(Luận văn) the impact of credit risk on profitability in commercial banks in vietnam

ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep w n lo ad ju y th The IMPACT of CREDIT RISK on yi pl PROFITABILITY IN cOMMERCIAL BANKS ua al n in vietnam n va ll fu oi m at nh z z By Trong Quoc Tran Email : trong906@gmail.com Tel : 0907003639 k jm ht vb om l.c gm n a Lu n va y te re ac th HOCHIMINH CITY-2010 ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep w n lo ad ACKNOWLEDGEMENT ju y th yi pl I would like to express my thankfulness to all those who gave me the possibility ua al to complete this research project I am grateful all authors who have given me n a source of referential documents in the process of writing my thesis va n Especially, I am deeply indebted to my supervisor Dr Pham Huu Hong Thai, fu ll whose support, interest, encouragement and suggestion supported me during m oi the research and writing process of this research project at nh I also send to my gratitude to all teachers Financial and banking department has encouraged and help me this completes my thesis I would like to thank the z z library staff of the University of Economics Ho Chi Minh City for their vb k jm ht relentless effort in making access to research data and literature possible om l.c gm n a Lu n va y te re ac th Abstract By: Tran Quoc Trong ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep Nowadays, Credit risk management in banks has become more important because of the financial crisis that the world is experiencing Since granting w n credit is one of the main sources of income in commercial banks, the lo ad management of the risk related to that credit affects the profitability of the ju y th banks The study evaluates the impact of credit risk on profitability in yi Commercial Banks in Vietnam for the period of 2005-2009 Using financial pl ratios such as Return on Asset (ROA), Return on Equity (ROE), Non- al ua performing loan (NPL) analyze In the study try to find out how the credit risk n management affects the profitability in banks The study is limited to va n identifying the relationship of credit risk management on profitability of fu ll twenty commercial banks in Viet Nam The results of the study are limited to m oi banks in the sample and are not generalized for the all the commercial banks in nh at Viet Nam Furthermore, as the study only uses the quantitative approach and z focuses on the description of the outputs from SPSS, the reasons behind will z ht vb not be discussed and explained The quantitative method is used in order to jm fulfill the main purpose of the study The study have used regression model to k the empirical analysis In the model the study have defined ROE as gm profitability indicator while NPLR and CAR as credit risk management om l.c indicators The data is collected from the sample banks annual reports (20052009) and capital adequacy and risk management on financial reports (2005- a Lu 2009) in twenty commercial banks The findings and analysis reveal that credit n n va risk has effect on profitability in all twenty banks y te re Keywords: credit risk management, profitability, banks ac th By: Tran Quoc Trong ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep List of Acronyms w n lo ad Adj R2 Adjusted R-squared BCBS Basel Committee on Banking Supervision CAR Capital Adequacy Ratio CCF Credit Conversion Factors Coef Coefficient CRD Capital Requirements Directives FIRB Foundation Internal Rating-based FSA Financial Supervisory Authority ICAAP Internal Capital Adequacy Assessment Process IFRS International Financial Reporting Standards IRB Internal Rating-based LGD Loss Given Default N Number (of Observations) NI Net Income NPL Non-performing Loan NPLR Non-performing Loan Ratio PD Probability of DefaultP-value Probability Value R2 R-squared ROA Return on Assets ROE Return on Equity RORAC Return on Risk Adjusted Capital RWA Risk Weighted Asset SFSA Swedish Financial Supervisory Authority Signif Significance TL Total Loan TSE Total Shareholders’ Equity ju y th yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm n a Lu n va y te re ac th By: Tran Quoc Trong ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep TABLE OF CONTENT TITLE PAGES PAGES w n lo (2) Abstract (3) List of Acronyms (4) ad ACKNOWLEDGEMENT y th ju CHAPTER ONE (8) yi 1.Introduction pl (8) ua al 1.1 Statement of problems (10) 1.3 Research question (10) n 1.2 Problem Discussion n va (11) oi (12) nh 1.6 Layout of the study (12) m 1.5 Scope of the study ll fu 1.4 Objective of the study at CHAPTER TWO LITERATURE REVIEW z (13-14) z 2.1 The relationship between profitability and capital vb (14-15) jm ht 2.2 The relationship between capital and risk 2.3 The relationship between risk and profitability (18-19) (19-20-21-22) n a Lu 2.5 Theories (17-18) om 2.4.3.Capital and profitability : l.c 2.4.2 Credit risk management indicators gm 2.4.1 ROE – profitability indicator k 2.4 Previous Studies (15-16) (24) (28) ac 2.6.1 The Basel Accords th 2.6 Regulations (24-25-26) y 2.5.3 Bank Profitability te re 2.5.2 Credit risk management in banks n (23) va 2.5.1 Risks in banks (28-29-30) CHAPTER THREE METHODOLOGY By: Tran Quoc Trong ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep w n lo (31) 3.2 Hypothesis (31) 3.3 Sampling (32) 3.4 Data Collection (32) ad 3.1 Research approach (32-33) (33) 3.6.1 Dependent variable (33) (33) yi 3.6 Applied regression model al ju y th 3.5 Data analyzing instruments pl ua 3.6.2 Independent variables (34-35-36-37) n 3.6.3 Regression analysis explained va (37-38) n 3.7.Reliability and validity fu ll CHAPTER FOUR : OVERVIEW OF THE COMMERCIAL BANKING oi m SYSTEM IN VIETNAM nh at 4.1.The commercial banking system of Vietnam was the process of z transition from mono-banking system to commercial banking system (39) z (39-40) ht vb 4.2 Role of commercial banks in the economy jm 4.3 Banking system of the role of trade in Vietnam after 20 years (40-42) (42-43) k 4.4.Opportunities for Vietnam's commercial banking system gm 4.5 The difficulties and challenges for Vietnam's banking system (44-45) 5.1Overview of the banks studied (46-48) a Lu 5.2 Return on Equity (ROE) om l.c CHAPTER FIVE : EMPIRICAL RESULT AND DISCUSSION (50-52) n (54-55) 5.4 Capital Adequate Ratio (CAR) (56-57) 5.6.Basel I and basel II application affect CHAPTER SIX : CONCLUSION AND SUGGESTIONS (60-61) n va 5.3 Non-Performing Loan (NPLR) y te re th 6.1 Conclusion By: Tran Quoc Trong ac 6.1 Conclusion (66-67) ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep CHAPTER ONE w INTRODUCTION n lo ad y th Introduction ju In this chapter, we present the background of the thesis followed by the yi pl problem statement The discussion also contains the motivation for our thesis ua al Finally, we present the research question, the purpose of this thesis and limit n the area of the study va n 1.1 Statement of problems fu ll Credit activities are crucial of Vietnam banking system, They bring 80-90% to m oi income for each bank, but the risks are not less Credit risk will be higher than at nh the enormous influence to business banking Facing the opportunities and z challenges of the process of international economic integration, the issue of z vb raising the competitiveness of the domestic commercial banks with foreign jm ht commercial banks, in particular improving the quality of credit, risk reduction k has become urgent Besides, the world economic situation is complicated and gm the risk of increasing the credit crisis Vietnam is a country with open economy om l.c should not avoid the effects of the world economy Facing this situation, requires commercial banks of Vietnam must improve the management of credit a Lu risk, limited to the minimum possible risks, causing potential risks n va Managing credit risk in financial institutions is critical for the survival and n growth of the financial institutions In the case of banks, the issue of credit risk te re is even of greater concern because of the higher levels of perceived risks y debtor’s non-payment of a loan or other forms of credit As they default, delay By: Tran Quoc Trong ac that they find themselves in Credit risk refers to the risk of loss because of th resulting from some of the characteristics of clients and business conditions ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep in repayments, restructuring of borrower repayments and bankruptcy are also considered as additional risks When it comes to banking, credit risk is w n apparent on lending services to clients There is the need for an effective lo ad employment of credit scorecard for the purpose of ranking potential and ju y th existing customers according to risk In this will be based the appropriate yi measures to be applied by the banks Nevertheless, banks charge higher price pl for higher risk customers Credit limits and faced by lenders to consumers, al ua lenders to business, businesses and even individuals Credit risks, nevertheless, n are most encountered in the financial sector particularly by the institutions va n such as banks Credit risk management therefore is both a solution and a fu ll necessity in the banking setting The global financial crisis also requires the m oi banks to regain enough confidence by the public not only for the financial nh at institutions but also the financial system in general and to not just rely on the z financial aid by the governments and central banks It is critical for the banks z jm exemption ht vb to engage in better credit risk management practices Banks are not an k The banks of Vietnam as well as the other over all the World are required to gm follow Basel II capital adequacy framework from 2007 Basel II aims to build om l.c on a solid foundation of prudent capital regulation, supervision, and market discipline, and to enhance further risk management and financial stability a Lu However, it is worth mentioning that regulatory and deregulatory transitions n n va usually end up with the same result The exposed risk – the main and most importance of this risk is increased by the fact that it is linked to the problem techniques, wider than Basel I did The goal is to improve the credit risk By: Tran Quoc Trong ac studied For this reason, Basel II considers varieties of credit risk measurement th of collateral Therefore, it is in need of being deliberately examined and y te re difficult one to identify – is the credit risk in the particular current case The ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep management quality without constraining banks’competitiveness Regulations should be interactive or flexible to be successful because of rapidly changing w n technological, political, and economical circumstances Credit risk lo ad measurement tools presented in Basel II intended to be flexible The banks can ju y th either choose from the proposed options or employ their own as long as it yi gives sound and fair results The importance of the credit risk management and pl its impact on profitability has motivated us to pursue this study We assume al ua that if the credit risk management is sound, the profit level will be satisfactory n The other way around, if the credit risk management is poor, the profit level va n will be relatively lower Because the less the banks loss from credits, the more fu ll the banks gain.The profitability is the indicator of credit risk management The m oi central question is how significant is the impact of credit risk management on at z 1.2 Problem Discussion nh profitability z ht vb The importance of the credit risk and its impact on profitability has motivated jm us to pursue this study We assume that if the credit risk management is sound, k the profit level will be satisfactory The other way around, if the credit risk gm management is poor, the profit level will be relatively lower Because the less om l.c the banks loss from credits, the more the banks gain Profitability is the indicator of credit risk management The central question is how significant is a Lu the impact of credit risk management on profitability This thesis is an n va The discussed background and problem formulation make us to have the 1.4 Objective of the study By: Tran Quoc Trong ac commercial banks in Vietnam ? th following research question: How does credit risk affect the profitability in y te re 1.3 Research question n endeavor to find the answer ng Master’s thesis Supervisor : Dr Pham Huu Hong Thai hi ep The purpose of the research is to describe the impact level of credit risk on profitability in twenty commercial banks in Vietnam w n The study is to test the following hypothesis by econometric model : lo ad H1: Banks with higher profitability (ROE, ROA) have lower loan losses (Non- ju y th Performing Loans/ Total Loans) yi H2: Banks with higher interest income (net interest/Average total assets, pl interest net /total income) also have lower bad loans (NPL) al ua H3: The growth of ROE/ ROA may also depend on the capitalization of the n banks and operating profit margin If a bank is highly capitalized through the va n risk-weighted capital adequacy ratio (RWCAR) or Tier capital adequacy fu ll ratio (CAR), the expansion of ROE will be retarded m oi we test the hypothesis using the following regression model: nh at P(ROA/ROE)= α+β1NPLR+ β2CAR+ ε z Using data on 20 commercial banks in Vietnam and our results show no jm ht vb 1.5 Scope of the study z rejection by ourhypothesis k The research is limited on evaluate the impact of credit risk on profitability in gm the twenty Banks in Vietnam Thus, the other risks mentioned in Basel om l.c Accords are not discussed Due to the unavailability of information in annual reports, our sample only contains twenty largest commercial banks and their a Lu years’ annual reports from 2005 to 2009 respectively Since the banks in n n va sample rejected to participate in our internet based survey, the primary data the results of the study are limited to twenty commercial banks in the sample By: Tran Quoc Trong 10 ac uses the quantitative approach and focus on the description of the outputs from th and are not generalized for all the banks in Vietnam Finally, as the study only y te re was not possible to obtain Considering the above mentioned circumstances, ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w n Coefficients lo Coefficients Unstandardized Coefficients Correlations ad Standardized Collinearity Statistics t 3,598 NPLR_BASEL_II -1,761 1,656 CAR_BASEL_II -,593 ,260 5,811 ,000 -,161 -1,064 ,294 -,346 -2,282 ,028 Zero-order Partial -,193 p 20,906 Sig Part Tolerance VIF -,172 -,161 ,992 1,008 -,351 -,345 ,992 1,008 uy i (Constant) t Beta -,361 an u Std Error l a l B h y j Model a Dependent Variable: ROE_BASEL_II v an f ul l Collinearity Diagnosticsa m Model on Eigenvalue Condition Index (Constant) 1 2,736 1,000 ,01 ,04 ,234 3,417 ,03 ,95 ,030 9,570 ,96 ,01 oi n Variance Proportions Dimensi NPLR_BASEL_II CAR_BASEL_II h a t z ,01 z ,04 v b h t ,95 k jm a Dependent Variable: ROE_BASEL_II gm Maximum Predicted Value 7,3585 14,9869 Residual -1,03707E1 Std Predicted Value -2,011 Std Deviation N 11,8705 2,24422 40 14,85267 ,00000 5,22062 40 1,389 ,000 1,000 40 L u a n v a n ey t re By: Tran Quoc Trong Mean c o m Minimum l Residuals Statisticsa 82 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai 2,771 ,000 ,974 w -1,935 40 n Std Residual lo ad a Dependent Variable: ROE_BASEL_II t h y j uy i Regression p l a l an u [DataSet1] C:\Users\LENOVO\Documents\ABC.sav Std Deviation N ROA 1,5940 ,80887 100 NPLR ,7481 ,49928 100 CAR 12,8013 3,04983 100 ul l f Mean an v Descriptive Statistics m h oi n a t z z CAR ROA 1,000 -,166 ,389 NPLR -,166 1,000 ,102 CAR ,389 ,102 ROA ,050 ,000 NPLR ,050 ,157 CAR ,000 ,157 100 100 b h t NPLR k ROA jm Pearson Correlation v Correlations gm l 100 v a n ey t re By: Tran Quoc Trong L ROA u a n N c o m Sig (1-tailed) 1,000 83 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai CAR 100 100 100 w 100 lo 100 n 100 ad NPLR t h y j uy i Variables Entered/Removedb Variables Entered Removed Method CAR, NPLRa Enter an u Model l a l p Variables an v a All requested variables entered b Dependent Variable: ROA f ul l m oi n Model Summaryb h R R Square Adjusted R Square Estimate ,440a ,194 ,177 ,73374 R Square Change Change Statistics F Change df1 df2 Sig F Change Durbin-Watson 11,656 97 ,00002906 1,316 z Model a t z Std Error of the v jm b h t a Predictors: (Constant), CAR, NPLR ,194 b Dependent Variable: ROA k gm Model Sum of Squares 12,551 Residual 52,222 v a n ey t re By: Tran Quoc Trong Mean Square F Sig 6,275 11,656 ,00002906 97 ,538 L Regression df u a n c o m l ANOVAb 84 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w 64,772 99 n Total lo ad a Predictors: (Constant), CAR, NPLR h y j t b Dependent Variable: ROA uy i l a l p Coefficientsa Standardized u NPLR -,336 ,148 CAR ,109 ,024 1,383 ,170 -,197 -,207 -2,262 ,026 -,630 ,410 4,473 ,00000294 ,060 Collinearity Statistics Zero-order Partial Part Tolerance VIF -,041 -,166 -,224 -,206 ,990 1,010 ,157 ,389 ,414 ,408 ,990 1,010 1,104 a t z h a Dependent Variable: ROA Upper Bound f ,328 Lower Bound m ,453 Sig ul l (Constant) t Beta oi n Std Error Correlations an B 95% Confidence Interval for B v Model Coefficients an Unstandardized Coefficients z -,102 NPLR -,102 1,000 CAR ,001 ,000 NPLR ,000 Covariances b h t 1,000 gm CAR Correlations ,022 u a n L a Dependent Variable: ROA c o m l NPLR k CAR jm Model v Coefficient Correlationsa v a n ey t re By: Tran Quoc Trong 85 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w n Collinearity Diagnosticsa lo Eigenvalue Condition Index (Constant) NPLR CAR 1 2,755 1,000 ,01 ,03 ,01 ,218 3,553 ,03 ,96 ,04 ,027 10,140 ,96 ,01 ,95 t on h y j Model ad Variance Proportions Dimensi uy i p l a l an u a Dependent Variable: ROA v an f ul l m Maximum Mean Std Deviation N Predicted Value ,6750 2,5193 1,5940 ,35605 Residual -1,15144 3,31219 ,00000 ,72629 Std Predicted Value -2,581 2,599 ,000 1,000 Std Residual -1,569 4,514 ,000 ,990 100 z v b h t jm 100 100 100 k a Dependent Variable: ROA h Minimum a t z oi n Residuals Statisticsa gm l c o m Regression L u a n [DataSet1] C:\Users\LENOVO\Documents\ABC.sav v a n ey t re By: Tran Quoc Trong 86 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w n Std Deviation N ROA_BASEL_I 1,5932 ,75905 57 NPLR_BASEL_I ,7374 ,50092 57 CAR_BASEL_I 12,6205 3,00051 57 h y j t Mean ad lo Descriptive Statistics uy i p u l a l an NPLR_BASEL_I CAR_BASEL_I ROA_BASEL_I 1,000 -,260 ,407 NPLR_BASEL_I -,260 1,000 ,074 CAR_BASEL_I ,407 ,074 1,000 ROA_BASEL_I ,025 NPLR_BASEL_I ,025 a t z CAR_BASEL_I ,001 ,291 ROA_BASEL_I 57 57 57 NPLR_BASEL_I 57 57 57 CAR_BASEL_I 57 57 57 Pearson Correlation m h ,001 z v b h t k jm N oi n Sig (1-tailed) ul l f ROA_BASEL_I an v Correlations ,291 gm l c o m Variables Entered/Removedb Variables Entered L Model u a n Variables Removed v a n ey t re By: Tran Quoc Trong Method 87 t h a c ng p hi e Supervisor : Dr Pham Huu Hong Thai w CAR_BASEL_I, Enter ad lo NPLR_BASEL_Ia n Master’s thesis a All requested variables entered t h y j b Dependent Variable: ROA_BASEL_I uy i p l a l Model Summaryb u Change Statistics an Std Error of the R Square Adjusted R Square Estimate R Square Change F Change ,501a ,251 ,223 ,66914 ,251 9,030 df1 df2 Sig F Change Durbin-Watson 54 ,0004-4 1,445 v R an Model f ul l a Predictors: (Constant), CAR_BASEL_I, NPLR_BASEL_I m a t z h oi n b Dependent Variable: ROA_BASEL_I ANOVAb Mean Square Regression 8,086 4,043 Residual 24,178 54 ,448 Total 32,265 56 v df F Sig 9,030 ,00004-4 k jm b h t Sum of Squares z Model gm b Dependent Variable: ROA_BASEL_I c o m l a Predictors: (Constant), CAR_BASEL_I, NPLR_BASEL_I L u a n v a n ey t re By: Tran Quoc Trong Coefficientsa 88 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w (Constant) ,549 ,400 NPLR_BASEL_I -,442 ,179 CAR_BASEL_I ,109 ,030 t Sig Lower Bound Upper Bound Zero-order 1,372 ,176 -,253 1,351 -,292 -2,470 ,017 -,801 -,083 ,429 3,633 ,001 ,049 ,168 Beta Collinearity Statistics Partial Part Tolerance VIF -,260 -,319 -,291 ,994 1,006 ,407 ,443 ,428 ,994 1,006 t Std Error Correlations ad B 95% Confidence Interval for B Coefficients h y j Model lo Unstandardized Coefficients n Standardized uy i p l a l an u a Dependent Variable: ROA_BASEL_I v an f ul l Coefficient Correlationsa CAR_BASEL_I 1,000 -,074 NPLR_BASEL_I -,074 1,000 CAR_BASEL_I ,001 ,000 NPLR_BASEL_I ,000 ,032 Correlations a t z z Covariances m NPLR_BASEL_I h CAR_BASEL_I oi n Model v b h t k jm a Dependent Variable: ROA_BASEL_I gm l c o m L u a n v a n ey t re By: Tran Quoc Trong 89 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w n Collinearity Diagnosticsa lo Eigenvalue Condition Index (Constant) NPLR_BASEL_I CAR_BASEL_I 1 2,748 1,000 ,01 ,03 ,01 ,225 3,494 ,03 ,95 ,04 ,026 10,208 ,96 ,01 ,95 t on h y j Model ad Variance Proportions Dimensi uy i p l a l an u a Dependent Variable: ROA_BASEL_I v an Maximum Mean Std Deviation N Predicted Value ,5268 2,2929 1,5932 ,38000 57 Residual -,97070 2,71450 ,00000 ,65708 57 Std Predicted Value -2,806 1,841 ,000 1,000 Std Residual -1,451 4,057 ,000 ,982 57 h oi n m Minimum a t z ul l f Residuals Statisticsa 57 z v k jm b h t a Dependent Variable: ROA_BASEL_I gm [DataSet1] C:\Users\LENOVO\Documents\ABC.sav L Std Deviation v a n Mean u a n Descriptive Statistics ey t re By: Tran Quoc Trong c o m l Regression N 90 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai ,7400 ,52042 40 CAR_BASEL_II 13,0305 3,31482 40 w NPLR_BASEL_II lo 40 n ,53997 h y j t 1,4022 ad ROA_BASEL_II uy i l a l p Correlations ROA_BASEL_II NPLR_BASEL_II CAR_BASEL_II u ,091 CAR_BASEL_II ,250 ,091 1,000 ROA_BASEL_II ,226 ,060 NPLR_BASEL_II ,226 ,288 CAR_BASEL_II ,060 ,288 ROA_BASEL_II 40 40 NPLR_BASEL_II 40 40 CAR_BASEL_II 40 40 v 1,000 f -,122 an NPLR_BASEL_II m ,250 h oi n -,122 a t z N 1,000 ul l Sig (1-tailed) ROA_BASEL_II an Pearson Correlation 40 z 40 v k jm b h t 40 gm Variables Entered/Removedb Variables Entered CAR_BASEL_II, c o m Model l Variables Removed L a u a n NPLR_BASEL_II v a n ey t re By: Tran Quoc Trong Method Enter 91 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w n Variables Entered/Removedb lo Model Variables Entered Method Enter h y j t Removed ad Variables CAR_BASEL_II, uy i NPLR_BASEL_II a p l a l a All requested variables entered u an b Dependent Variable: ROA_BASEL_II v an ul l oi n m Std Error of the f Model Summaryb R R Square Adjusted R Square Estimate R Square Change ,289a ,084 ,034 ,53072 ,084 a t z h Model a Predictors: (Constant), CAR_BASEL_II, NPLR_BASEL_II Change Statistics F Change df1 df2 Sig F Change Durbin-Watson 1,686 37 ,199 1,397 z jm b h t v b Dependent Variable: ROA_BASEL_II Regression ,950 Residual 10,422 Total 11,371 39 F Sig ,475 1,686 ,199a Mean Square l 37 gm df Sum of Squares c o m Model k ANOVAb ,282 L u a n a Predictors: (Constant), CAR_BASEL_II, NPLR_BASEL_II v a n ey t re By: Tran Quoc Trong 92 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w F Sig Regression ,950 ,475 1,686 ,199a Residual 10,422 37 ,282 Total 11,371 39 lo Mean Square h y j df t Sum of Squares ad Model n ANOVAb uy i p an u l a l b Dependent Variable: ROA_BASEL_II v an Coefficientsa ,356 NPLR_BASEL_II -,152 ,164 CAR_BASEL_II ,043 ,026 2,686 ,011 -,146 -,926 ,263 1,663 m ,957 Sig Lower Bound Upper Bound ,235 1,679 ,360 -,484 ,105 -,009 h (Constant) t Beta z Std Error 95% Confidence Interval for B oi n B Coefficients a t z Model ul l Unstandardized Coefficients f Standardized Correlations Collinearity Statistics Zero-order Partial Part Tolerance VIF ,180 -,122 -,151 -,146 ,992 1,008 ,095 ,250 ,264 ,262 ,992 1,008 v k jm b h t a Dependent Variable: ROA_BASEL_II gm Coefficient Correlationsa Model CAR_BASEL_II NPLR_BASEL_II l Correlations CAR_BASEL_II c o m 1,000 -,091 -,091 1,000 CAR_BASEL_II ,001 ,000 NPLR_BASEL_II ,000 ,027 u a n L NPLR_BASEL_II Covariances v a n ey t re By: Tran Quoc Trong 93 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai w lo Correlations -,091 1,000 CAR_BASEL_II ,001 ,000 NPLR_BASEL_II ,000 ,027 Covariances h y j NPLR_BASEL_II p -,091 uy i 1,000 l a l CAR_BASEL_II t CAR_BASEL_II NPLR_BASEL_II ad Model n Coefficient Correlationsa an u a Dependent Variable: ROA_BASEL_II v an ul l f Collinearity Diagnosticsa Model on Eigenvalue Condition Index (Constant) 1 2,736 1,000 ,01 ,04 ,234 3,417 ,03 ,95 ,030 9,570 ,96 ,01 m Variance Proportions Dimensi oi n NPLR_BASEL_II CAR_BASEL_II a t z h ,01 ,04 z b h t v ,95 a Dependent Variable: ROA_BASEL_II k jm gm l c o m L u a n Residuals Statisticsa v a n Minimum ey t re By: Tran Quoc Trong Maximum Mean Std Deviation N 94 t h a c ng p hi e Master’s thesis Supervisor : Dr Pham Huu Hong Thai Residual -,81766 1,52347 ,00000 ,51693 40 Std Predicted Value -1,603 2,303 ,000 1,000 40 Std Residual -1,541 2,871 ,000 ,974 40 w 40 lo ,15605 n 1,4022 t 1,7616 ad 1,1521 h y j Predicted Value uy i a Dependent Variable: ROA_BASEL_II p u l a l an v an f ul l m h oi n a t z z v b h t k jm gm l c o m L u a n v a n ey t re By: Tran Quoc Trong 95 t h a c ng p hi e w n lo ad Supervisor : Dr Pham Huu Hong Thai Master’s thesis t h y j uy i p u l a l an v an f ul l m h oi n a t z z v b h t k jm gm l c o m L u a n v a n t re ey t h a c