Application of z score model in the credit rating of 100 enterprises listed on HOSE

ACADEMY OF POLICY AND DEVELOPMENT INTERNATIONAL SCHOOL OF ECONOMICS AND FINANCE GRADUATION THESIS Topic: “Application of Z-Score model in the credit rating of 100 enterprises listed on HOSE” Supervisor: M.Sc Dang Thuy Nhung Student: Luu To Uyen Student ID: 5083402217 Class: TCCLC8 Ha Noi, June 2021 ACKNOWLEDGEMENT This report would never have been possible without the consistent support and assistance of the people whom I approached during the various stages of writing this report To complete the full report, I would like to send my first and most sincere thanks to Mrs Dang Thuy Nhung Lecturer, Academy of Policy and Development, for her valuable advice, encouragement, direction, and assistance Writing this report would have been impossible without her guidance Next, I would like to thank the Academic of Policy and Development and all the lectures at the Academy for teaching me the most necessary knowledge and creating the best learning environment Due to my limited knowledge, the thesis cannot avoid mistakes I hope to receive the teacher's comment and give me suggestions and ideas for me to complete the thesis better Student Luu To Uyen TABLE OF CONTENTS ACKNOWLEDGEMENT .2 LIST OF TABLES LIST OF FIGURES OVERVIEW OF THE RESEARCH PROJECT 1.1 Origin of study .3 1.2 Objective of study 1.2.1 Goal of study 1.2.2 Mission of study 1.3 Scope of study .5 1.4 Research Methods .5 1.5 Structure of study CHAPTER 1: LITERATURE REVIEW AND EMPIRICAL REVIEW OF CREDIT RATING AND Z-SCORE MODEL .6 1.1 Overview of credit rating 1.1.1 Definition of credit rating .6 1.1.2 Characteristics of credit rating .8 1.1.3 Object of credit rating 1.1.4 Role of credit rating 10 1.1.5 Rule of credit rating .13 1.1.6 Credit rating process 15 1.1.7 Methodology of credit rating 18 1.2 Overview of Z-score model 29 1.2.1 Introduction of model 29 1.2.2 Content of the model 30 1.2.3 Evaluate the model Z-score 36 1.3 Empirical review on credit ratings and Z-score model 38 1.3.1 Empirical review on research of credit ratings 38 1.3.2 Empirical review on research of Z-score model 41 1.3.3 Research gap and research innovation 44 CHAPTER 2: Z-SCORE INDICATOR APPLICATION IN CORPORATE CREDIT RATING LISTED ON HOSE .45 2.1 Data and research methods 45 2.1.1 Data 45 2.1.2 Research methods 45 2.2 Research results 50 2.2.1 Research result 1: Overall assessment of credit ratings of 100 enterprises 50 2.2.2 Research result 2: Credit rating assessment of 100 enterprises by industry 56 2.2.3 Research result 3: Evaluation of credit ratings of 100 companies by the time of listing shares on HOSE 69 CHAPTER 3: CONCLUSION AND SOME RECOMMENDATIONS 72 3.1 Some recommendations for investors 72 3.2 Some recommendations to improve the role and innovate the credit rating method in Vietnam today .73 3.3 Conclusion 74 REFERENCE .76 APPENDIX 79 LIST OF TABLES Table 1.1: Evaluate non-financial indicators .21 Table 1.2: The difference between models 36 Table 2.1: Data description 45 Table 2.2: Number of companies studied 46 Table 2.3: Classification of enterprises by industry of manufacturing enterprises .47 Table 2.4: Non-manufacturing firms 48 Table 2.5: Statistics of manufacturing and real estate enterprises 56 Table 2.6: Statistics of wholesalers and retailers of consumer goods 59 Table 2.7: Statistics of Technology and services 62 Table 2.8: Food business credit score results .66 LIST OF FIGURES Figure 1.1: Credit rating scoring criteria 14 Figure 1.2: Financial criteria 15 Figure 1.3: Credit rating process 16 Figure 1.4: Horizontal link model 28 Figure 2.1: Scoring credit ratings of 100 businesses in 2020 50 Figure 2.2: Number of businesses in credit rating by industry 56 Figure 2.3: Z-score distribution of firms in the construction and real estate industries .58 Figure 2.4: Z-score distribution of enterprises in the Wholesales industry and details 60 Figure 2.5: Z-score distribution of enterprises in the technology and Service 62 Figure 2.6: Credit scoring results for raw material mining and manufacturing enterprises .64 Figure 2.7: A summary of the number of companies listed on the HOSE from 2000 to 2020 69 OVERVIEW OF THE RESEARCH PROJECT 1.1 Origin of study Today, credit activities are one of the main activities of enterprises to meet the demand for loans When performing credit activities, commercial banks will act as a bridge between those who have excess capital and those who need capital Therefore, commercial banks both play the role of receiving deposits and acting as lenders and benefit from the difference, contributing to the benefits of the parties involved Credit rating has since become an important method for commercial banks when dealing with credit Beginning from the limited risks in the method of scoring credit ratings of commercial banks today, the author has learned about a credit rating scoring model being used in the world Altman Z - score model (referred to as Z - score model) is one of many models invented in the world and has been used in practice in many countries The Z-score model used to assess the bankruptcy risk of enterprises was developed in 1968 by American professor Edward I Altman, Leonard N Stern School of Business, New York University Although the Z-score model was found in the US, most countries can still use it with high confidence, including Vietnam In Vietnam, credit rating still has many limitations and inadequacies in the credit rating process of enterprises Credit rating methods and models that are in line with international standards have not been universally implemented At commercial banks, the customer credit scoring method is still heavily formal, not reflecting the actual situation that businesses are facing In addition, commercial banks mainly rely on internal credit ratings based on the requirements of the State Bank Therefore, the credit rating system of banks is often misleading, still does not accurately reflect the risks of enterprises, is lengthy, and especially the status of some businesses that are about to go bankrupt is still rated safe Credit risk is the action that borrowers are not able to repay the bank's debt when due date, this directly affects the development process of the bank and can also determine the survival of the bank at or bankrupt of the Bank Therefore, if in the process of credit rating the bank still has a rating based on form, the credit risk will lead the bank to make regular provisioning capital and limit the cash flow used with other business purposes of the bank Therefore, commercial banks need to pay more attention and improve more models and methods of credit rating to minimize credit risks from borrowers and provide capital provisions in case of bankruptcy borrowers Through the process of learning about the model, the author found that the current credit rating model at commercial banks is not suitable for the actual economic and financial situation of enterprises listed on the exchange securities, but the Z-score model is being used by many countries, especially developed countries This proves that the Z-score model is a very beneficial method in the credit rating process of banks From the above reasons, the author chooses the topic: "Application of Z-Score model in the credit rating of 100 enterprises listed on HOSE" 1.2 Objective of study 1.2.1 Goal of study The project is implemented to propose the application of the Z-Score model in credit rating of 100 enterprises listed on HOSE stock exchange 1.2.2 Mission of study - Clarifying the theoretical and practical basis of corporate credit rating Collect data on the financial situation of 100 1enterprises listed on the HOSE Application of Z-Score model in the credit rating of 100 enterprises listed on the HOSE 1.3 Scope of study Scope of research space: study 100 enterprises listed on the HOSE stock exchange - Time range: 2020 - 2021 • List of 100 companies listed on the HOSE as of May 20, 2021 • Financial figures: financial statements of 100 enterprises in the fourth quarter of 2020 • Share price closed at 20:41 on May 19, 2021 1.4 Research Methods The thesis uses the document research method in research, the author searches for documents from books, dissertations and scientific research works In addition, there is the guidance of the lecturer The author uses the method of collecting, processing and analyzing data as the main research method of the thesis The research data was downloaded by the author from Cafef.vn and Vietstock.com.vn, mainly financial statements and business results of 100 enterprises The author processes the data by using statistical methods with the help of Excel to calculate the results In addition, when analyzing data, the author uses multidimensional statistical methods, sampling methods and logic to analyze results obtained from calculation and data processing 1.5 Structure of study - Chapter 1: Literature review and empirical review of credit rating and Z-Score model Chapter 2: Z-score indicator application in corporate credit rating listed on hose - Chapter 3: Conclusion and some recommendations Wo.Capital HAG -6,498,604,992 DTK -2,556,237,816 PRT 337,102,736 PGV 9,433,189,342 CII 2,664,058,439 TID 279,317,206 VSH -987,156,798 HNG -4,748,749,782 HDG 154,937,575 VGT 1,627,767,333 PVI 3,210,023,939 LGC -230,624,632 QTP 2,263,703,704 HVN -24,455,915,410 MSR 2,248,144,833 VGC -537,338,287 GEX 2,239,729,177 DCM 1,928,040,342 SIP 6,400,428,244 POW 417,356,756 SNZ 3,538,292,534 SBT 1,223,352,956 BWE 471,563,813 BVH 4,456,465,158 GEG 678,215,489 HND 1,942,019,536 VCG 4,404,826,442 PVT 2,242,774,424 HT1 -2,295,711,807 SDI -5,820,922,229 BCM 8,387,838,393 SSI 3,216,652,962 HPX 2,661,640,084 TVN -1,049,688,119 PVD 2,308,851,906 PVS 6,800,252,633 HPG 4,772,040,750 VIC -3,208,802,000 KDC 1,672,152,032 FPT 3,247,779,035 OIL 5,117,070,203 DIG 1,312,491,768 PAN 2,529,598,176 DXG 9,404,521,021 NT2 -197,527,380 NVL 82,776,217,987 PDR 6,542,874,185 PTB 275,948,081 CMG 930,465,745 HTM 836,729,864 DPM 4,288,128,930 CTD 7,114,573,103 KBC 14,441,082,833 BSR 9,589,877,057 HSG 30,826,535 NLG 5,130,426,661 VGI 10,611,098,549 REE 2,565,198,698 GMD -388,811,528 PGD 719,923,056 MPC 3,397,386,762 FOX -1,366,713,397 MSN -9,113,978,000 VCI 4,578,313,682 TCH 8,068,824,619 VJC 5,548,970,184 VHM -1,073,168,000 ROS 2,565,472,124 DGC 1,624,879,775 PHR 1,973,825,312 VTP 765,520,523 HCM 4,259,393,966 MWG 7,894,720,531 DNH 1,080,625,304 KDH 8,813,658,128 QNS 1,528,273,690 GTN 2,460,128,195 PLX 2,397,143,852 MCH -685,547,059 PNJ 3,912,021,680 APPENDEX 02: DATA FOR MANUFACTURING BUSINESS X1 VEA 0.6385 VIF 0.5923 VRE 0.0873 GTN 0.5878 DHG 0.5991 PME 0.3538 VNM 0.3191 BHN 0.3585 VCS 0.4793 MCH -0.0268 VHC 0.3880 DPM 0.3795 SAB 0.5238 MPC 0.3802 ROS 0.2447 PNJ 0.4612 DGC 0.2765 BMP 0.5297 HPG 0.0363 VCF 0.4650 BSR 0.1716 KDH 0.6325 DCM 0.2212 KDC 0.1354 PDR 0.4189 HSG 0.0017 QNS 0.1537 PHR 0.3019 TVN -0.0472 PAN 0.2231 REE 0.1249 CTD 0.5025 SBT 0.0681 HT1 -0.2286 NLG 0.3761 MSN -0.0787 VCG 0.2246 GEX 0.0825 HPX 0.3607 KBC 0.6071 VGT 0.0903 BCM 0.1730 DIG 0.1110 SNZ 0.1727 DXG 0.4034 HDG 0.0112 NVL 0.5727 LGC -0.0194 VHM -0.0050 SDI -0.3415 TID 0.0210 PRT 0.0521 VIC -0.0076 CII 0.0902 HNG -0.1925 HAG -0.1744 83 APPENDIX 03: DATA FOR NON - MANUFACTURING BUSINESS X1 BVH 0.2396 SQC -0.0371 SCS 0.3733 PPC 0.4852 TCH 0.7781 AST 0.4475 SAS 0.3888 GAS 0.4702 ACV 0.5990 VCI 0.5462 MWG 0.1715 HTM 0.2732 QTP 0.2154 HND 0.1732 DNH 0.1294 FPT 0.0778 PGD 0.2201 CMG 0.1850 PVT 0.2022 HCM 0.3411 PVS 0.2588 NT2 -0.0310 PVD 0.1107 SIP 0.3833 PTB 0.0578 VTP 0.1745 OIL 0.2318 VGI 0.1798 GMD -0.0395 FOX -0.0850 BWE 0.0572 POW 0.0077 GEG 0.0873 PLX 0.0392 VJC 0.1228 PVI 0.1441 SSI 0.0899 PGV 0.1294 MSR 0.0561 VGC -0.0252 VEF 0.0201 DTK -0.1273 VSH -0.1020 HVN -0.3909 85 APPENDIX 04: TYPE OF BUSINESS VEA BVH VIF VIC SQC SCS GTN PPC TCH DHG AST PME SAS GAS VNM BHN VCS ACV MCH VCI VHC DPM SAB MPC VHM PNJ MWG DGC BMP HPG HTM VCF QTP HND BSR DNH NVL DCM FPT KDC PGD BCM CMG PVT HCM HSG QNS PVS NT2 PVD SIP PHR PTB VTP OIL VGI GMD FOX TVN BWE POW PAN GEG 88 PLX CII DXG VJC SBT HT1 KBC PVI MSN VCG SSI GEX PGV SNZ VRE VGT PDR HDG REE LGC SDI DIG NLG KDH MSR VGC CTD TID PRT ROS VEF HPX DTK VSH HNG HAG HVN 90 ... credit rating Collect data on the financial situation of 100 1enterprises listed on the HOSE Application of Z- Score model in the credit rating of 100 enterprises listed on the HOSE 1.3 Scope of study... propose the application of the Z- Score model in credit rating of 100 enterprises listed on HOSE stock exchange 1.2.2 Mission of study - Clarifying the theoretical and practical basis of corporate credit. .. 2.1: Scoring credit ratings of 100 businesses in 2020 50 Figure 2.2: Number of businesses in credit rating by industry 56 Figure 2.3: Z- score distribution of firms in the construction and