Luận Văn Tốt Nghiệp: Ứng Dụng Mô Hình Z-Score Đánh Giá Tín Dụng 100 Doanh Nghiệp Niêm Yết Trên HOSE

Luận văn tốt nghiệp nghiên cứu Luận văn tốt nghiệp application of z score model in the credit rating of 100 enterprises listed on, điều tra thực trạng, phân tích số liệu, đề xuất

• Tác giả: Luu To Uyen
• Người hướng dẫn: M.Sc. Dang Thuy Nhung
• Trường học: Academy of Policy and Development, International School of Economics and Finance
• Chuyên ngành: Economics and Finance
• Đề tài: Application of Z-Score model in the credit rating of 100 enterprises listed on HOSE
• Loại tài liệu: Graduation thesis
• Năm xuất bản: 2021
• Địa điểm: Ha Noi

Mục lục chi tiết

• ACKNOWLEDGEMENT
• 1. 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
• 1.1.5. Rule of credit rating
• 1.1.6. Credit rating process
• 1.1.7. Methodology of credit rating
• 1.1.8. Overview of Z-score model
• 1.1.8.1. Introduction of model
• 1.1.8.2. Content of the model
• 1.1.8.3. Evaluate the model Z-score
• 1.1.9. Empirical review on credit ratings and Z-score model
• 1.1.9.1. Empirical review on research of credit ratings
• 1.1.9.2. Empirical review on research of Z-score model
• 1.1.10. Research gap and research innovation
• 2. CHAPTER 2: Z-SCORE INDICATOR APPLICATION IN CORPORATE CREDIT RATING LISTED ON HOSE
• 2.1. Data and research methods
• 2.2. Research result 1: Overall assessment of credit ratings of 100 enterprises
• 2.3. Research result 2: Credit rating assessment of 100 enterprises by industry
• 2.4. Research result 3: Evaluation of credit ratings of 100 companies by the time of listing shares on HOSE
• 3. CHAPTER 3: CONCLUSION AND SOME RECOMMENDATIONS
• 3.1. Some recommendations for investors
• 3.2. Some recommendations to improve the role and innovate the credit rating method in Vietnam today
• LIST OF TABLES
• LIST OF FIGURES

Tóm tắt

I. Tổng quan về mô hình Z Score

Mô hình Z-Score được phát triển bởi Edward Altman vào năm 1968, nhằm đánh giá khả năng thanh toán và rủi ro phá sản của doanh nghiệp. Mô hình này sử dụng các chỉ số tài chính để tính toán một điểm số, từ đó xác định khả năng tài chính của doanh nghiệp. Đánh giá tín dụng thông qua mô hình Z-Score giúp các ngân hàng và nhà đầu tư có cái nhìn tổng quan về tình hình tài chính của doanh nghiệp, từ đó đưa ra quyết định cho vay hoặc đầu tư. Mô hình này đã được áp dụng rộng rãi trên toàn thế giới và cho thấy tính hiệu quả trong việc dự đoán rủi ro tài chính. Theo nghiên cứu của Altman, các chỉ số như tỷ lệ nợ, lợi nhuận và tài sản có thể được sử dụng để tính toán Z-Score, từ đó phân loại doanh nghiệp thành các nhóm rủi ro khác nhau. Việc áp dụng mô hình này tại Việt Nam, đặc biệt là cho các doanh nghiệp niêm yết trên HOSE, có thể giúp cải thiện quy trình đánh giá tín dụng và giảm thiểu rủi ro cho các ngân hàng.

1.1. Đặc điểm của mô hình Z Score

Mô hình Z-Score có một số đặc điểm nổi bật. Đầu tiên, nó dựa trên các chỉ số tài chính có thể đo lường được, giúp cho việc đánh giá trở nên khách quan hơn. Thứ hai, mô hình này có khả năng phân tích rủi ro tài chính một cách hiệu quả, từ đó giúp các nhà đầu tư và ngân hàng đưa ra quyết định chính xác hơn. Cuối cùng, mô hình Z-Score có thể được điều chỉnh để phù hợp với từng ngành nghề khác nhau, giúp tăng tính chính xác trong việc đánh giá tín dụng. Việc áp dụng mô hình này không chỉ giúp các ngân hàng giảm thiểu rủi ro mà còn tạo ra một môi trường đầu tư minh bạch hơn cho các doanh nghiệp niêm yết trên HOSE.

II. Ứng dụng mô hình Z Score trong đánh giá tín dụng doanh nghiệp

Việc áp dụng mô hình Z-Score trong đánh giá tín dụng của 100 doanh nghiệp niêm yết trên HOSE mang lại nhiều lợi ích thiết thực. Đầu tiên, mô hình này giúp các ngân hàng có cái nhìn rõ ràng hơn về tình hình tài chính của doanh nghiệp, từ đó đưa ra quyết định cho vay hợp lý. Thứ hai, việc sử dụng Z-Score giúp giảm thiểu rủi ro tín dụng, vì nó cung cấp một phương pháp định lượng để đánh giá khả năng thanh toán của doanh nghiệp. Theo nghiên cứu, các doanh nghiệp có Z-Score thấp thường có nguy cơ phá sản cao hơn, điều này giúp các ngân hàng có thể đưa ra các biện pháp phòng ngừa kịp thời. Hơn nữa, việc áp dụng mô hình này cũng giúp các doanh nghiệp tự đánh giá được tình hình tài chính của mình, từ đó có những điều chỉnh cần thiết để cải thiện khả năng thanh toán.

2.1. Phân tích kết quả đánh giá tín dụng

Kết quả từ việc áp dụng mô hình Z-Score cho thấy có sự phân hóa rõ rệt giữa các doanh nghiệp niêm yết trên HOSE. Các doanh nghiệp có Z-Score cao thường có tình hình tài chính ổn định và khả năng thanh toán tốt, trong khi những doanh nghiệp có Z-Score thấp thường gặp khó khăn trong việc duy trì hoạt động. Điều này cho thấy tầm quan trọng của việc sử dụng mô hình Z-Score trong phân tích tài chính và đánh giá tín dụng. Hơn nữa, việc phân tích theo ngành cũng cho thấy sự khác biệt trong khả năng thanh toán giữa các lĩnh vực, từ đó giúp các nhà đầu tư có cái nhìn tổng quan hơn về rủi ro khi đầu tư vào các doanh nghiệp khác nhau.

III. Kết luận và khuyến nghị

Mô hình Z-Score đã chứng minh được giá trị của nó trong việc đánh giá tín dụng cho các doanh nghiệp niêm yết trên HOSE. Việc áp dụng mô hình này không chỉ giúp các ngân hàng giảm thiểu rủi ro mà còn tạo ra một môi trường đầu tư minh bạch hơn. Để nâng cao hiệu quả của mô hình, các ngân hàng cần thường xuyên cập nhật và điều chỉnh các chỉ số tài chính phù hợp với tình hình thực tế của doanh nghiệp. Hơn nữa, việc đào tạo nhân viên về cách sử dụng mô hình Z-Score cũng là một yếu tố quan trọng để đảm bảo rằng các quyết định tín dụng được đưa ra dựa trên dữ liệu chính xác và đáng tin cậy.

3.1. Khuyến nghị cho các nhà đầu tư

Các nhà đầu tư nên chú ý đến việc sử dụng mô hình Z-Score như một công cụ hỗ trợ trong quá trình ra quyết định đầu tư. Việc hiểu rõ về khả năng thanh toán và rủi ro tài chính của doanh nghiệp sẽ giúp các nhà đầu tư đưa ra những quyết định thông minh hơn. Hơn nữa, các nhà đầu tư cũng nên theo dõi thường xuyên các chỉ số tài chính của doanh nghiệp để có thể phát hiện sớm những dấu hiệu bất thường, từ đó có những điều chỉnh kịp thời trong danh mục đầu tư của mình.

Trích đoạn nội dung tài liệu

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. 1 LIST OF FIGURES. 2 OVERVIEW OF THE RESEARCH PROJECT. Origin of study .2 Objective of study.

Goal of study. Mission of study .3 Scope of study. Structure of study. 5 CHAPTER 1: LITERATURE REVIEW AND EMPIRICAL REVIEW OF CREDIT RATING AND Z-SCORE MODEL.

Overview of credit rating. Definition of credit rating. Characteristics of credit rating. Object of credit rating.

Role of credit rating .5 Rule of credit rating. Credit rating process. Methodology of credit rating. Overview of Z-score model.

Introduction of model. Content of the model. Evaluate the model Z-score. Empirical review on credit ratings and Z-score model.

Empirical review on research of credit ratings. Empirical review on research of Z-score model. Research gap and research innovation. 44 CHAPTER 2: Z-SCORE INDICATOR APPLICATION IN CORPORATE CREDIT RATING LISTED ON HOSE.

Data and research methods. Research result 1: Overall assessment of credit ratings of 100 enterprises. Research result 2: Credit rating assessment of 100 enterprises by industry. 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. Some recommendations for investors. Some recommendations to improve the role and innovate the credit rating method in Vietnam today. 79 LIST OF TABLES Table 1.1: Evaluate non-financial indicators .2: The difference between 3 models .2: Number of companies studied .3: Classification of enterprises by industry of manufacturing enterprises .4: Non-manufacturing firms.5: Statistics of manufacturing and real estate enterprises .6: Statistics of wholesalers and retailers of consumer goods.7: Statistics of Technology and services .8: Food business credit score results.

66 1 LIST OF FIGURES Figure 1.1: Credit rating scoring criteria .3: Credit rating process .4: Horizontal link model.1: Scoring credit ratings of 100 businesses in 2020 .2: Number of businesses in credit rating by industry .3: Z-score distribution of firms in the construction and real estate industries .4: Z-score distribution of enterprises in the Wholesales industry and details .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 .7: A summary of the number of companies listed on the HOSE from 2000 to 2020. 69 2 OVERVIEW OF THE RESEARCH PROJECT 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. 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 3 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".2 Objective of study 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.

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 4 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. 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.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. 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 5 CHAPTER 1: LITERATURE REVIEW AND EMPIRICAL REVIEW OF CREDIT RATING AND Z-SCORE MODEL 1.

Overview of credit rating 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 3 letters A, B, and C ranked from AAA to C respectively. These ratings do 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 6 obligations fully and on time of an issuer such as a business, government, or people's committee. In addition, credit rating also refers to the credit quality of an individual debt such as a corporate or local government bond and the relative probability that the issue may default. According to a study by Nomura Research Institute - Japan's prestigious General Research Institute, credit rating is the current assessment of a company's availability and ability to pay principal or interest on debt securities.

issued during the life of the security. For Fitch Corporation(1924) - one of the three prestigious credit institutions in the US in the world , credit ratings are assessments of an object's ability to meet financial commitments such as interest rates, shares, and interest rates, incentives, principal repayments, insurance claims, or partnership obligations. Credit ratings related to securities and issuer obligations may include recovery expectations. Credit ratings are used by investors as an indication of their ability to repay the money they have invested in.

Vietnam's conception: The word "Credit rating" is translated into many different meanings. In this study, the authors use the term "'credit rating'". In terms of definition, each financial institution defines credit rating differently, but the core content includes an evaluation of the credit quality or repayment ability of the issuer or debt instrument. Issuers include Enterprises, special purpose companies, governments, local authorities, non-profit organizations, sovereign states.

Credit-rated debt instruments include Government bonds, corporate bonds, certificates of deposit (CDs), local government bonds, preferred shares, mortgage- backed securities, Collateralized Debt Obligations. 7 The ranking is made based on the analysis of qualitative and quantitative factors related to the borrower's business activities, borrowing history, and debt repayment. Thus, in this research topic: “Credit rating is understood as an assessment of credit quality, showing the willingness to pay financial obligations (principal and interest) of an entity.