MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY -o0o - TRẦN ĐÌNH KHẢI BANK INCOME STRUCTURE AND RISK: AN EMPIRICAL ANALYSIS OF VIETNAM COMMERCIAL BANKS MASTER OF BUSINESS ADMINISTRATION HO CHI MINH CITY, 2012 MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY -o0o - E Â1 TRẦN ĐÌNH KHẢI BANK INCOME STRUCTURE AND RISK: AN EMPIRICAL ANALYSIS OF VIETNAM COMMERCIAL BANKS MAJOR: BUSINESS ADMINISTRATION MAJOR CODE: 60.34.05 MASTER THESIS SUPERVISOR: Dr VÕ XUÂN VINH HO CHI MINH CITY, 2012 ACKNOWLEDGEMENT This thesis would not have been possible without the guidance and the help of several individuals who in one way or another contributed and extended their valuable assistance in the preparation and completion of this study First and foremost, my utmost gratitude to Dr Vo Xuan Vinh, whose sincerity and encouragement I will never forget Dr Vinh has been my inspiration as I hurdle all the obstacles in the completion this research Dr Vinh has spent plenty of time in many weeks to support me with his fully enthusiasm I also express my warm gratitude to all professors at Faculty of Business Administration, University of Economics in Hochiminh City for their teaching and sharing during my MBA course I have many thanks to my classmates who show their sharing and encouragements when I this thesis Last but not the least, I want to thank so much to my beloved wife who always understands and encourages me to complete my thesis especially in the hardly time of taking care of my newborn baby ABSTRACT This paper investigates the relationship between bank risks and product diversification of the Vietnam banking industry Employing a sample of Vietnam commercial banks for the period 2008–2011, the results indicate that banks expanding into non-interest income activities not present higher risk than banks that mainly supply loans However, considering size effects and splitting non-interest activities into both trading activities and commission and fee activities, we show that the link with risk is mostly accurate for small banks and essentially driven by commission and fee activities Whereas, for both of small and large banks, a higher share of trading activities is never associated with higher risk Keywords: Bank risk; Interest income; Non-interest income; Diversification CONTENTS ACKNOWLEDGEMENT ABSTRACT LIST OF TABLES ABBREVIATIONS CHAPTER 1: INTRODUCTION 1.1 BACKGROUND 1.2 RESEARCH PROBLEM 1.3 RESEARCH OBJECTIVE 1.4 RESEARCH METHODOLOGY AND SCOPE 10 1.5 STRUCTURE OF RESEARCH 10 CHAPTER 2: BASIC THEORETICAL BACKGROUND AND LITERATURE REVIEW 11 2.1 BANK RISK 11 2.2 BANK INCOME 13 2.3 DIVERSIFICATION .13 2.4 BANK RISK AND DIVERSIFICATION 15 2.5 HYPOTHESIS DEVELOPMENT 18 CHAPTER 3: DATA AND RESEARCH METHODS 19 3.1 MODEL 19 3.2 VARIABLES 20 3.2.1 DIVERSIFICATION VARIABLES 20 3.2.2 BANK RISK MEASURES 20 3.2.3 CONTROL VARIABLES 21 3.3 DATA 22 CHAPTER 4: RESULTS AND DISCUSSION 27 4.1 UNIVARIATE MEAN TESTS .27 4.1.1 BANK RISK AND INCOME STRUCTURE 27 4.1.2 INCOME STRUCTURE AND BANK CHARACTERISTICS .30 4.2 MULTIVARIATE REGRESSION ANALYSIS 32 CHAPTER 5: CONCLUSION 44 5.1 RESEARCH FINDINGS: 44 5.2 RESEARCH CONTRIBUTIONS: 45 5.3 RECOMMENDATIONS FOR FUTURE RESEARCH: 45 REFERENCES 46 APPENDIX 49 LIST OF TABLES Table 1: Descriptive statistics for Vietnam commercial banks, on average over the period 2008-2011 (%) Table 2: Descriptive statistics for small and large Vietnam commercial banks, on average over the period 2008-2011 (%) Table 3: Income structure and accounting indicators of risk for Vietnam commercial banks (2008-2011) Table 4: Income structure and bank characteristics for Vietnam commercial banks (2008-2011) Table 5: OLS estimations for the sample of 35 banks with M_NNII as the independent variable Table 6: OLS estimations for the first cohort of 13 small banks with M_NNII as the independent variable Table 7: OLS estimations for the second cohort of 22 large banks with M_NNII as the independent variable Table 8: OLS estimations for the sample of 35 banks with M_COM and M_TRAD as the independent variables Table 9: OLS estimations for the first cohort of 13 small banks with M_COM and M_TRAD as the independent variables Table 10: OLS estimations for the second cohort of 22 large banks with M_COM and M_TRAD as the independent variables ABBREVIATIONS NII _ Net interest income to net operating income NNII _ Net non interest income to net operating income COM _ Net commission and fee income to net operating income TRAD _ Net trading income to net operating income Q75 _ Third quartile Q25 _ First quartile LOANS _ loans to total assets; DEP _ deposits to total assets; EQUITY_ equity to total assets; EXPENSES _personnel expenses to total assets; ROA_ return on average assets; ROE_ return on average equity; TA _ total assets SDROA_ standard deviation of the return on average assets; SDROE_ standard deviation of the return on average equity; LLP_ ratio of loan loss provisions to net loans; ADZ_ Z-score; ADZP_ ‘‘ZP-score”; ADZP1_ measure of bank portfolio risk; ADZP2_ measure of leverage risk OLS _ Ordinary least squares HOSE_Hochiminh Securities Exchange HNX_Hanoi Securities Exchange OTC_ Over The Counter CHAPTER 1: INTRODUCTION 1.1 BACKGROUND Following more definitions of bank income structure in the world, bank income structures has two main components: interest income that stems from traditional activities such as giving loan and non-interest income that stems from nontraditional activities such as supplying services, trading services In the context of financial deregulation that took place in the seventies and in the eighties, western banking systems faced major changes in the form of increased competition, concentration and restructuring Banks have reacted to the new environment by adopting a proactive strategy widening the range of products they offer to their clients These changes mainly implied an increasing share of non-interest income in profits Non-interest income stems from traditional service charges (checking, cash management, letters of credit .) but also from new sources With the decline in interest margins induced by higher competition banks were incited to charge higher fees on existing or new services (cash withdrawal, bank account management, data processing .) As a result, structure of bank income experienced a dramatic change in the world In the eighties, non-interest income represented 19% of US commercial banks’ total income This share had grown to 43% of total income in 2001 (Stiroh, 2004) and increased from 10% in 1984 to 31% in 2011 In Europe, non-interest income has increased from 26% to 41% between 1989 and 1998 (European Central Bank, 2000) In Vietnam, non-interest income represented 20% of commercial banks’ total income and its share had increased 9% for period of 2008-2011 (State Bank of Vietnam, 2012) With the adoption of the new universal banking principle, commercial banks can compete on a wider range of market segments (investment banking, market trading ) Numerous studies questioned the implications of this new environment on bank risk The issue is of importance for the safety and soundness of the banking system and a major challenge for supervisory authorities The existing literature, mostly based on US banks, either focused on portfolio diversification effects risk return profile (Boyd et al., 1980; DeYoung & Roland, 2001; Kwan, 1998) or on incentives approaches (Boyd et al., 1998; John et al., 1994; Puri, 1996; Rajan, 1991) Few studies were able to show that the combination of lending and non-interest income activities allows for diversification benefits and therefore risk reduction Conversely, some papers find a significant positive impact of diversification on earnings volatility (DeYoung & Roland, 2001; Stiroh, 2004; Stiroh & Rumble, 2006) As noted by DeYoung & Roland (2001), three main reasons may explain this increase in risk Firstly, income from lending activities is likely to be relatively stable over time because switching and information costs make it costly for either borrowers or lenders to walk away from a lending relationship In contrast, income from noninterest income activities may suffer from larger fluctuations as it might be easier to switch banks for this type of activities than for lending Secondly, expanding non-interest income activities may imply a rise in fixed costs (for example, additional staff may be required), which increases the operational leverage of banks Conversely, once a lending relationship is established, the marginal cost 38 In Table as below, we consider the relationship between risks and diversification with M_COM, M_TRAD as a independent variable in our sample of 35 banks The results of this estimation indicate that the constant variable and independent variables (except DTA) has effect to the risk but the model is explained by only constant variable and control variables such as M_LOAN, M_ROA, with high significant The results also indicate that M_COM has effect to risks with positive effectiveness to risk indicators and negative effectiveness to insolvency risk indicators, however, with low significant In addition, M_TRAD has effect to risks with positive effectiveness to risk indicators ADZ, ADZP1 and negative effectiveness to others risk indicators, however, with low significant Therefore, the effectiveness of risk and diversification cannot be explained by the independent variable M_COM and M_TRAD in estimation of sample of 35 banks The total of independent variables explain high percentage of variance of each dependent variable such as SDROA, LLP (R2, R2(adj) at high value) The multicollinearity of variables in our model is dismissed due to the Durbin Watson Statistic is more than 2.0 With low Pro (F-stat) value