detail.
2.1 The 2008 Global crises
The Global financial crises had its origin in the United State, which was a result of inequality and uncontrolled lending. Furthermore, from many years before 2008, financial institutions were giving mortgages to people who were relying on buying houses as that is considered as a good opportunity of investment, because of the expectation on their rising prices and also collateral in the case of default in the lenders point of view. Though, banks were lending as much as they could even borrow from other financial institutions in order to lend more, unfortunately, the default in mortgage made the house prices to fall and the financial institutions started going bankruptcy and it was the beginning of the crisis. The American’s economy started being hurt by the effect of the crisis by January 2008, followed by other developed countries like China, Japan and the European countries
3
. As Malaysia occupies the category of the developing countries, and also was relying heavy on trading with the US financial sectors and other developed countries within Asia. Thus, the country was affected by the contagious and the negative impact of the Global financial crisis to the Malaysian’s economy began in the last three months of 2008. Financial institutions suffered mostly from the stock market that fell down approximately to 50% compare to the previous year (KHOON and MAH-HUI 2010), the other financial activities were not much affected by the crisis. However, that was a
3 http://www.wikinvest.com/concept/2008_Financial_Crisis

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6 result of some positive changes made by the Malaysian government to the banking sectors after the Asian Financial crisis. Malaysia’s export
4
constituted the major sources of the country’s income, and the sector was the most impacted by the crisis due to the lack of external demand, resulting to a fall of 27.8% of export by January 2009
5
. The consequences of this fall had an effect in most of the Malaysian sectors, for instance, the gross domestic product(GDP) growth fell by 6.2% at the beginning of the year 2009 compare to 0.1% at the end of 2008 (UNDP)
6
. It is important to note that the unemployment level was also very high which impacted negatively the consumer expenditures. The picture given by the table 2.1 is supported by previous studies like the one that have been done by Matthews and Ismael (2006), saying that foreign commercial banks started operating in Malaysia before its independence (1957), however, the Central Bank and domestic banks waited two years after it to be established. It is also shown in this table that on average foreign banks could be larger than domestic in term of Assets size; and Malaysia has higher number of foreign commercial Banks compare to the domestics.
4 Before the 2008 global crisis, Malaysia’s exports were 81% of manufacture for which 66% of electrical
and electronic merchandise.
5 http://www.adbi.org/working-paper/2009/08/26/3275.malay
sia.gfc.impact.response.rebalancing/impact.of.the.crisis.on.the.malaysian.economy/
6 A join report by the Institute of Strategic and International Study (ISIS) Malaysia commissioned by the
United Nations Development Programme.
http://www.isis.org.my/index.php?option=com_content&view=article&id=456:curr&catid=92:recent- papers&Itemid=168

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7 Table 2.1: List of licensed Commercial Bank in Malaysia
7
: No Banks Ownership Date of Establish Total Asset (USD Billion) 1 Bank Negara Malaysia Central Bank 1959 1209.92 2 JP Morgan Foreign 1964 2,459.13 3 HSBC Foreign 1994 2,117.61 4 Bank of China Berhad Foreign 1991 2,042.09 5 Bangkok Bank Berhad Foreign 1959 970.39 6 Malayan Banking Berhad (Maybank) Dometic 1960 110.3 7 CIMB Bank Berhad Domestic 1965 88.3 8 Public Bank Domestic 1972 74.2 9 Hong Leong Bank + Eon Bank Domestic 2011 43.2 10 AmBank Domestic 1975 42.4 11 RHB Bank Domestic 1966 31.6 12 Hong Long Bank Domestic 1968 27.8 13 Royal Bank of Scotland Berhad Foreign 1964 22.0 9 14 OCBC Bank Berhad Foreign 1912 21.38 15 Mizuho Corporate Bank B Foreign 1973 20.93 16 United Overseas Bank Berhad Foreign 1993 18.36 17 CitiBank Berhad Foreign 1994 16.39 18 Standard Chartered Bank Foreign 1875 15.85 19 Affin Bank Domestic 2000 15.4 20 Eon Bank Domestic 1960 15.2
7 http://www.bnm.gov.my/index.php?ch=13&cat=banking&type=CB&fund=0&cu=0

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8 21 Allance Bank Domestic 2004 10.4 23 Deutsche Bank (Malaysia) Foreign 1967 4.074 24 BANKOF Tokyo- Mitsubishi Foreign 1959 3.12 25 Bank of Nova Scotia Berhard Foreign 1973 3.9 Sources: the web side of each bank and annual reports In contrast to what we have seen in the first table, it is important to note that in the Table 2.2, domestic Islamic banks have larger size than foreign and also they are higher in number.

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9 Table 2.2: List of licensed Islamic Malaysian Banks
8
No Banks Owner Date of Establish Asset Size($billion) 1 CIMB Islamic Bank Berhad Domestic 2003 70.63 2 AmIslamic Bank Berhad Domestic 2006 37.83 3 Maybank Islamic Berhad Domestic 1960 21.97 4 HSBC Amanah Berhad Foreign 1994 21.25 5 Bank Islamic Malaysia Berhad Domestic 1983 10.12 6 RHB Islamic Bank Berhad Domestic 2005 7.54 7 Bank Muamalat Malaysia Berhad Domestic 1999 6.06 8 Hong Leong Islamic Bank Berhad Domestic 2005 4.06 9 Affin Islamic Bank Berhad Domestic 1993 3.51 10 Kuwait Finance House berhad Foreign 2005 3.38 11 Alliance Islamic Bank Berhad Domestic 1994 2.07 12 Al Rajhi Islamic Bank Berhad Foreign 2006 1.97 13 OCBC Al-Amin Bank Berhad Foreign 2008 1.58 14 Standard Chartered Saadiq Berhad Foreign 2008 1.57 15 Public Islmic Bank Berhad Domestic 2004 1.53 16 Asian Finance Bank Berhad Foreign 2007 0.75 Sources: the web side of each bank and annual reports.
8 http://www.bnm.gov.my/index.php?ch=13&cat=banking&type=CB&fund=0&cu=0

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Chapter 3 LITERATURE REVIEW
It is important to recognize that several studies have been done in order to examine the factors influencing bank profitability, about the most popular, we have the primary study done by Short (1979), followed by Bourke (1989) who gave more detail to the relevant variables. The improvement of these studies has led to more specific examination of bank profitability such as the following focusing in a particular country or region: Molyneux and Seth (1996), Said and Tumin (2011), Sufian (2009), Davydenko (2010), Matthewsand Ismail (2005), Flamini, McDonald and Schumacher (2009), B Nimalathasan (2008), Gul et al (2011), Gerlach,Peng and Shu (2005), Varadi, V. Kumar, Mavaluri, P. Kumar and Boppana, Nagarjuna (2006). Molyneux and Seth (1996) examine foreign bank profitability and commercial credit extension for the period 1987-1991 in the USA and they find out that the capital strength and demand on loan have positive effect on the foreign bank profitability but unfortunately unrelated to an improvement in commercial lending. Furthermore, in order to generate higher profitability, a foreign bank in USA should deal with a considerable capital, in other words with a certain higher level of capital compare to other financial institutions.

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11 Said and Tumin (2011) analyze the relationship between performance and financial ratios of commercial banks in Malaysia and China by using some internal factors, their results suggest that credit risk and operating expenses affect negatively the performance of banks in both countries in the case of return on asset (ROA), however, this is different in the case of return on equity (ROE). Therefore, in this case, credit risk and operating expenses have respectively a negative impact on Malaysian and Chinese banks performance. In addition, this study shows that bank performance in both countries is not affected by bank size and liquidity. In the case of Malaysia which is more related to this study, Sufian (2009) analyzes the factors influencing bank profitability in Malaysia covering the period 2000-2004 and focusing specially to foreign and domestic commercial banks. He comes up with the results that there is a negative relationship between credit risk and loan concentrated for Malaysian banks. Therefore, the higher the credit risks of a bank, the more its exposure to loan payment which will result consequently in a low level of profitability. In contrast, he finds that capital size, income from non-interest sources and operating expenses have a positive effect on Malaysian banking profitability. Furthermore, well capitalized bank will generate higher profitability due to lower cost of borrowing but on the contrary is possible otherwise. The results show also, although the negative relationship between economic growth and profitability in the Malaysian banks, high inflation rate affect them positively. Analyzing efficiency and productivity of Malaysian domestic and foreign commercial banks from 1994 till 2000, Matthews and Ismail (2005) figure out that efficiency is

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12 related to size instead of profitability and productivity is based on technical change. They conclude that foreign banks are in a better position than domestic banks in the case of efficiency. In addition, another publication done by the same author (Sufian 2010), which analyzes the effect of regulation and supervision in Malaysian commercial banks’ profitability for the period 1992-2003. The results point out a negative relationship between the regulations and supervisions and the banks’ profitability. Thus the higher the regulation and/or supervision in the Malaysian banking system, the lower the profitability the banks will generate from their operations. On the other hand, the economic growth has a positive effect on Malaysian banks’ profitability and also inflation is positively related to profitability, meaning that the level of inflation was anticipated by the banking sector. Flamini, McDonald and Schumacher (2009) analyze the determinants of commercial bank profitability in Sub-Saharan Africa (SSA) by testing a sample of 389 banks in 41 SSA countries. The results of this study show that private and foreign banks are doing better than public and local banks respectively in term of profitability. It is also mentioned that bank size, activity diversification and private ownership are positively related to the banking profitability in terms of return on asset. In contrast, credit risk and macroeconomic variables have a negative impact on bank profitability. B.imalathasan (2008) uses CAMELS rating in order to do a comparative study of financial performance of Banking Sector in Bangladesh which is categorized in four parties: Nationalized, Public, Private and Foreign commercial banks. According to the

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13 result of the analysis that is done on 48 banks covering the period of 1999-2006, there are 3 strong banks, 31 satisfactory, 7 fair, and 2 unsatisfactory banks. Gul et at (2011) analyze the effect of bank-specific and macroeconomic factors on profitability in the case of Pakistan. Focusing on 15 commercial banks, covering a period of 2005-2009; and using Pooled Ordinary Least Squares, they find that there is a positive relationship between both internal and external factors and profitability, meaning the higher the Equity capital, economic growth and so on, the more profitable the banks are. Gerlach, Peng and Shu (2005) analyze the macroeconomic conditions and banking performance in Hong Kong by using a panel data for 29 banks covering the period of 1994-2002. They use only two ratios of profitability determinant that are Net Interest Margin (NIM) and Non-Performing Loans (NPLS) because they couldn’t get enough data due to some confidentiality. For instance, they don’t know the Asset size of individual banks and they also don’t have any information about banks ownership. The finding of the study is that changes in macroeconomic conditions affect banks’ performance and financial health. In order to examine Efficiency of Indian banks, Varadi, V. Kumar, P. Kumar and Boppna, Nagarjuna (2006) have used four indicators which are profitability, productivity, asset quality and financial management for public, private and foreign banks for a period of 1999-2003. The results of the study show that public banks have a high efficiency according to both above ratios, whereas private banks have a very high

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14 inefficiency, but foreign banks are in a better situation compare to private in term of efficiency.

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Chapter4 DATA AND METHODOLOGY
4.1 Data
The data that are used in this study are firstly collected from the balance sheet and income statement of each bank that are provided throughout their financial annual reports for the concerning period, secondly put in excel spreadsheet in order to calculate the ratios needed for the empirical study. It is important to underline that the data are annual data. Instead of analyzing all the local commercial banks (8)
9
, this study will focus on the seven local banks; the reason is simply the problem that was faced in the collecting data.
9 http://www.bnm.gov.my/index.php?ch=13&cat=banking&type=CB&fund=0&cu=0

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16 Table 4.1: Selected commercial banks and Ownerships No Name of Banks Ownerships 1 Affin Bank Berhad Local Bank(domestic) 2 Alliance Bank Malaysia Berhad Local Bank 3 CIMB Bank Berhad Local Bank 4 Hong Leong Bank Berhad Local bank 5 Malayan Banking Berhad Local Bank 6 Public Bank Berhad Local Bank 7 RHB Bank Berhad Local Bank 8 Bank of China (Malaysia) Berhad Foreign Bank 9 Citibank Berhad Foreign Bank 10 Deutsche Bank (Malaysia) Berhad Foreign Bank 11 HSBC Bank Malaysia Berhad Foreign Bank 12 OCBC Bank (Malaysia) Berhad Foreign Bank 13 Standard Charteredt Bank Malaysia Berhad Foreign Bank 14 United Overseas Bank (Malaysia) Berhad Foreign Bank
4.2 The Variables
Referring to the previous studies, this thesis will employ two categories of variables in order to examine the profitability of the selected commercial banks. These categories are classified as dependent variables and independent variables. In the case of this study, seven (7) variables have been chosen: two dependent and five independent.

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17 Table 4.2: The variables measures and their notation Bank-Specific Variables Measures Notation Dependent Variables Profitability Return on Assets(ROA)=Net Income/Total Asset Return on Equity=Net Income/Total Equity ROA ROE Independent Variables Capital Adequacy Equity/Total Asset CAR Asset Quality Total Loan, Advances and Financing/Total Asset ASQ Earnings Interest Income/Interest Expense EAR Liquidity Liquidity Asset/Total Asset LQR Bank Size Natural logarithm of Total Asset LSIZE 4.2.1 Dependent Variables According the importance role played by the Return on Asset (ROA) and Return on Equity (ROE) in the banking profitability, these dependent variables are present in almost all the bank performance analysis. ROA: Return on Asset (ROA) ratio is obtained from the division of the Net Income by the Total Asset, and expressed in percentage. It is a key indicator of profit and asset management efficiency. Therefore, it indicates how well the bank’s assets are managed to bring profit for each one dollar of asset that has been invested to the company or the bank (Gul et Al 2011). ROE: Return on Equity (ROE) is obtained by the ratio of Net Income to Total Equity and expressed in percentage. This ratio is also an important indicator of bank profitability in

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18 the case of the use of the shareholder’s Equity. Furthermore, it shows the ability of the management to utilize the shareholder’s Equity whether to improve the return earning or to keep the bank in good position. Thus the better the management of the shareholder’s Equity, the more efficient or the more profit the bank will generate in term of Return on Equity. 4.2.2 Independent Variables Capital adequacy: Capital adequacy ratio, also known as capital to risk weighted asset ratio, is calculated by the division of Equity to Total Asset and estimated as a percentage of the bank riskiness or ability to protect its depositors from bank failure. (Mlyneux, 1993), indicates in his study a positive relationship between Equity and bank profitability in the case of lowering the cost of capital. Asset Quality: It is the ratio of Total Loan, advances and financing to Total Asset, this ratio determines the degree of use of asset in term of Loan. As Loan is the main source of bank’s income and is also expected to have positive impact on profit, the higher this ratio, the more profitable the bank is in a stable economy and the worst on the other hand when the borrowers fall to pay their promises. Earning: Management Efficiency is calculated as the ratio of Interest Income over Interest Expense, this ratio will show how well a financial institution is able to use its assets and liabilities internally. Moreover, as the goal is to earn more from the investments that

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19 have been made, the higher this ratio for a company the more efficient it is in generating more profit over its operating expenses. Liquidity: Liquidity Ratio is expressed as a company’s ability to repay its short-terms debts obligations. It is obtained from the division of the Liquidity Assets by the Total Assets of the company. A larger number of this ratio implies sufficient liquidity to meet unexpected customers need in cash, thus the more safety for going bankruptcy. Some authors like Bourke (1989) mentions in his study a positive relationship between liquidity and bank profitability. In contrast, Molyneux and Thorton (1992) point out a negative impact of liquidity on the profitability. However keeping a certain amount of liquidity will engender loses because of the time of money. Bank Size: Calculated as Logarithmic of Total Asset, Bank Size is expected to have a positive impact in the company profitability especially in economy of scale. There has been a lot of discussion concerning the relationship between Bank Size and profitability. Anthanasoglou et, at (2006) point out that according to some factors, increasing bank size may have negative effect on profitability. Dummy: Dummy is introduced in the regression as another variable indicator of profitability especially during a period of crisis to indicate whether the financial institutions have

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20 been affected by the crisis or not. In the present study, dummy is given the value zero (0) for the stable period and the value one (1) for the financial crisis 2008.
4.3 Methodology
4.3.1 Panel Unit root Test: As the aim of this study is to analyze factors affecting Malaysian banking industry by analyzing bank specific, a regression analysis is employed to the panel data that have been collected from the balance sheet and income statement through their financial annual report. Panel data is defined as the combination of cross-section and time series data. Before running the regression analysis, a test has been done in order to see whether the data are stationary or not, by doing so, a unit root test has confirmed a rejection of the null hypothesis under the Levin Lin and Chu (LLC), Pesaran and Shin W-stat (PS); and Fisher Chi-square (M-W), which means the data are stationary. The Unit Root of the panel is provided in the Empirical Analysis and Results. 4.3.2 Proposed Model: After verifying and finding that the data are stationary, it comes to the estimation of the banking performance, and to do so, the Ordinary Least Square (OLS) is employed. The regression analysis is done by applying Eviews software program to the OLS method, unfortunately this OLS method will not be efficient if there is autocorrelation in the regression model as it is in this case, because the value of Durbin Watson obtain from the regression analysis (OLS) is below tow (2). Therefore, the best way of elimination of the autocorrelation is to use Var model (Vector Auto regression model) that will lead to a fitted model at lag1, lag2 and lag3 as the case in this study.

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21 Referring to the dependent variables (ROA, ROE) involved in this thesis, the econometric of the Panel Regression will be as the following: Yi = β0 + βXi + Di + εt Where: Yi represents the dependent variable of the function βο the intercept of the model Xi represents the independent variables Di represents the dummy variables εt represents the error term In respect to the model above, the regression analysis of this study are the following: LROA=βο+β1LCAR+β2LLQR+β3LEAR+D+εt LROE=βο+β1LCAR+β2LLQR+β3LEAR+D+εt Asset Quality (ASQ) does not figure in the regression because of the higher multicollinearity it has with Liquidity Ratio (LQR) and also by using it instead of LQR the regression will not give efficient significance, the same problem is also faced with bank size (LSIZE). In addition, the natural Logarithm is used here in order to eliminate the trend in the model because the variables are too much volatile.

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Chapter 5 EMPIRICAL ANALYSIS AND RESULTS
5.1 Panel Unit Root Test Results:
The results of the Unit Root Analysis indicate the rejection of the null hypothesis and accepting the alternative meaning that the data involve in this study are stationary. Furthermore, single star (*) stands for probability less than α=1%, double stars (**) for α=5% and finally three stars (***) for α=10% Unit Root Analysis (All Banks) Variables Levels LLC IPS M-W ROA
τT
-8.87* 0.50 41.03***
τμ
-7.13* -0.13 37.29
τ
-3.18* - 41.78** ROE
τT
-7.82* 0.10 50.04*
τμ
-1.93** 1.10 21.45
τ
-4.89* - 76.33* CAR
τT
-4.59* -0.68 38.27***
τμ
-1.58*** 0.26 34.61
τ
-0.47 - 33.97
τT
-13.45* -0.53 73.81

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23 LQR
τμ
-5.76* 1.26 62.82*
τ
-3.81*** - 33.97 EAR
τT
-31.54* -1.60*** 52.68*
τμ
-2.3 0.33 21.71
τ
34.66 - 13.90
5.2 Correlation Analysis:
Correlation analysis is employed to identify the relationship between a dependent variable and one or more independent variables. In the case of this study, the correlation is analyzed in three separate categories or groups: firstly, the correlation of the variables for all banks in general, secondly, for domestic banks, and finally, for foreign banks. Correlation analysis plays double role in the regression analysis model by indicating how the dependent variable is affected by the independent variables and by testing for the existence of multicollinearity between the independent variables. It is important to note that in all the three tables of correlation below, the dependent variables (ROA and ROE) are positively correlated.

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24 Table 5.1: correlation Matrix for All banks ROA ROE CAR LQR ASQ LSIZE EFF D ROA 1.00 ROE 0.60 1.00 CAR -0.01 -0.62 1.00 LQR -0.23 -0.28 0.31 1*.00 ASQ 0.27 0.28 -0.24 -0.92 1.00 LSIZE 0.23 .41 -0.60 0.61 0.51 1.00 EAR 0.29 0.06 0.01 -0.03 0.08 0.06 1.00 D 0.12 0.10 -0.10 -0.10 0.00 -0.00 -0.16 1.00 According to the result of the correlation analysis in table 5.1, Capital Adequacy (CAR) and Liquidity (LQR) have negative effect on both Return on Asset (ROA) and Return on Equity (ROE), in contrast, Asset Quality (ASQ) and Erning (EAR) affect ROA and ROE positively. The same table shows a higher negative (-0.92) correlation between two independent variables which are ASQ and LQR, also a low correlation between these variables and the other remaining, thus the presence of multicollinearity problem in the model. However, in order to eliminate this higher multicollinearity, ASQ and bank size have been dropped and in the case of the lower value of Durbin Watson (below 2), a Var model at lag3 is used.

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25 Table 5.2: Correlation Matrix for Domestic Banks ROA ROE CAR LQR ASQ EFF D ROA 1.00 ROE 0.41 1.00 2 CAR 0.39 -0.51 1.00 LQR -0.18 -0.12 0.02 1.00 ASQ 0.18 0.04 -0.02 -0.70 1.0 EAR 0.24 -0.10 0.08 -0.37 0.47 1.00 D 0.02 0.19 -0.09 -0.13 -0.08 -0.21 1.00 This table 5.2 indicates that a positive relationship between ROA and CAR, ASQ, EAR and a negative with LQR. Looking to the ROE, only ASQ has positive impact on it, while the other variables (CAR, LQR, and EAR) have inverse relationship. Here also, there is higher negative (-0.70) correlation between ASQ and LQR as the case in the table 5.1.

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26 Table 5.3: Correlation Matrix for Foreign Banks ROA ROE CAR LQR ASQ EFF D ROA 1.00 ROE 0.70 1.00 CAR -0.22 -0.68 1.00 LQR -0.33 -0.45 0.40 1.00 ASQ 0.36 0.41 -0.28 -0.96 1.00 EAR 0.32 0.08 -0.01 0.03 0.07 1.00 D 0.21 0.01 0.01 -0.10 0.03 -0.15 1.00 As in the first table this for the foreign banks shows that ASQ and EAR are positively related to both on ROA and ROE, however, CAR and LQR affect them negatively. The higher negative correlation between ASQ and LQR also appeared in these results.
5.3 Regression Analysis Results
After finding the correlation between the variables, the present task is to see whether the explanatory (independent) variables affect or not the explained (dependent) variables, in other word, to see how the selected ratios (CAR, LQR, ASQ, EAR, LSIZE) impact profitability of financial institutions which are represented by ROA and ROE in this case. Furthermore, the regression analysis result is categorized in three parts as the following: 5.3.1 Regression Analysis Result of All Banks The regression analysis shows a negative relationship between Capital Adequacy (Equity/Total Asset) and Return on Asset (ROA) at lag3 and also this independent

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27 variable is statistically significant. This finding suggests that when the Capital Adequacy increases, profitability will decrease. In another words, when the banks increase the use of Equity, they will register more losses. The explanation of this phenomenon can be firstly the amount they are paying to their shareholders as a dividend is greater than what they are generating from it as a profit. Secondly, it could be the case that they are using retain earning without investing it in new plan that will give more profit to the company. Regarding the second profitability indicator which is the Return on Equity (ROE), Capital Adequacy (CAR) is not significant, that means ROE is not affected by CAR. Liquidity (Liquidity Asset/Total Asset) is also statistically significant and has two different effects on the ROA; the first one is negative impact at lag2 and second is positive at lag3. In the first case of the negative impact is supported by the previous studies as Molyneux and Thorton (1992) point out a negative impact of liquidity (LQR) on the banking sector profitability. Therefore, in this situation increasing liquidity will decrease profitability. In the second one, the positive impact on ROA is a good sign of profitability because it shows that banks have the ability to meet unexpected demand in cash by their customers. Bourke (1989) mentions in his study a positive relationship between Liquidity and bank’s profitability. Similarly to it relation with ROA, LQR has one negative effect at lag1 and one positive effect at lag3 to the ROE and it is statistically significant. That means at lag1 in order to get benefit or increase the profit, Malaysian banks should reduce the amount of liquidity they are taking from their shareholders. In contrast, at lag3 they should increase liquidity as it will bring more profit. Coming to Earning (Interest Income/Interest Expense), as the precedent LQR, Earning (EAR) affects ROA and ROE in two sense invers and it is also statistically significant. At lag2 it impacts both ROA and ROE negatively meaning that

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28 the management of assets and liabilities of banks could not work efficiently in order to generate sufficient interest income. However, at lag3 EAR has a positive relationship with also both ROA and ROE, according to this relationship here, the higher the Earning, the more profit the banks will have. Dummy is significant only in the case of ROE and affects it negatively at lag1. This shows that Malaysian commercial banks also suffered from the Global Financial crisis 2008 which started in the U.S. 5.3.2 Regression Analysis Result of Domestic Banks: The regression analysis result of domestic banks shows that CAR is not statistically significant in both ROA and ROE. Thus it does not have any effect in these profitability indicators. LQR has a positive impact in both ROA and ROE and also significant at lag3 in the two dependent variables. Therefore, an increase in liquidity indicates an increase in domestic banks profitability, thus the more safety for them of going bankruptcy. EAR has positive relationship with ROA and statistically significant at lag3, that means assets and liabilities are well utilized by the management team and generate more profit. Dummy does not have any significance effect on Malaysian domestic bank’s profitability indicators. Therefore, they did not suffer from any losses due to the Global Financial Crisis 2008. 5.2.3 Regression Analysis Result of Foreign Banks: The result of this regression analysis indicates that CAR has a positive impact on ROA as well as on ROE and is also significant in both at lag1. Therefore, as CAR is defined as Equity/Total Asset, the higher the increase in Equity the more profit of foreign banks; this is the result of the reduction of the cost of funding. LQR is not statistically significant, thus does not affect any of the dependent variables, and consequently does not impact the profitability of foreign banks. The behavior of EAR here (foreign banks)

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29 is similar to that one with All Banks, this means that EAR is significant in both cases (ROA and ROE) and has two different manners of affecting these ROA and ROE profitability indicators. In the ROA side, EFF has a positive relationship at lag1 and negative one at lag2. When coming to the ROE, it has positive impact at lag1 and lag3; and a negative one at lag2. The meaning of these changes is that banks can not keep gaining or losing profit continuously in their period of operation. Dummy variable is statistically significant at lag1 and has a negative effect on both ROA and ROE, the meaning of that is that Malaysian foreign banks were affected by the Global Financial Crisis 2008; as a consequence, they registered losses from their annual operating income.
5.4 Comparison between Domestic and Foreign Banks
Comparison between the two categories of ownerships in term of profitability is done by taking the average of ROA and ROE of the banks respectively; and then finding their graph in the same figure. By doing so, figure 5.1 and figure 5.2 show that foreign banks are more profitable than domestics banks, they highlight also that the former were more affected by the 2008 crisis than the latter. As a result of the consequence of the crisis, foreign banks register a lot of losses in the preceding years. Note that ROA1 and ROE1 stand for domestic; and ROA2 and ROE2 for foreign.

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30 Figure 5.1: ROA measure for All the Malaysian Banks ROA1: Domestic Banks ROA2: Foreign Banks
0.00000 0.50000 1.00000 1.50000 2.00000 2.50000 3.00000 3.50000 4.00000 2005 2006 2007 2008 2009 2010 2011 ROA1 ROA2

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31 Figure 5.2: ROE measure for All the Malaysian Banks ROE1: DOMESTIC Banks ROE2: Foreign Banks
0.00000 10.00000 20.00000 30.00000 40.00000 50.00000 60.00000 2005 2006 2007 2008 2009 2010 2011 ROE1 ROE2

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32
Chapter 6 CONCLUSION AND SUGGESTION
The aim of this study is to examine the performance of the Malaysian’s local and foreign banks, and compare their profitability in the financial sector. Profitability of commercial banks can be influenced by several factors, such as liquidity, Asset Quality, capital, operating expenses, and the size of the banks. Measuring the profitability in term of Return on Asset (ROA) and Return on Equity (ROE) is done by using bank specific variables and Dummy is introduced in the regression as another factor that influence profitability especially during the period of 2008 to indicate whether the financial institutions have been affected by the crisis or not. For this analysis, a panel regression methodology has been applied to empirically investigate the performance of seven (7) local and seven (7) foreign commercial banks, covering a period between 2005 and 2011. Some previous studies have been carried out in the same field such as the work of Sufian (2009) investigating the factors influencing the profitability of the Malaysian banking industry covering the period 2000-2004 and focusing specially to foreign and domestic commercial banks. He comes up with the results that there is a negative relationship between credit risk and loan concentrated for Malaysian banks. In contrast, he finds that capital size, income from non-interest sources and operating expenses have a positive effect on Malaysian banking profitability.

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33 The empirical finding shows that all commercial banks are positively affected by LQR, EFF, in contrast, they are negatively impacted by CAR, LQR, EAR and Dummy at some lags (see tables of Var Mdel). In the case of domestic banks LQR and EAR have positive effect on profitability; the remaining variables are not significant. Profitability of foreign banks is affected positively by CAR, EAR; and negatively by EAR and dummy at some different lags. The comparison between the two categories of ownership indicates that foreign banks are more profitable than domestic; this is supported by the study of Matthews and Ismail (2005) saying that foreign Malaysian banks are in better position than domestic in the case of profitability. The suggestion of this Thesis for future studies is to introduce additional bank specific and macroeconomic variables in order extend these results. Regarding the policy maker, it would be better to encourage domestic banks by providing some support such as providing subsidy or making a reduction on their taxes comparably to foreign banks.

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34
REFERENCES
A. Ghan (2005): Creating a comparative banking system-towards the enhancement of quality and efficiency in Malaysian banks: 9
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Malaysian Banking Summit 2005 “enhancing competitiveness to meet challenges”,Kuala Lumpur, 10 May 2005. Al Shaher, Kasawneh and Salem (2011): The Major Factors that Affect Banks’ performance in Middle Eastern Countries. Journal of Money, Investement and Banking Abidin and Rasiah (2009): the Global Finacial Crisis and the Malaysian Economy: Impact and Resonses:Unitea Nations Development Programme. B. Nimalathasan (2008): A comparative study of financial performance of Banking sector in Bangladesh-An application of CAMELS rating/Annals of University of
Bucharest,Economic and Administrative Series, Nr,2 (2008) 141-152
Bank Negara Malaysia: Central Bank of Malaysia. http://www.bnm.gov.my/index.
php?ch=13&cat=banking.
D. Hadad, J. B. Hall, Kenjegaliea, Santoso, Satria and Simper (2008): Banking Efficiency and Stock Market Performance: An analysis of Listed Indonesian Banks: Discussion Paper Series
Davydenko, Antonina (2011): “Determinants of Banks Profitabilityin Ukrain”, Undergraduate Economic Review: vol. 7: iss. 1, Article 2.

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35 E. Detragiache, P. Gupta (2006): Foreign banks in emerging market crises Evidence from Malaysia. Journal of Financial Stability 2 (2006) 217-242 F. Laswad (1999): An Analysis of Financial Performnce of Malayisa-Based multinational En trprises: Commercial Division Paper No.74 Flamin, McDonald, and Schumacher 2009: The Determinants of Commercial BANK Profitability in Sub-Saharn Africa. IMF Working Paper. African Department F. Sufian (2010): Developments in the performance of the Malaysian banking sector: opportunity cost of regulatory compliance. Int. J. Business Competition and Growth,
Vol. 1, 2010
F.Sufian (2009): Determinants of bank efficiency during unstable macroeconomic environment: Empirical evidence from Malaysia. Research in International Business and Finance 23 (2009) 54-77 F. Sufian (2009): Factors Influencing Profitability in a Developing Economy: Empirical Evidence from Malaysia. Global Business Review 2009 10: 225 Gul et al (2011): Factors Affecting Bank Profitability in Pakistan: The Romanian
Economic Journal Gerlach, Peng and Shu (2005): Macroeconomic conditions and banking performance in Hong Kong SAR: a panel data study. BIS Papers No 22 Havrylchyk and Juryk (2011): Profitability of foreign banks in Central and Eastern Europe. Does the entry mode matter? Economics of Transition. 19(3) 2011, 443-472 Ing. Bobakova, CSc. (2003): Raising the Profitability of Commercial Banks: BIATIC, xi.

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NARODNA BANKA SLOVENSKA Ito and Hashimoto (2007): Bank Restructuring in Asia: Crisis management in the aftermath of the Asian financial crisis and prospects for crisis prevention-Malaysia- J.Goddard (2004): The profitability of European Banks: A Cross-sectional and dynamic panel analysis. The Manchester School Vol 72 No.3
Khoon and Mah-Hui 2010. The impact of the Global Financial Crisis: The case of Malaysia. Third World Network 131 Jalan Macalister 10400 Penang, Malaysia. Matthews and Ismail (2006): Efficiency and Productivity Growth of Domestic and Foreign Commercial Banks in Malaysia. Cardiff Economics Working Papers. Mehmet SEN (2009): Relationship between Efficiency Level of Working Capital Management and Return on Total Assets in Ise (Insabul Stock Exchange). Molyneux and Seth (1996): Foreign Banks, Profits and Commercial credit Extension in the United States. Federal Reserve Bank of New York. Research Paper No.9628 Ong, Teo and Teh (2011): Analysis on Financial Performance and Efficiency Changes of Malaysian Commercial Banks after Mergers and Acquisitions. International
Journal of Business & Management Tomorrow Nor.Faezah (2007): Evaluation of Capital Adequacy Ratio of Commercial Bank in Malaysia Based on Basel II Accord: A thesis submitted to the Graduate School in partial fulfillment of the requirements for the degree Master of Science (Banking) University Utara Malaysia.

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37 Said and Tumin 2011: Performance and Finance Ratios of Commercial Banks in Malaysia and China. International Review of Business Research Papers. Vol. 7. 2.
March 2011. Pp. 157-169 Suhaimi, Abdullah and Saban (2010): Factors affecting profit efficiency of commercial banks in Malaysia: 2010 International Conference on Science and Social Research (CSSR 2010), December 5-7, 2010, Kuala Lumpur, Malaysia. Varadi, V. Kumar, Mavaluri, P. Kumar and Boppana, Nagarjuna (2006): Measurement of Efficiency of Banks in India: Munich Personal RePEc Archive
W. Naude (2009): The Financial Crisis of 2008 and the Developing Countries: Discussion Paper, United Nations University

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38
APPENDICES

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39 Unit Root Analysis (All Banks) Variables Levels LLC IPS M-W ROA
τT
-8.87* 0.50 41.03***
τμ
-7.13* -0.13 37.29
τ
-3.18* - 41.78** ROE
τT
-7.82* 0.10 50.04*
τμ
-1.93** 1.10 21.45
τ
-4.89* - 76.33* CAR
τT
-4.59* -0.68 38.27***
τμ
-1.58*** 0.26 34.61
τ
-0.47 - 33.97 LQR
τT
-13.45* -0.53 73.81
τμ
-5.76* 1.26 62.82*
τ
-3.81*** - 33.97 EAR
τT
-31.54* -1.60*** 52.68*
τμ
-2.3 0.33 21.71
τ
34.66 - 13.90

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40 Unit Root Analysis (Domestic Banks) Variables Levels LLC IPS M-W ROA
τT
-11.78* -0.69 39.38*
τμ
-11.61* -2.83* 38.61*
τ
-2.62* 24.29** ROE
τT
-9.68* -0.78 46.93*
τμ
-5.13* -1.25 25.85**
τ
-3.46* 39.93* CAR
τT
-3.72* 0.33 23.27***
τμ
-2.03** 0.04 13.58
τ
0.81 8.95 LQR
τT
-11.80* -0.91 49.50*
τμ
-3.72* -0.86 28.27**
τ
-4.03* 24.00***
τ
0.96 6.75 EAR
τT
-19.91* -1.36*** 32.47*
τμ
-1.30*** 0.66 7.85
τ
21.18 6.16

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41 Unit Root Analysis (Foreign Banks) Variables Levels LLC IPS M-W ROA
τT
-1.19 0.18 4.29
τμ
2.50 1.30 5.35
τ
-2.12* 18.69 ROE
τT
-4.05* 0.13 19.93
τμ
-1.04 1.27 11.87
τ
-4.10* 31.92* CAR
τT
-3.07* 0.49 11.43
τμ
-1.28* 0.38 13.82
τ
-1.25 14.81 LQR
τT
-4.81* 0.23 21.74***
τμ
-4.43* -0.90 31.73*
τ
-1.02 11.86 ASQ
τT
-5.38* -6.00 30.04*
τμ
-5.89* -1.52*** 45.04*
τ
-0.90 19.32 EAR
τT
-4.80* 0.17 19.65
τμ
-2.94* -0.31 15.42
τ
-0.03 6.54

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42 Regression Analysis for all the Banks
Dependent Variable: LROE Method: Panel Least Squares Date: 05/03/12 Time: 16:29 Sample: 2005 2011 Periods included: 7 Cross-sections included: 14 Total panel (balanced) observations: 98 Variable Coefficient Std. Error t-Statistic Prob. C 6.006070 0.381598 15.73925 0.0000 LCAR -1.083099 0.083478 -12.97460 0.0000 LLQR -0.129011 0.095041 -1.357418 0.1779 LEAR 0.473448 0.204616 2.313831 0.0229 D 0.134217 0.098119 1.367892 0.1746 R-squared 0.684339 Mean dependent var 3.617860 Adjusted R-squared 0.670763 S.D. dependent var 0.576450 S.E. of regression 0.330763 Akaike info criterion 0.674842 Sum squared resid 10.17457 Schwarz criterion 0.806728 Log likelihood -28.06724 Hannan-Quinn criter. 0.728187 F-statistic 50.40508 Durbin-Watson stat 1.111897 Prob(F-statistic) 0.000000 Dependent Variable: LROA Method: Panel Least Squares Date: 05/03/12 Time: 16:28 Sample: 2005 2011 Periods included: 7 Cross-sections included: 14 Total panel (balanced) observations: 98 Variable Coefficient Std. Error t-Statistic Prob. C 1.400740 0.381562 3.671064 0.0004 LCAR -0.083057 0.083471 -0.995040 0.3223 LLQR -0.128976 0.095033 -1.357182 0.1780 LEAR 0.473387 0.204597 2.313750 0.0229 D 0.134226 0.098110 1.368120 0.1746 R-squared 0.107042 Mean dependent var 1.119032 Adjusted R-squared 0.068635 S.D. dependent var 0.342701 S.E. of regression 0.330732 Akaike info criterion 0.674653 Sum squared resid 10.17265 Schwarz criterion 0.806540 Log likelihood -28.05802 Hannan-Quinn criter. 0.727999 F-statistic 2.787054 Durbin-Watson stat 1.112036 Prob(F-statistic) 0.030915

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43 Regression Analysis for Domestic Banks
Dependent Variable: LROA Method: Panel Least Squares Date: 05/08/12 Time: 18:11 Sample: 2005 2011 Periods included: 7 Cross-sections included: 7 Total panel (balanced) observations: 49 Variable Coefficient Std. Error t-Statistic Prob. C 0.664885 0.615788 1.079729 0.2861 LCAR 0.231273 0.143565 1.610925 0.1143 LLQR -0.060108 0.125768 -0.477933 0.6351 LEAR 0.245851 0.394021 0.623953 0.5359 D 0.074776 0.123887 0.603581 0.5492 R-squared 0.090358 Mean dependent var 1.123976 Adjusted R-squared 0.007663 S.D. dependent var 0.282908 S.E. of regression 0.281822 Akaike info criterion 0.401368 Sum squared resid 3.494637 Schwarz criterion 0.594411 Log likelihood -4.833514 Hannan-Quinn criter. 0.474608 F-statistic 1.092672 Durbin-Watson stat 1.290100 Prob(F-statistic) 0.371974 Dependent Variable: LROE Method: Panel Least Squares Date: 05/08/12 Time: 18:12 Sample: 2005 2011 Periods included: 7 Cross-sections included: 7 Total panel (balanced) observations: 49 Variable Coefficient Std. Error t-Statistic Prob. C 5.270065 0.615794 8.558161 0.0000 LCAR -0.768711 0.143567 -5.354384 0.0000 LLQR -0.060116 0.125769 -0.477986 0.6350 LEAR 0.245851 0.394025 0.623948 0.5359 D 0.074744 0.123888 0.603316 0.5494 R-squared 0.420798 Mean dependent var 3.638860 Adjusted R-squared 0.368143 S.D. dependent var 0.354543 S.E. of regression 0.281825 Akaike info criterion 0.401387 Sum squared resid 3.494702 Schwarz criterion 0.594430 Log likelihood -4.833972 Hannan-Quinn criter. 0.474627 F-statistic 7.991635 Durbin-Watson stat 1.289917 Prob(F-statistic) 0.000062

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44 Regression Analysis for Foreign Banks
Dependent Variable: LROA Method: Panel Least Squares Date: 05/10/12 Time: 01:18 Sample: 2005 2011 Periods included: 7 Cross-sections included: 7 Total panel (balanced) observations: 49 Variable Coefficient Std. Error t-Statistic Prob. C 1.903969 0.666420 2.857010 0.0065 LCAR -0.156396 0.115753 -1.351116 0.1836 LLQR -0.227016 0.185074 -1.226622 0.2265 LEAR 0.500027 0.259328 1.928168 0.0603 D 0.227432 0.153099 1.485525 0.1445 R-squared 0.212127 Mean dependent var 1.114088 Adjusted R-squared 0.140503 S.D. dependent var 0.396545 S.E. of regression 0.367634 Akaike info criterion 0.932991 Sum squared resid 5.946796 Schwarz criterion 1.126034 Log likelihood -17.85828 Hannan-Quinn criter. 1.006231 F-statistic 2.961647 Durbin-Watson stat 0.979700 Prob(F-statistic) 0.029879 Dependent Variable: LROE Method: Panel Least Squares Date: 05/10/12 Time: 01:18 Sample: 2005 2011 Periods included: 7 Cross-sections included: 7 Total panel (balanced) observations: 49 Variable Coefficient Std. Error t-Statistic Prob. C 6.509157 0.666511 9.766022 0.0000 LCAR -1.156466 0.115769 -9.989457 0.0000 LLQR -0.227011 0.185099 -1.226429 0.2266 LEAR 0.500126 0.259363 1.928286 0.0603 D 0.227461 0.153119 1.485516 0.1445 R-squared 0.772577 Mean dependent var 3.596859 Adjusted R-squared 0.751903 S.D. dependent var 0.738181 S.E. of regression 0.367683 Akaike info criterion 0.933262 Sum squared resid 5.948409 Schwarz criterion 1.126305 Log likelihood -17.86493 Hannan-Quinn criter. 1.006502 F-statistic 37.36812 Durbin-Watson stat 0.979532 Prob(F-statistic) 0.000000

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45 Var model of ROA of All Banks
LROA LROA(-1) 0.787165 (0.31173) [ 2.52515] LROA(-2) -0.307000 (0.37107) [-0.82733] LROA(-3) -0.251620 (0.23296) [-1.08009] LCAR(-1) -0.074521 (0.11034) [-0.67539] LCAR(-2) 0.139953 (0.19086) [ 0.73326] LCAR(-3) -0.356222 (0.15794) [-2.25549] LLQR(-1) -0.240578 (0.13408) [-1.79427] LLQR(-2) -0.374747 (0.16861) [-2.22252] LLQR(-3) 0.717548 (0.09766) [ 7.34755] LEAR(-1) 0.113119 (0.20316) [ 0.55681] LEAR(-2) -2.040824 (0.33153) [-6.15573] LEAR(-3) 3.342458 (0.47382) [ 7.05432] D -0.105122

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46
C 0.154760 (0.45324) [ 0.34145] R-squared 0.864572 Adj. R-squared 0.813787 Sum sq. resids 1.274080 S.E. equation 0.178471 F-statistic 17.02404 Log likelihood 26.46700 Akaike AIC -0.373821 Schwarz SC 0.204851 Mean dependent 1.049461 S.D. dependent 0.413584
Var Model of ROE of All Banks
LROE LROE(-1) 0.348040 (0.40790) [ 0.85324] LROE(-2) 0.295222 (0.48562) [ 0.60793] LROE(-3) 0.103330 (0.30475) [ 0.33906] LCAR(-1) 0.306520 (0.36876) [ 0.83121] LCAR(-2) -0.229539 (0.38419) [-0.59746] LCAR(-3) -0.248970 (0.32968) [-0.75520]

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47
8LLQR(-1) -0.523877 (0.17540) [-2.98674] LLQR(-2) -0.155779 (0.22056) [-0.70629] LLQR(-3) 0.642726 (0.12773) [ 5.03184] LEAR(-1) 0.074867 (0.26575) [ 0.28172] LEAR(-2) -1.955905 (0.43365) [-4.51032] LEAR(-3) 2.479366 (0.61976) [ 4.00055] D -0.205456 (0.09503) [-2.16210] C 0.974648 (1.78582) [ 0.54577] R-squared 0.882569 Adj. R-squared 0.838533 Sum sq. resids 2.179903 S.E. equation 0.233447 F-statistic 20.04175 Log likelihood 11.42944 Akaike AIC 0.163234 Schwarz SC 0.741906 Mean dependent 3.526446 S.D. dependent 0.580960
Var Model of ROA of Domestic Banks
LROA

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48
LROA(-1) 0.273531 (0.62680) [ 0.43639] LROA(-2) -0.169872 (0.73726) [-0.23041] LROA(-3) -0.486860 (0.42071) [-1.15722] LCAR(-1) 0.092140 (0.16811) [ 0.54809] LCAR(-2) 0.026446 (0.26753) [ 0.09885] LCAR(-3) 0.021701 (0.27020) [ 0.08032] LLQR(-1) -0.319289 (0.20151) [-1.58446] LLQR(-2) -0.111991 (0.26126) [-0.42866] LLQR(-3) 0.644583 (0.13520) [ 4.76762] LEAR(-1) -0.036219 (0.66963) [-0.05409] LEAR(-2) -0.105671 (0.83733) [-0.12620]

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LEAR(-3) 2.227668 (0.91099) [ 2.44533] D -0.046663 (0.12313) [-0.37898] C -0.822065 (1.86177) [-0.44155] R-squared 0.863950 Adj. R-squared 0.693887 Sum sq. resids 0.389614 S.E. equation 0.180188 F-statistic 5.080185 Log likelihood 20.11695 Akaike AIC -0.294068 Schwarz SC 0.467192 Mean dependent 1.066579 S.D. dependent 0.325676
Var Model of ROE of Domestic Banks
LROE LROE(-1) -0.358590 (0.96971) [-0.36979] LROE(-2) 0.468711 (1.14067) [ 0.41091] LROE(-3) -0.105640 (0.65078) [-0.16233] LCAR(-1) -0.101412 (0.84911) [-0.11943] LCAR(-2) -0.037122

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(0.98066) [-0.03785] LCAR(-3) -0.021221 (0.64711) [-0.03279] LLQR(-1) -0.501346 (0.31166) [-1.60862] LLQR(-2) 0.105748 (0.40397) [ 0.26177] LLQR(-3) 0.562261 (0.20903) [ 2.68981] LEAR(-1) -0.229994 (1.03529) [-0.22215] LEAR(-2) -0.005127 (1.29485) [-0.00396] LEAR(-3) 0.411004 (1.40866) [ 0.29177] D -0.193773 (0.19040) [-1.01773] C 3.360233 (5.64396) [ 0.59537] R-squared 0.745204 Adj. R-squared 0.426708 Sum sq. resids 0.931437 S.E. equation 0.278603 F-statistic 2.339763 Log likelihood 7.914951 Akaike AIC 0.577503 Schwarz SC 1.338763 Mean dependent 3.578717 S.D. dependent 0.367958

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51 Var Model of ROE of Foreign Banks
LROA LROA(-1) 1.122359 (0.42838) [ 2.61998] LROA(-2) 0.057979 (0.63873) [ 0.09077] LROA(-3) 0.263494 (0.36319) [ 0.72549] LCAR(-1) 0.866079 (0.35907) [ 2.41201] LCAR(-2) -0.538179 (0.46867) [-1.14830] LCAR(-3) -0.282704 (0.28149) [-1.00430] LLQR(-1) 0.246019 (0.29392) [ 0.83704] LLQR(-2) -0.617033 (0.39450) [-1.56409] LLQR(-3) 0.228128 (0.44521) [ 0.51240] LEAR(-1) 0.510237 (0.23036) [ 2.21497] LEAR(-2) -2.912200 (0.41893) [-6.95154] LEAR(-3) 1.786901 (1.15130) [ 1.55207] D -0.367593

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(0.09892) [-3.71589] C 0.404548 (0.55046) [ 0.73493] R-squared 0.965199 Adj. R-squared 0.921699 Sum sq. resids 0.227166 S.E. equation 0.137588 F-statistic 22.18813 Log likelihood 27.66960 Akaike AIC -0.833543 Schwarz SC -0.072283 Mean dependent 1.032343 S.D. dependent 0.491696
Var Model of ROE of Foreign Banks
LROE LROE(-1) 1.111212 (0.40349) [ 2.75403] LROE(-2) 0.054312 (0.60217) [ 0.09019] LROE(-3) 0.079927 (0.34201) [ 0.23370] LCAR(-1) 1.061531 (0.41161) [ 2.57899] LCAR(-2) -0.842658 (0.69849) [-1.20640] LCAR(-3) 0.172190 (0.35051) [ 0.49125] LLQR(-1) -0.022663 (0.27685) [-0.08186] LLQR(-2) -0.696338

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(0.37165) [-1.87365] LLQR(-3) 0.554980 (0.41956) [ 1.32277] LEAR(-1) 0.412174 (0.21705) [ 1.89897] LEAR(-2) -2.751378 (0.39475) [-6.96989] LEAR(-3) 2.369656 (1.08480) [ 2.18441] D -0.343610 (0.09318) [-3.68771] C -1.153389 (2.79999) [-0.41193] R-squared 0.986342 Adj. R-squared 0.969269 Sum sq. resids 0.201522 S.E. equation 0.129590 F-statistic 57.77304 Log likelihood 29.34659 Akaike AIC -0.953328 Schwarz SC -0.192068 Mean dependent 3.474176 S.D. dependent 0.739236

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