Predicting the probability of default for small and medium enterprises based on financial indications
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: Predicting the probability of default for small and medium enterprises based on financial indications
Predicting the probability of default for small and medium enterprises based on financial indications
MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications DEFAULT FOR SMALL AND MEDIUM ENTERPRISES BASED ON FINANCIAL INDIC ATORSGRADUATION THESISMAJOR: FINANCE & BANKINGCODE: 7340201HO CHI MINH CITY, 2021MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITYNGUYEN DIEI LINTIPREDICTING THE PROBABILITY OF DEFAULT FORS Predicting the probability of default for small and medium enterprises based on financial indications MALL AND MEDIUM ENTERPRISES BASED ONFINANCIAL INDICATORSGRADUATION THESISMAJOR: FINANCE & BANKINGCODE: 7340201SCIENCE INSTRUCTORPh.D. NGUYEN MINH NHATPredicting the probability of default for small and medium enterprises based on financial indications
HO CHI MINH CITY, 202ỈThe internal credit rating system always plays an important role at commercial banks in assessing customers' credit risk and assMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications building a legal framework for the credit rating to improve information transparency and support for banks to control credit risk from the beginning as well as support the stock market, the bond market to promote capital mobilization through the slock market, protect the rights and interests of inve Predicting the probability of default for small and medium enterprises based on financial indications stors.Researching and selecting suitable rating models will significantly contribute to the development of credit rating activities in Vietnam. HowevePredicting the probability of default for small and medium enterprises based on financial indications
r, the current models for predicting default probability7 have certain limitations and are being debated, inconsistency about these models' reliabilitMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications cial ratios affect the ranking results is always the goal, which needs to be studied in default prediction research, up to now. there are still not many studies published in Vietnam on selecting models to forecast the probability of default of enterprises based on financial indicators.Therefore. the Predicting the probability of default for small and medium enterprises based on financial indications thesis focuses on the issue of "Predicting (he probability of default for Small and Medium Enterprise based on financial indicators" to provide commePredicting the probability of default for small and medium enterprises based on financial indications
rcial banks systematically a theoretical basis and empirical evidence related to the selection of an appropriate business bankruptcy prediction model MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications this study is to: (i) determine the criteria of an appropriate forecasting model; (ii) how to choose a model capable of predicting the default probability7 of Small and Medium Enterprises (SMEs) at Vietnamese commercial banks based on financial indicators. The results obtained from this study aim to Predicting the probability of default for small and medium enterprises based on financial indications provide additional quantitative scientific evidence to answer which predictive model gives the best results in predicting the probability of defaultPredicting the probability of default for small and medium enterprises based on financial indications
of medium firmsand small in Vietnamese commercial banks; (iii) The most importantiicontribution of this study is to develop a basic idea in the use ofMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications commercial banks in Vietnam in the coming time.SMEs play a major role in most economies, particularly in developing countries. SMEs account for the majority of businesses worldwide and arc important contributors to job creation and global economic development. Micro, small and medium enterprises, co Predicting the probability of default for small and medium enterprises based on financial indications mmonly known as small and medium enterprises, are smallsized enterprises in terms of capital, labor or turnover. Small and medium enterprises can be dPredicting the probability of default for small and medium enterprises based on financial indications
ivided into three categories based on their size: micro enterprises, small enterprises and medium enterprises. According to the World Bank Group's criMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications ss than 200 people and a capital of 20 billion or less; medium enterprises have from 200 to 300 employees with capital of 20 to 100 billion.Probability of default is an important component applied in many credit risk analysis and risk management activities. According to Basel II. it is a key paramet Predicting the probability of default for small and medium enterprises based on financial indications er used in calculating the level of economic capital capable of absorbing risks at credit institutions. PI) is one of the most useful ratios for classPredicting the probability of default for small and medium enterprises based on financial indications
ifying borrowers. All banks, whether using standard or other advanced methods must provide supervisors with an internal estimate of the PI) relative tMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications inancial ratios and can practically reflect the business's slate. PI) can effectively reduce credit risk if fully considered.Through a review of domestic and foreign studies shows that financial institutions can apply many different credit rating models to predict the default probability of enterpri Predicting the probability of default for small and medium enterprises based on financial indications ses. These predictive models can be polynomial models, logit models, probit models, artificial neural network models. Besides, these ranking models usPredicting the probability of default for small and medium enterprises based on financial indications
e inputs or different financial indicators to forecast the bankruptcy of a business. Financial ratios are commonly used as short-term solvency, rate oMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications priate credit rating model and financial indicators affecting the probability of default in the researchers arc different, as well as the application in Research to predict the possibility of default of SMEs customers in Vietnam according to the author which is a new point. Through the analysis, com Predicting the probability of default for small and medium enterprises based on financial indications parison and synthesis of the above studies and related issues, the author has pointed out some research gaps, proposing the proposed research model anPredicting the probability of default for small and medium enterprises based on financial indications
d expected method for the topic.To accomplish the research objectives, the author implemented through 04 stages according to the following steps: StagMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications ing models (the logit model, the probit model, the complementary log-log model); rhe last stage use the Confusion matrix and 11 - Score to evaluate each model's regression results. On that basis, select an appropriate credit rating model and has the ability to predict well the probability of default Predicting the probability of default for small and medium enterprises based on financial indications of customers.The study was conducted based on the data, which arc taken from the annual financial statements of approximately 400 companies from 2017Predicting the probability of default for small and medium enterprises based on financial indications
to 2019. These financial statements have been audited to ensure the quality of the information source. Out of 400 businesses, there are 31 businessesMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF D Predicting the probability of default for small and medium enterprises based on financial indications the construction and installation industry; 43 enterprises in the pharmaceutical industry and medical equipment; 45 enterprises in the textile and garment industry; 47 enterprises in the fisheries sector (fish, shrimp, clam....); 54 businesses in the iron and Steel industry and 66 businesses in the Predicting the probability of default for small and medium enterprises based on financial indications agricultural sector (rice, coffee, pepper....). Based on the studies, the author selected 14 financial indicators as independent variables for the crePredicting the probability of default for small and medium enterprises based on financial indications
dit rating models in the research paper.MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF DMINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAMBANKING UNIVERSITY OF HO CHI MINH CITY---oOo---NGUYEN DIEU LINKPREDICTING THE PROBABILITY OF DGọi ngay
Chat zalo
Facebook