Model for risk quantification in guaranteed asset at asia commercial joint stock bank

RESEARCH PROJECT BMBR5103 Model for Risk Quantification in Guaranteed Asset Valuation at Asia Commercial Joint Stock Bank STUDENT’S FULL NAME : THANH QUANG TRUNG STUDENT ID : CGS00018500 INTAKE : SEPTEMBER, 2014 ADVISOR’S NAME & TITLE : ASSOC.PROF.DR PHAN DINH NGUYEN December, 2015 Advisor’s assessment Advisor’s signature ABSTRACT The thesis "Model for Risk Qualification in Guaranteed Asset Valuation at Asia Commercial Joint Stock Bank" aims to identify the factors that cause valuation risks of guaranteed assets, quantify probability of risks and identify important factors that influence valuation risks of guaranteed assets, and last but not least propose measures to minimize risks and remedy losses from such risks Thesis provided points of view, the existence of risk, identification, assessment and study of valuation risks of guaranteed assets To identify and assess the valuation risks of guaranteed assets, Thesis built a factor analysis model and used linear regression analysis to find out which factors cause valuation risks of guaranteed assets Additionally an assessment scale of the valuation risks of guaranteed assets was created The scale of valuation risks includes 22 variables and scores similarly to Likert scale and its reliability is tested by Cronbach's Alpha Some new points of the thesis include the application of risk scale in valuation of guaranteed assets, creation of a factor analysis model and the use of linear regression analysis to identify all the factors resulting in valuation risks of guaranteed assets Based on results of the regression analysis, the thesis proposed some solutions and recommendations to minimize risks and overcome losses resulting from such risks Contents ABBREAVIATIONS LIST OF FIGURES LIST OF TABLES CHAPTER ONE INTRODUCTION 1.1 Background of the study 1.2 Research Objectives 12 1.3 Research questions 13 1.4 Scope of the study 13 LITERATURE REVIEW 15 2.1 Definition of relevant concepts 15 2.2 Factors leading to valuations risks 17 2.3 Risk management in valuation 19 CHAPTER THREE: RESEARCH METHODOLOGY 24 3.1 Research Design 24 3.2 Qualitative method 25 3.3 Quantitative method 25 3.4 Data Resource 27 3.5 RESEARCH SAMPLES 29 3.6 ADJUSTMENTS OF RESEARCH MODEL 29 3.7 CREATION OF MEASUREMENT SCALES 31 DATA ANALYSIS AND RESULTS 36 4.1 INTRODUCTION 36 4.2 ASSESSMENT ON MEASURING SCALE 36 4.3 TESTING MEASURING SCALE 39 4.4 ANALYSIS OF FACTORS 41 4.5 MULTIVARIATE REGRESSION ANALYSIS 48 CHAPTER V - SOLUTIONS AND RECOMMENDATIONS 56 5.1 SPECIFIC SOLUTIONS TO LIMIT RISKS IN BUSINESS ON PRICE VERTIFICATION OF SECURED ASSETS 56 5.2 GENERAL SOLUTIONS TO LIMIT RISK IN BUSINESS ON VALUATION OF SECURED ASSETS 58 5.3 RECOMMENDATION 62 CONCLUSION 66 APPENDICES 72 APPENDIX 1: QUESTIONNAIRE Error! Bookmark not defined APPENDIX 2: RELIABILITY ANALYSIS Error! Bookmark not defined ABBREAVIATIONS ACB: Asia Commercial Joint Stock Bank RE: Real estate CRE: Comparable real estate for VRE: Valuated real estate CA: Cronbach's Alpha EFA: Exploratory Factor Analysis B: Bank V: Price Valuation CJS: Commercial Joint Stock GA: Guaranteed Assets LIST OF FIGURES Figure 2.1: Initial theoretical research model Figure 3.1: Research Process Figure 3.2: Research model Figure 4.1: Frequency of standardized residuals LIST OF TABLES Table 3.1: Scale of Risks in Business Valuation Table 3.2: Scale of Objects in Valuation Table 3.3: Scale of Operating Environment of the organization Table 3.4: Scale of Valuer's Awareness Table 3.5: Scale of Information Environment Table 3.6: Scale of Legal Environment Table 4.1: Statistical results of variables affecting valuation risks Table 4.2: Test results of scales Table 4.3: Test results of KMO and Bartlett's Test of Sphericity of Scales Table 4.4: Table of Communalities (Factor Loading) Table 4.5: Initial Eigenvalues in Total Variance Explained Table 4.6: Rotated component matrix Table 4.7: Interpretation of factors affecting risk level in valuation of Asia Commercial Joint Stock Bank Table 4.8: Independent variable included in regression analysis Table 4.9: Results of multivariate regression CHAPTER ONE INTRODUCTION 1.1 Background of the study There are many important studies in the world related to the valuation of real estate for various purposes The research "Estimating Land Values" by Ted Gwartney Arden and Delaware in July 1999 is a typical instance In their research, the authors studied and introduced a number of principles as well as methods for determining the value of land In her "EMS and Land Valuation" research, Catherine Nind (2002) mainly referred to the assessment of land values taking into account of environmental factors Catherine Nind focused on methods for determining the values of land resources based on ensuring environmental factors By studying market transactions of real estate in the period from 1994 - 2000 and effects of values of real estate for mortgage on Nigerian credit institutions' lending activities, Aluko and Bioye Tajudeen concluded that the market values of real estate were a fundamental basis for estimating values of mortgaged real estate The authors applied multiple regression models to estimate market values of mortgaged real estate This value will constitute the maximum limits that credit institutions should not exceed to avoid risks for lending activities However, in those studies, the authors only pointed out that such prices would not be maintained in the future The authors also concluded that lending rates for mortgages depended significantly on the development of real estate market at the time of valuation and valuer's views on values Therefore, the appraised values are temporary only Any movements out of valuation time will affect the appraised values of real estate Kwong Chaw, Wailai (2002) studied valuation methods for real estate as guaranteed assets for loans at banks and credit institutions of China This research mainly focused on methods applied to valuation of mortgage Particularly, Kwong Chaw and Wailai studied deeply into two basic methods including costbased and income-based methods for determining values of mortgaged real estate According to them, values of real estate would be calculated based on their constituted incomes and costs Nevertheless, the two authors only identified valuation methods not process or organization for valuation of mortgaged real estate In general, these studies were conducted with relatively complete information and applied in a close legal system In Vietnam, there are also a number of research topics related to real estate valuation In his "Model for Risk Qualification in Asset Valuation" thesis for Economic Master Degree, Nguyen Khanh Tuyen presented his views on the existence of risk and identification, assessment and study of valuation risks of appraisal firms To identify and assess the valuation risks of guaranteed assets, he built a factor analysis model and used linear regression analysis to find out which factors cause risks in valuation as well as probability of each profile for valuation He also built a unidirectional scale of risk assessment in valuation Additionally an assessment scale of the valuation risks of guaranteed assets was created The scale of valuation risks includes 15 variables and scores similarly to Likert scale and its reliability was tested by Cronbach's Alpha; unidirectional property of scale was also confirmed through factor analysis Some new points of this thesis included the application of risk scale in valuation, application of factor analysis and linear regression analysis together with non-linear relationships to identify main factors affecting valuation risks and risk probability of each profile for valuation 10 Verification Policy 771 Processing Time 770 Orientation of the leaders 750 Bring records to external organizations 745 Incorrectly identify the technical specifications 674 Appraiser having malicious intent 653 Legal records 638 Breach in Appraisal Process 635 Unfavorable Planning 610 Legal System 514 -.673 Guiding legal documents 598 -.669 Specifications of Object of Price Verification are dissimilar with the compared real estate 563 Specifications of Object of Price Verification are complex 513 -.520 566 501 98 533 Incorrectly identify the wrong location 605 636 Extraction Method: Principal Component Analysis a components extracted Rotated Component Matrixa Component Developing incomplete information 885 No using reviews 814 Verification Policy 768 Information on sale 756 Processing Time 727 Breach in Appraisal Process 847 Incorrectly identify the technical specifications 843 Incorrectly identify the wrong location 751 99 558 Orientation of the leaders 733 Appraiser having malicious intent 730 Specifications of Object of Price Verification are dissimilar with the compared real estate 908 Specifications of Object of Price Verification are complex 893 Legal records 845 Unfavorable Planning 815 Guiding legal documents 910 Legal System 905 Bring records to external organizations 553 641 Testing on the previous evaluation results 610 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization a Rotation converged in iterations 100 Component Transformation Matrix Component 638 498 421 409 -.160 344 555 -.741 -.097 -.664 702 238 -.747 438 150 477 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization Component Score Coefficient Matrix Component Legal records Unfavorable Planning Specifications of Object of Price Verification are dissimilar with the compared real estate -.056 -.029 290 003 003 -.070 277 -.032 -.083 -.042 329 000 101 Specifications of Object of Price Verification are complex -.103 -.020 329 -.010 Verification Policy 237 -.089 -.036 -.007 Processing Time 210 -.089 -.014 011 Bring records to external organizations 090 -.059 -.026 167 Testing on the previous evaluation results -.002 071 -.016 167 Orientation of the leaders 036 208 -.019 -.080 Appraiser having malicious intent 081 209 -.024 -.174 Incorrectly identify the wrong location -.260 309 -.033 234 Incorrectly identify the technical specifications -.174 318 -.027 102 Breach in Appraisal Process -.002 284 -.039 -.124 No using reviews 263 -.021 -.056 -.102 Developing incomplete information 315 -.104 -.050 -.093 Information on sale 182 010 -.029 -.012 102 Legal System -.079 -.053 -.012 344 Guiding legal documents -.042 -.069 -.010 328 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization Component Scores Component Score Covariance Matrix Componen t 1.000 000 000 000 000 1.000 000 000 000 000 1.000 000 000 000 000 1.000 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization Component Scores 103 APPENDIX Multivariate Regression Variables Entered/Removedb Model Variables Entered Variables Removed Number of Working Years, Gender of the surveyed person, legal environment of the organization, valued object, awareness of appraiser and Environment information of organizations, Title of surveyed persona Method Enter a All requested variables entered b Dependent Variable: Risk on Price verification 104 Model Summaryb Mode l R Change Statistics Std R Adjuste Error of Durbin Squar d R the R Square Sig F e Square Estimate Change F Change df1 df2 Change Watson 811a 658 650 606 658 80.360 292 000 1.202 a Predictors: (Constant), number of working years, gender of the surveyed person, legal environment of the organization, valued object , awareness of valuer and information environment of the organization, title of the surveyed person b Dependent Variable: Risk on Price verification ANOVAb Model Sum of Squares df Mean Square Regression 206.254 29.465 Residual 107.066 292 367 Total 313.320 299 F 80.360 Sig .000a a Predictors: (Constant), number of working years, gender of the surveyed person, legal environment of the organization, valued object, awareness of valuer and information environment of the organization, title of the surveyed person b Dependent Variable: Risk on Price verification 105 Coefficientsa Standardi zed Unstandardized Coefficien Coefficients ts Model Std Error B (Constant) Beta Collinearity Statistics t Sig Toleranc e VIF 3.438 210 16.398 000 Information Environment of Organization 170 039 166 4.337 000 801 1.249 Appraiser's Awareness 087 036 085 2.383 018 923 1.083 Valued Object 673 039 658 17.289 000 808 1.237 Legal Environment of Organization 126 036 123 3.529 000 962 1.039 Gender of the surveyed person -.076 073 -.036 -1.034 302 988 1.012 Title of surveyed person -.378 120 -.131 -3.136 002 673 1.487 Number of working years -.192 062 -.131 -3.082 002 652 1.534 106 ANOVAb Model Sum of Squares df Mean Square F Regression 206.254 29.465 Residual 107.066 292 367 Total 313.320 299 Sig 80.360 000a a Predictors: (Constant), number of working years, gender of the surveyed person, legal environment of the organization, valued object, awareness of valuer and information environment of the organization, title of the surveyed person a Dependent Variable: Risk on Price verification Collinearity Diagnosticsa Variance Proportions Lega Infor l matio Envi n ron Enviro ment nment Appra of Dim of iser's Orga Mod ensi Eigenvalu Conditio (Constan Organ Aware Valued nizat el on e n Index t) ization ness Object ion 1 3.378 1.000 00 00 107 00 00 00 Gend er of the surve yed perso n 03 Num Title of ber of surveye worki d ng person years 00 00 1.017 1.822 00 05 74 00 08 02 00 00 1.007 1.831 00 22 05 40 15 00 00 00 1.000 1.838 00 30 08 38 06 00 00 00 1.000 1.838 00 22 02 01 67 00 00 00 543 2.493 00 00 05 00 01 94 01 00 039 9.315 12 01 02 16 04 01 99 11 016 14.696 87 20 05 04 00 00 00 88 a Dependent Variable: Risk on Price verification Residuals Statisticsa Minimum Predicted Value Maximum Mean Std Deviation N 84 4.19 2.34 831 300 Residual -1.696 2.557 000 598 300 Std Predicted Value -1.810 2.224 000 1.000 300 108 Std Residual -2.801 4.222 a Dependent Variable: Risk on Price verification 109 000 988 300 APPENDIX SPEARMAN GRADING CORRELATION VALUATION Correlations Informat ion Environ ment of PHAND Organiz U ation Spear PHAND Correlation man's U Coefficient rho Sig (2tailed) N Informat Correlation ion Coefficient Environ ment of Sig (2Organiz tailed) ation N Apprais Correlation er's Coefficient 1.000 ** 167 004 300 167** 004 300 -.146* 300 Legal Appr Enviro aiser' nment s of Awar Valued Organi eness Object zation Gende r of the survey ed person 146* 206** 098 011 000 300 020 1.000 727 018 757 300 300 020 1.00 002 110 Title of surveye d person Numbe r of workin g years -.027 324** -.568** 091 640 000 000 300 300 300 300 055 300 132* -.006 022 920 340 000 300 300 300 300 034 -.091 -.414** 197** 300 169** Awaren Sig (2ess tailed) N Valued Correlation Object Coefficient Legal Environ ment of Organiz ation 011 727 300 300 300 206** 970 556 115 001 003 300 300 300 300 -.018 002 1.000 -.003 300 -.420** -.254** -.043 Sig (2tailed) 000 757 970 959 456 000 000 N 300 300 300 300 300 300 300 Correlation Coefficient 098 132* 034 -.003 Sig (2tailed) 091 022 556 959 N 300 300 300 Gender Correlation of the Coefficient surveye d person Sig (2tailed) N Title of Correlation surveye Coefficient 349 -.027 -.006 -.091 -.043 -.054 640 920 115 456 349 300 300 300 -.324 ** 197* -.055 * 111 -.159** -.015 1.000 -.054 300 300 300 300 300 006 791 300 300 1.000 000 019 300 -.420** -.159** 000 300 996 745 300 1.000 300 432** d person Sig (2tailed) N 000 340 001 000 300 300 300 006 996 300 300 300 Number Correlation 169* ** ** -.568 -.414 -.254** -.015 * of Coefficient working years Sig (2.000 000 003 000 791 tailed) N 300 300 300 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 112 300 300 019 000 300 432** 300 1.000 745 000 300 300 300 ... Qualification in Guaranteed Asset Valuation at Asia Commercial Joint Stock Bank Scope of the study: The thesis "Model for Risk Qualification in Guaranteed Asset Valuation at Asia Commercial Joint Stock. .. Commercial Joint Stock Bank - Identifying influence extent of each factor affecting valuation risks of guaranteed assets at Asia Commercial Joint Stock Bank - Proposing overall solutions for commercial. .. of risks in valuation 19 Identification of risk in valuation is continuous and systematic determining of risks in valuation Risk identification in valuation intends to develop information on