(Luận văn HV chính sách và phát triển) 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com TABLE OF CONTENTS ACKNOWLEDGEMENT LIST OF TABLES LIST OF FIGURES OVERVIEW OF THE RESEARCH PROJECT 1.1 Origin of study 1.2 Objective of study 1.2.1 Goal of study 1.2.2 Mission of study 1.3 Scope of study 1.4 Research Methods 1.5 Structure of study CHAPTER 1: LITERATURE REVIEW AND EMPIRICAL REVIEW OF CREDIT RATING AND Z-SCORE MODEL 1.1 Overview of credit rating 1.1.1 Definition of credit rating 1.1.2 Characteristics of credit rating 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com CHAPTER 1: LITERATURE REVIEW AND EMPIRICAL REVIEW OF CREDIT RATING AND Z-SCORE MODEL 1.1 Overview of credit rating 1.1.1 Definition of credit rating World of conception: Before the 19th century, businesses were close to each other, knew each other's financial ability, so it was easy to extend credit to partners However, when the gap increases, this becomes difficult, investors are afraid to extend credit because they are worried about the risk of their counterparty not being able to repay the debt That created the first basis for the birth of the credit rating industry The Mercantile Agency, the ancestor of today's credit rating agencies, was established after the financial crisis of 1837 This organization ranks merchants' ability to repay loans and then publishes them According to John Moody's research in 1909, credit ratings are opinions about credit quality and debt solvency for creditors based on research results expressed through the notation system Aaa to C The new word “credit rating” was first issued by financial analyst John Moody in his “Railway Securities Handbook” when he researched, analyzed, and published ratings The first credit for 1500 bonds of 250 companies under a system of symbols consisting of letters A, B, and C ranked from AAA to C respectively These ratings not have a profound effect on the market for in 1936, a new law was passed: Banning banks from investing in speculative bonds, or bonds with low credit ratings, to avoid the risk of default that could lead to financial loss The act was quickly enforced by companies and financial institutions As a result, relying on credit ratings has become the standard According to research in 1860 by Standard & Poor's group - a credit rating agency in the US Credit ratings are opinions about the risk, solvency of financial LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com REFERENCE Vietnamese Nguyen Trong Hoa, 2010, Luan an tien si de tai: “ Xay dung mo hinh xep hang tin dung doi voi cac doanh nghiep Viet Nam nen kinh te chuyen doi”, chuyen nganh dieu khien hoc kinh te Tran Thi Hoa ( 2016), Khoa luan tot nghiep de tai: “Ung dung mo hinh Z-score xep hang tin dung khach hang doanh nghiep Ngan Hang Thuong Mai Co Phan Dau Tu Phat Trien Viet Nam- chi nhanh Thua Thien Hue”, chuyen nganh Tai chinh Ths Nguyen Phuc Canh, Vu Xuan Hung, 2014, Ung dung mo Hinh Z-score vao quan ly rui ro tin dung cho ngan hang thuong mai Viet Nam, NXB tap chi Phat trien Hoi nhap PDS.TS Nguyen Van Hieu, 2015, De tai: “ van dung mo hinh Z-score de kiem tra ket qua phan hang tin dung noi bo uoc luong xac suat vo no”, NXB tap chi nghien cuu Tai chinh ke toan, So 08 Phan Thi Thanh Lam,, 2012, Luan van thac si de tai: “ van dung mo hinh Z-score xep hang tin dung khach hang tai Ngan Hang Thuong mai co phan Ngoại Thuong – chi nhanh Quang Nam” , chuyen nganh Tai chinh Ngan hang , Dai học Da Nang Lam Minh Chanh, 2007, De tai “ Dung chi so Z de uoc luong he so tin nghiem” , NXB tai chi nhip cau dau tu , TP Ho Chi Minh Ngan Hang Nha nuoc Viet Nam, 2007, Xep hạng tin dung cac doanh nghiep niem yet tren thi truong chung khoan Viet Nam, NXB Lao Dong, Ha Noi Ngan Hang Nha nuoc Viet Nam, 2008, Xep Xep hạng tin dung cac doanh nghiep niem yet tren thi truong chung khoan Viet Nam, NXB Lao Dong, Ha Noi 76 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com https://www.bravo.com.vn/vi/Tin-tuc/Quan-tri-doanh-nghiep/Dac-diem-cua- doanh-nghiep-san-xuat-la-gi 10 https://ktpt.neu.edu.vn/tap-chi/so-188/nghien-cuu-trao-doi-685/mo-hinh-xep- hang-tin-dung-cho-cac-cong-ty-san-xuat-o-viet-nam.372652.aspx 11 https://www.slideshare.net/trongthuy2/chuyen-de-mo-hinh-xep-hang-tin-dungdoanh-nghiep-rat-hay-free 12 https://finance.vietstock.vn/VEF/tai-chinh.htm?languageid=2 13 https://s.cafef.vn/ 14.https://www.phs.vn/data/research/PDF_Files/analysis_report/vn/20200615/Pow er%20Electricity%20Industry-20200615-V.pdf 15 https://winerp.vn/doanh-nghiep-san-xuat-la-gi 16 https://www.saga.vn/luoc-su-ve-cac-to-chuc-xep-hang-tin-dung-tren-the- gioi~31888 77 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com English 17 Edward I.Altman, Max L.Heine , 2007, Corporate financil Distress Diagnosis in China, Salomon Centre, Newyork University http://pages.stern.nyu.edu/~ealtman/WP-China.pdf 18 Edward I.Altman and Anthony Saunders, 1996, Credit risk Measurement: Developmets over last 20 years, NewYork University https://pages.ucsd.edu/~aronatas/project/academic/science.pdf 19.Edward I Altman, (2000) Predicting financial distress of companies: Revisiting the Z-score and Zeta models 20 Bradstreet, D & (1994) The Failure Record 21 Frank J.Fabozzi , Capital Market Institutions and Instruments, Fourth Edition 22.https://www.fitchratings.com/products/rating-definitions#about-ratingdefinitions 23 https://www.wallstreetmojo.com/altman-z-score/ 24 file:///C:/Users/Admin/Desktop/KHOA%20LUAN/english.pdf 25 https://www.cleverism.com/altman-z-score-model-guide-examples/ 26 https://penpoin.com/altman-z-score/ 78 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com APPENDIX APPENDIX 01: DATA OF 100 COMPANIES 79 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Wo.Capital TA 2019 TA 2020 R.E HAG -6,498,604,992 38,632,487,089 37,265,819,551 -6,301,662,837 DTK -2,556,237,816 21,932,003,704 20,080,779,447 523,118,419 PRT 337,102,736 5,672,704,586 6,464,585,872 473,421,505 PGV 9,433,189,342 74,979,050,274 72,899,968,406 3,641,098,585 CII 2,664,058,439 29,249,127,937 29,547,034,101 2,310,477,430 TID 279,317,206 12,831,316,467 13,324,976,521 36,033,657 VSH -987,156,798 9,048,823,273 9,676,165,108 877,477,132 HNG -4,748,749,782 23,280,489,096 24,669,866,839 -2,306,105,397 HDG 154,937,575 13,866,320,800 13,878,647,735 1,300,731,895 VGT 1,627,767,333 19,833,530,990 18,019,676,442 716,755,394 PVI 3,210,023,939 22,086,852,254 22,276,442,444 939,616,223 LGC -230,624,632 11,260,219,776 11,905,685,986 1,066,459,071 QTP 2,263,703,704 10,965,519,606 10,507,594,530 1,345,044,410 HVN -24,455,915,410 76,454,866,037 62,562,137,696 -9,328,983,491 MSR 2,248,144,833 29,774,719,881 40,108,847,814 2,766,593,412 VGC -537,338,287 19,887,754,160 21,323,239,971 711,944,173 GEX 2,239,729,177 21,261,915,628 27,152,092,660 1,900,046,810 DCM 1,928,040,342 10,172,594,753 8,717,480,692 583,467,405 SIP 6,400,428,244 13,465,969,220 16,700,343,267 1,138,998,222 POW 417,356,756 55,695,702,534 54,050,146,600 4,302,230,689 SNZ 3,538,292,534 18,297,634,822 20,492,806,378 1,340,278,851 SBT 1,223,352,956 16,743,296,336 17,955,718,784 281,924,508 BWE 471,563,813 6,207,482,520 8,245,843,456 373,846,077 BVH 4,456,465,158 128,238,238,184 18,600,117,275 2,571,513,584 GEG 678,215,489 6,763,219,424 7,773,108,134 219,977,104 HND 1,942,019,536 12,663,606,219 11,210,550,334 1,618,777,850 VCG 4,404,826,442 19,318,370,538 19,609,980,551 2,156,620,907 PVT 2,242,774,424 10,997,298,677 11,089,584,286 875,710,420 HT1 -2,295,711,807 10,288,564,690 10,040,531,017 727,675,817 SDI -5,820,922,229 22,545,000,768 17,046,045,840 6,561,973,982 BCM 8,387,838,393 43,515,596,287 48,485,332,045 4,741,749,904 SSI 3,216,652,962 27,044,115,025 35,769,528,008 2,676,816,163 HPX 2,661,640,084 6,829,641,459 7,378,527,086 516,430,309 TVN -1,049,688,119 22,618,592,229 22,261,371,612 2,870,268,956 PVD 2,308,851,906 20,891,727,392 20,856,190,206 1,937,943,723 PVS 6,800,252,633 26,003,967,533 26,279,277,127 3,970,850,787 HPG 4,772,040,750 101,776,030,100 131,511,434,389 21,792,442,633 VIC -3,208,802,000 403,740,754,113 422,503,767,000 4,359,645,000 KDC 1,672,152,032 11,932,153,628 12,349,155,156 840,072,183 FPT 3,247,779,035 33,394,164,264 41,734,323,235 6,390,906,128 OIL 5,117,070,203 26,480,890,458 22,074,963,607 -898,817,341 DIG 1,312,491,768 8,197,228,508 11,826,163,042 1,034,315,398 PAN 2,529,598,176 10,764,553,683 11,336,295,461 522,660,753 DXG 9,404,521,021 19,880,517,215 23,311,433,045 841,362,108 NT2 -197,527,380 7,564,111,829 6,381,321,298 1,281,939,014 NVL 82,776,217,987 89,979,242,599 144,536,345,634 12,051,422,037 PDR 6,542,874,185 13,961,379,480 15,617,489,555 973,918,146 PTB 275,948,081 4,328,694,369 4,773,757,358 380,059,053 CMG 930,465,745 4,649,385,394 5,028,878,993 264,256,443 HTM 836,729,864 3,390,570,559 3,063,135,575 10,537,593 DPM 4,288,128,930 11,440,308,264 11,299,941,305 654,776,859 CTD 7,114,573,103 16,198,834,655 14,157,413,679 365,227,529 KBC 14,441,082,833 16,432,989,803 23,785,878,250 4,316,487,152 BSR 9,589,877,057 53,583,992,996 55,894,934,071 27,902,497 HSG 30,826,535 17,225,438,463 17,756,407,665 1,954,018,045 NLG 5,130,426,661 10,904,393,811 13,642,706,053 2,131,776,751 VGI 10,611,098,549 60,868,569,743 59,004,260,711 -3,560,933,109 REE 2,565,198,698 19,622,764,796 20,530,453,735 7,114,818,742 GMD -388,811,528 10,119,906,897 9,834,544,207 435,146,072 PGD 719,923,056 2,961,136,297 3,271,330,791 237,760,640 MPC 3,397,386,762 8,064,484,199 8,935,571,486 669,217,548 FOX -1,366,713,397 13,330,954,555 16,080,968,979 1,082,212,907 MSN -9,113,978,000 97,297,251,000 115,736,562,000 2,182,124,000 VCI 4,578,313,682 7,242,960,228 8,382,405,125 1,572,516,640 TCH 8,068,824,619 8,656,398,785 10,369,637,644 1,623,674,569 VJC 5,548,970,184 48,858,753,809 45,196,830,232 11,589,250,587 VHM -1,073,168,000 197,241,028,039 215,326,377,000 56,259,405,000 ROS 2,565,472,124 10,649,455,091 10,483,276,778 332,706,015 DGC 1,624,879,775 4,721,856,571 5,876,149,772 1,139,904,853 PHR 1,973,825,312 5,854,513,683 6,538,924,776 530,606,339 VTP 765,520,523 3,394,208,367 4,387,835,013 349,608,473 HCM 4,259,393,966 7,488,678,629 12,488,827,553 675,286,734 MWG 7,894,720,531 41,708,095,545 46,030,879,952 10,389,683,598 DNH 1,080,625,304 9,231,703,052 8,351,971,628 1,034,827,684 KDH 8,813,658,128 13,237,325,073 13,934,472,240 1,836,456,359 QNS 1,528,273,690 9,047,802,426 9,945,956,463 2,742,784,489 GTN 2,460,128,195 4,024,676,742 4,185,277,880 -138,004,875 PLX 2,397,143,852 61,762,413,838 61,106,212,964 2,760,573,038 MCH -685,547,059 20,469,607,312 25,533,406,553 4,583,857,862 PNJ 3,912,021,680 8,602,964,422 8,483,146,098 1,605,080,896 EBIT 205,730,343 1,747,290,198 97,121,554 4,760,227,895 1,144,706,175 113,461,029 136,778,419 147,084,053 2,076,444,954 1,279,672,816 918,526,299 463,677,456 1,833,993,905 -7,436,910,927 177,958,652 2,327,681,804 2,627,189,866 1,316,847,800 689,065,150 4,580,095,072 1,904,691,497 1,454,540,786 1,236,078,509 1,244,795,747 760,656,177 1,911,778,128 836,323,887 1,118,223,188 1,355,587,502 878,330,682 3,260,634,309 2,465,005,297 339,496,983 1,736,984,134 328,794,993 778,165,980 18,904,049,904 17,312,806,000 1,764,988,408 11,813,657,475 1,957,604,232 640,468,221 1,537,099,268 1,874,605,669 894,772,040 1,832,878,970 1,821,914,604 1,140,889,346 978,410,634 123,072,772 1,729,803,614 856,407,013 689,029,018 -2,224,827,020 4,627,267,348 670,769,109 6,883,681,877 1,605,865,669 949,584,535 690,360,057 1,528,422,748 5,725,071,298 17,888,697,000 1,207,587,105 1,161,241,311 -1,411,928,469 25,936,077,000 37,175,005 1,479,185,092 388,730,676 698,591,523 874,890,418 23,954,497,272 844,296,505 1,963,617,307 2,019,826,959 821,674,658 10,039,936,944 9,919,214,140 3,434,732,881 80 PRICE 5.25 11.80 14.40 17.00 20.30 24.50 19.50 10.70 41.00 14.70 32.60 58.20 13.00 26.70 18.90 32.60 24.50 16.65 163.50 11.70 28.40 19.65 28.90 53.20 15.95 18.30 46.60 16.15 14.95 53.90 36.00 34.80 14.40 20.00 21.30 66.10 120.10 51.00 76.30 108.00 26.50 24.20 23.15 19.30 142.00 70.20 84.50 35.50 12.50 18.20 54.30 32.50 15.10 38.70 37.00 30.50 55.00 37.90 27.55 35.00 90.80 12.00 73.00 21.85 110.00 100.40 7.27 67.50 51.00 84.70 35.45 141.70 27.40 35.80 38.40 17.00 54.20 116.20 93.50 37.90 N.o Stock TL TE 927,399,283 27,238,024,092 10,027,795,459 680,000,000 12,713,493,653 7,367,285,794 135,000,000 2,438,922,114 4,025,663,758 1,069,969,577 57,935,983,254 14,963,985,152 238,838,282 21,761,422,304 7,785,611,798 200,000,000 10,150,707,275 3,174,269,246 236,241,246 6,345,908,278 3,330,256,830 1,108,553,895 15,989,847,212 8,680,019,627 154,286,919 9,901,226,889 3,977,420,846 500,000,000 9,951,059,544 8,068,616,898 223,518,567 15,071,207,138 7,205,235,306 192,854,765 7,460,780,462 4,444,905,524 450,000,000 4,418,962,661 6,088,631,869 1,418,290,847 62,562,137,696 6,072,333,791 1,099,155,420 26,029,306,779 14,079,541,035 448,350,000 14,299,124,845 7,024,115,126 488,244,000 18,936,906,033 8,215,186,627 529,400,000 2,391,033,022 6,326,447,670 79,405,357 13,922,431,457 2,777,911,810 2,341,871,600 22,783,553,220 31,266,593,379 376,491,800 12,057,000,814 8,435,805,564 638,770,380 10,313,417,424 7,642,301,360 155,420,000 4,836,484,817 3,409,358,639 742,322,764 404,803,491 18,195,313,783 271,175,188 4,305,192,356 3,467,915,778 500,000,000 4,261,525,941 6,949,024,393 402,410,673 12,446,775,834 7,163,204,717 323,651,228 4,810,694,225 6,278,890,062 381,541,911 4,648,064,810 5,392,466,207 119,995,800 7,430,839,096 9,615,206,743 1,035,000,000 31,297,860,239 17,187,471,806 645,861,433 25,896,730,956 9,872,797,052 291,990,902 3,757,583,715 3,620,943,371 678,000,000 12,201,787,260 10,059,584,352 421,129,789 6,814,172,859 14,042,017,347 477,966,290 13,395,159,975 12,884,117,152 3,313,282,659 72,291,648,083 59,219,786,306 3,382,430,590 286,651,052,000 135,852,715,000 228,749,100 4,649,767,704 7,699,387,453 789,114,878 23,128,655,834 18,605,667,401 1,088,425,100 11,509,108,572 10,565,855,035 342,086,376 7,036,033,811 4,790,129,230 222,294,750 5,163,141,743 6,173,153,718 519,275,500 14,227,392,346 9,084,040,700 287,876,029 2,083,784,580 4,297,536,717 1,161,513,770 112,604,198,448 31,932,147,186 486,771,916 10,423,212,058 5,194,277,497 46,059,624 2,783,132,013 1,990,625,345 99,999,866 2,629,969,000 2,398,909,993 219,958,600 783,296,989 2,279,838,586 391,334,260 3,052,441,965 8,247,499,341 75,175,423 5,758,744,203 8,398,669,476 469,760,189 13,132,883,122 10,652,995,128 3,100,499,616 24,830,395,140 31,064,538,931 444,697,013 11,165,669,154 6,590,738,511 285,270,660 6,922,368,313 6,720,337,740 3,043,811,200 28,735,178,328 30,269,082,383 309,050,926 8,317,804,815 12,212,648,920 301,377,957 3,239,614,949 6,594,929,258 89,998,070 1,942,723,997 1,328,606,794 197,086,610 3,613,486,043 5,322,085,442 273,616,446 11,002,713,268 5,078,255,711 1,174,683,246 90,706,283,000 25,030,279,000 166,453,000 3,860,918,606 4,521,486,520 374,437,834 1,509,651,520 8,859,986,124 523,838,594 30,218,431,247 14,978,398,985 3,289,513,918 126,196,462,000 89,129,915,000 567,598,121 4,474,659,553 6,008,617,225 171,079,683 1,808,718,873 4,067,430,899 135,499,198 3,227,633,789 3,311,290,987 83,047,926 3,179,237,740 1,208,597,273 305,041,862 8,048,473,022 4,440,354,531 475,475,757 30,549,190,106 15,481,689,846 422,400,000 2,551,925,772 5,800,045,857 550,806,579 5,776,372,073 8,158,100,167 356,939,955 2,673,695,664 7,272,260,799 249,000,000 473,730,310 3,711,547,570 1,223,813,235 36,979,810,498 24,126,402,467 708,793,818 11,250,421,793 14,282,984,760 227,442,803 3,241,284,233 5,241,861,865 SALE 3,189,964,886 12,768,778,190 962,677,072 40,367,208,023 5,408,405,794 7,418,076,011 340,618,213 2,374,911,980 4,999,229,572 13,938,731,520 9,122,659,616 725,301,690 9,182,384,793 40,756,791,189 7,365,774,085 9,455,265,892 18,086,263,045 7,716,890,478 5,088,295,414 29,731,733,708 4,974,931,095 12,923,457,051 3,025,337,456 1,408,926,397 1,494,522,682 10,900,258,406 5,551,586,318 7,382,693,924 8,440,110,589 7,103,361,132 6,703,803,103 4,366,801,068 1,329,627,916 31,654,749,472 5,228,638,834 20,179,913,750 91,279,041,772 110,755,497,000 8,465,765,184 29,921,698,144 50,033,857,003 2,503,768,922 8,541,860,271 2,898,850,191 6,082,248,451 5,241,732,045 3,911,211,875 5,602,248,622 5,288,735,349 946,942,375 7,867,574,305 14,589,198,781 2,150,962,555 57,959,112,673 27,765,155,626 2,260,022,752 285,270,660 5,644,088,890 2,605,666,370 7,526,763,927 14,377,079,727 11,552,202,993 78,868,319,000 1,729,591,591 4,423,314,435 18,220,292,889 71,546,737,000 1,799,265,020 6,236,486,135 1,634,501,074 17,234,281,759 2,247,905,973 109,801,253,691 1,686,110,693 4,616,848,433 6,241,287,660 2,828,394,349 124,001,495,876 23,988,058,548 17,681,913,026 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com APPENDEX 02: DATA FOR MANUFACTURING BUSINESS X1 X2 X3 X4 ( P*stock/TL) X5 Z-SCORE VEA 0.6385 0.3895 0.0062 88.8062 0.1213 58.289134 VIF 0.5923 0.1870 0.0543 55.4047 0.3260 36.936600 VRE 0.0873 0.2108 0.1010 51.1675 0.2202 33.700371 GTN 0.5878 -0.0336 0.2002 28.4884 0.6890 20.239724 DHG 0.5991 0.1791 0.4215 13.0082 0.9790 11.663973 PME 0.3538 0.1303 0.3439 11.8306 0.8374 10.149970 VNM 0.3191 0.1484 0.5942 6.8556 1.2825 8.220262 BHN 0.3585 0.2004 0.2561 8.2083 0.9723 7.780627 VCS 0.4793 0.4199 0.3375 5.7447 0.9751 6.927354 MCH -0.0268 0.1993 0.4312 5.8906 1.0429 6.481738 VHC 0.3880 0.4674 0.1469 5.6125 1.0374 6.233157 DPM 0.3795 0.0576 0.1521 6.9615 0.6920 6.184643 SAB 0.5238 0.4555 0.3129 4.2581 1.0356 6.058560 MPC 0.3802 0.0787 0.1798 4.9524 1.6914 6.019127 ROS 0.2447 0.0315 0.0035 8.5622 0.1703 5.999269 PNJ 0.4612 0.1879 0.4020 2.6595 2.0697 5.912910 DGC 0.2765 0.2151 0.2791 4.8239 1.1769 5.817195 BMP 0.5297 0.1529 0.4247 2.4801 1.6008 5.437624 HPG 0.0363 0.1868 0.1621 5.5044 0.7825 5.144530 VCF 0.4650 0.4603 0.4087 1.0953 1.3323 4.583031 BSR 0.1716 0.0005 -0.0406 4.8324 1.0588 4.222940 KDH 0.6325 0.1352 0.1445 0.3398 4.108146 3.6616 81 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com DCM 0.2212 0.0618 0.1394 3.6865 0.8170 3.987547 KDC 0.1354 0.0692 0.1454 3.7536 0.6973 3.838049 PDR 0.4189 0.0659 0.1232 3.9462 0.2645 3.791228 HSG 0.0017 0.1117 0.2646 1.4736 1.5874 3.560433 QNS 0.1537 0.2888 0.2127 2.2695 0.6572 3.399599 PHR 0.3019 0.0856 0.0627 3.5558 0.2638 3.228331 TVN -0.0472 0.1279 0.0774 1.1113 1.4106 2.498398 PAN 0.2231 0.0473 0.1391 0.9967 0.7730 2.203119 REE 0.1249 0.3544 0.0800 1.4082 0.2811 2.092115 CTD 0.5025 0.0241 0.0564 0.4243 0.9612 2.054690 SBT 0.0681 0.0162 0.0838 1.2170 0.7449 1.904221 HT1 -0.2286 0.0716 0.1334 1.2272 0.8303 1.880872 NLG 0.3761 0.1737 0.0547 1.2569 0.1841 1.863154 MSN -0.0787 0.0205 0.1679 0.9454 0.7404 1.833126 VCG 0.2246 0.1108 0.0430 1.5066 0.2852 1.815618 GEX 0.0825 0.0785 0.1085 0.6317 0.7471 1.717699 HPX 0.3607 0.0727 0.0478 1.1190 0.1872 1.595475 KBC 0.6071 0.2146 0.0343 0.5401 0.1070 1.594670 VGT 0.0903 0.0379 0.0676 0.7386 0.7365 1.592978 BCM 0.1730 0.1031 0.0709 1.1905 0.1457 1.493328 DIG 0.1110 0.1033 0.0640 1.1766 0.2501 1.491770 SNZ 0.1727 0.0691 0.0982 0.8868 0.2565 1.451821 DXG 0.4034 0.0390 0.0868 0.7044 0.1342 1.410034 HDG 0.0112 0.0938 0.1497 0.6389 0.3604 1.407509 NVL 0.5727 0.1028 0.0156 0.7241 0.0447 1.390804 LGC -0.0194 0.0921 0.0400 1.5044 0.0626 1.263141 82 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com VHM -0.0050 0.2727 0.1257 0.1895 0.3468 1.258521 SDI -0.3415 0.3315 0.0444 0.8704 0.3588 1.116257 TID 0.0210 0.0028 0.0087 0.4827 0.5672 0.933230 PRT 0.0521 0.0780 0.0160 0.7971 0.1586 0.893203 VIC -0.0076 0.0106 0.0419 0.6018 0.2681 0.796926 CII 0.0902 0.0389 0.2228 0.1840 0.673100 HNG -0.1925 -0.0962 0.0061 0.7418 0.0991 0.228313 HAG -0.1744 -0.1661 0.0054 0.1788 0.0841 -0.225474 0.0786 83 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com APPENDIX 03: DATA FOR NON - MANUFACTURING BUSINESS X1 X2 X3 X4 ( TE/TL) X5 ZSCORE BVH 0.2396 0.0350 0.0170 44.9485 0.0192 48.988156 SQC -0.0371 -0.1904 -0.0097 22.2791 0.0137 22.468673 SCS 0.3733 0.3545 0.4963 12.9279 0.6393 20.290373 PPC 0.4852 0.2961 0.1393 8.6478 1.0945 14.101820 TCH 0.7781 0.1707 0.1221 5.8689 0.4650 12.588593 AST 0.4475 0.0538 0.2003 6.3778 0.4797 11.063341 SAS 0.3888 0.0832 0.2145 5.1358 0.4424 9.559569 GAS 0.4702 0.1600 0.1819 3.6108 1.0230 8.538365 ACV 0.5990 0.1687 0.0241 1.9427 0.1354 6.670165 VCI 0.5462 0.2013 0.1546 1.1711 0.2214 6.437898 MWG 0.1715 0.2368 0.5460 0.5068 2.5029 5.852961 HTM 0.2732 0.0033 0.0381 2.9106 0.2935 5.097818 QTP 0.2154 0.1253 0.1708 1.3778 0.8552 4.339418 HND 0.1732 0.1356 0.1602 1.6306 0.9131 4.294828 DNH 0.1294 0.1177 0.0960 2.2728 0.1918 4.221054 FPT 0.0778 0.1701 0.3145 0.8044 0.7965 3.881664 PGD 0.2201 0.0763 0.2215 0.6839 2.4153 3.799509 CMG 0.1850 0.0546 0.2022 0.9121 1.0929 3.617248 PVT 0.2022 0.0793 0.1013 1.3052 0.6685 3.590546 HCM 0.3411 0.0676 0.0876 0.5517 0.2250 3.586182 PVS 0.2588 0.1519 0.0298 0.9618 0.7719 3.389291 NT2 -0.0310 0.1839 0.1283 2.0624 0.8723 3.366381 84 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com PVD 0.1107 0.0928 0.0158 2.0607 0.2505 3.291378 SIP 0.3833 0.0755 0.0457 0.1995 0.3373 3.256251 PTB 0.0578 0.0835 0.2507 0.7152 1.2309 2.974191 VTP 0.1745 0.0899 0.1795 0.3802 4.4292 2.962269 OIL 0.2318 -0.0370 0.0806 0.9180 2.0609 2.869459 VGI 0.1798 -0.0594 0.1148 1.0534 0.0048 2.812200 GMD -0.0395 0.0436 0.0952 2.0357 0.2612 2.617078 FOX -0.0850 0.0736 0.3893 0.4615 0.7855 2.607924 BWE 0.0572 0.0517 0.1710 0.7049 0.4186 2.356416 POW 0.0077 0.0784 0.0835 1.3723 0.5418 2.270538 GEG 0.0873 0.0303 0.1047 0.8055 0.2056 2.173024 PLX 0.0392 0.0449 0.1634 0.6524 2.0184 2.113553 VJC 0.1228 0.2464 -0.0300 0.4957 0.3874 1.940977 PVI 0.1441 0.0424 0.0414 0.4781 0.4113 1.845006 SSI 0.0899 0.0852 0.0785 0.3812 0.1390 1.760182 PGV 0.1294 0.0492 0.0644 0.2583 0.5459 1.684256 MSR 0.0561 0.0792 0.0051 0.5409 0.2108 1.225703 VGC -0.0252 0.0346 0.1130 0.4912 0.4589 1.171400 VEF 0.0201 0.0735 -0.0020 0.4055 0.0021 0.784755 DTK -0.1273 0.0249 0.0832 0.5795 0.6079 0.376102 VSH -0.1020 0.0937 0.0146 0.5248 0.0364 0.278915 HVN -0.3909 -0.1342 -0.1070 0.0971 0.5864 -3.570811 85 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com APPENDIX 04: TYPE OF BUSINESS ngành thời gian lên sàn VEA sx thiết bị nông nghiệp 22/12/2008 BVH tài chính, bảo hiểm 15/12/2016 VIF sx nơng nghiệp/ khai thác gỗ 7/5/2018 VIC xây dựng & bđs 21/12/2006 SQC khai khoáng 18/05/2006 SCS vận tải kho bãi 12/12/2018 GTN sx thực phẩm 18/07/2006 PPC tiện ích/ phân phối điện 20/07/2015 TCH bán buôn hàng lâu bền 2/2/2010 DHG sx hóa chất, dược phẩm 3/1/2017 AST bán lẻ, cửa hàng bách hóa tổng 10/8/2007 hợp PME sx hóa chất, dược phẩm SAS bán lẻ, cửa hàng bách hóa tổng 16/3/2017 27/12/2006 hợp GAS tiện ích/ phân phối khí đốt thiên 7/5/2019 nhiên VNM sx thực phẩm 17/9/2015 BHN sx đồ uống 29/5/2019 VCS sx sp từ đất sét vật liệu 18/1/2018 chịu nhiệt ACV tiện ích/ phân phối điện 31/3/2015 MCH sx thực phẩm 6/6/2019 86 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com VCI tài chính, bảo hiểm, mơ giới 14/1/2019 chứng khốn VHC sx thực phẩm - thủy sản 20/11/2017 DPM sx hóa chất, dược phẩm 25/02/2008 SAB sx đồ uống 20/7/2017 MPC sx thực phẩm 25/6/2009 VHM xây dựng & bđs 16/04/2015 PNJ sx sản phẩm kim loại tổng hợp 5/10/2016 MWG bán lẻ, cửa hàng thiết bị gia đình 5/9/2008 DGC sx hóa chất, dược phẩm 10/12/2007 BMP sx sp nhựa cao su 13/11/2007 HPG sx sp kim loại 16/6/2011 HTM bán buôn, hàng tiêu dùng 21/2/2018 VCF sx đồ uống 29/10/2007 QTP tiện ích/ phân phối điện 24/7/2018 HND tiện ích/ phân phối điện 18/1/2016 BSR sx xăng dầu than đá 5/12/2006 DNH tiện ích/ phân phối điện 20/9/2007 NVL xây dựng & bđs 6/11/2017 DCM sx hóa chất, dược phẩm 19/92007 FPT CNTT 12/12/2005 KDC sx thực phẩm 13/1/2017 PGD tiện ích/ phân phối khí đốt thiên 17/3/2018 nhiên BCM xây dựng & bđs 23/03/2009 87 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com CMG CNTT 15/12/2010 PVT vận tải kho bãi 22/12/2009 HCM tài chính, bảo hiểm, mơ giới 12/6/2015 chứng khốn HSG sx sp kim loại 28/12/2016 QNS sx thực phẩm 30/7/2010 PVS khai khống 22/7/2011 NT2 tiện ích/ phân phối điện 22/1/2010 PVD khai khống 4/5/2018 SIP tiện ích/ hệ thống thủy lợi, cung 5/11/2007 cấp nước PHR sx hóa chất, dược phẩm 20/1/2010 PTB bán buôn hàng lâu bền 18/12/2009 VTP vận tải kho bãi 1/3/2018 OIL bán buôn hàng tiêu dùng 5/12/2008 VGI CNTT, viễn thông 8/4/2013 GMD vận tải kho bãi 25/09/2018 FOX CNTT 28/07/2000 TVN sx sp kim loại 22/04/2002 BWE tiện ích/ hệ thống thủy lợi, cung 26/11/2009 cấp nước POW tiện ích/ phân phối điện 16/10/2017 PAN sx thực phẩm 13/12/2006 GEG tiện ích/ phân phối điện 5/11/2009 88 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com PLX bán buôn hàng tiêu dùng/ sp dầu 7/7/2017 khí CII xây dựng & bđs 4/1/2018 DXG xây dựng & bđs 21/11/2016 VJC vận tải kho bãi/ vận tải hàng 17/05/2018 không SBT sx thực phẩm 01/09/2016 HT1 sx sp khoáng chất phi kim 26/08/2014 KBC xây dựng & bđs 21/04/2017 PVI tài chính, bảo hiểm 23/11/2018 MSN sx thực phẩm 19/05/2009 VCG xây dựng & bđs 14/07/2014 SSI tài chính, bảo hiểm 19/06/2017 GEX sx trang thiết bị điện 1/2/2010 PGV tiện ích/ phân phối điện 20/12/2016 SNZ xây dựng & bđs 19/01/2017 VRE xây dựng & bđs 21/03/2018 VGT sx may mặc 5/1/2017 PDR xây dựng & bđs 19/8/2009 HDG xây dựng & bđs 26/01/2007 REE xây dựng & bđs 5/10/2016 LGC xây dựng & bđs 28/01/2011 SDI xây dựng & bđs 21/05/2012 DIG xây dựng & bđs 24/12/2007 NLG xây dựng & bđs 18/08/2009 89 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com KDH xây dựng & bđs 15/11/2007 MSR khai khoáng 17/12/2007 VGC bán lẻ/ kinh doanh vật liệu xây 8/11/2017 dựng CTD xây dựng & bđs 28/02/2017 TID Đầu tư chế biến thực phẩm 11/7/2006 PRT sx & xuất nhập 12/1/2017 ROS xây dựng & bđs 21/3/2017 VEF dịch vụ hỗ trợ 19/01/2006 HPX xây dựng & bđs 3/10/2014 DTK tiện ích/ phân phối điện 6/12/2016 VSH tiện ích/ phân phối điện 2/7/2018 HNG sx nông nghiệp/ trồng trọt 3/8/2018 HAG sx nông nghiệp/ trồng trọt 26/05/2016 HVN vận tải kho bãi 22/12/2015 90 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com ... industry in the business field of enterprises and using the Z- score model to rank credit With the topic: "Application of Z- score model in the credit rating of enterprises listed on HOSE" , the author... 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. .. 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