In the recent years, the banks pay more attention to the importance of the Credit Risk. Thus, more research institutions start to focus on the problem of the Credit Risk. And the KMV company is one of the most famous institutions. The paper uses Expected Default Frequency Model developed by KMV to value the expected default probability of Taiwan listed company, and compared two ways, Financial Statement Analysis and KMV Option Model, to value EDF, and try to understand the distribution of the EDF of Taiwan listed company.

Abstract Ever since 1980, facing the impact of the more freedom of trading market and the fast developing on the new technology, financial market grows rapidly in prosperity. Especially the derivative financial goods are brought to the market, the financial organization¡¦s affairs and trading styles become more diversified, also added new risks of uncertainty. Furthermore, more complicated credit risk patterns caused the traditional measuring tools of financial risk among market participants, even risk structure and credit culture being severely challenged. During 1990, financial crisis or fraud cases consecutively happened in the international financial market, so the financial risk management has become a subject concerned by financial organizations, government and the public investors. However, credit risk is always the focus in all the financial risks. Especially the Basel Committee on Banking Supervision, (a branch of the Bank for International Settlements, BIS), published ¡§The New Basel Capital Accord¡¨ (Basel II). In this New Basel Capital Accord, it not only emphasizes the importance of credit risk, but also allows financial organizations to develop Internal Rating Based Approach, ¡§IRB¡¨ to evaluate and calculate proper risk capital. These operations for credit risk evaluation model¡¦s development have been focused on the academic circle, government, and business circle. Since Merton (1974) has applied options pricing model as a technology to evaluate the credit risk of enterprise, it has been drawn a lot of attention from western academic and business circles. Merton¡¦s Model is the theoretical foundation of structural models. Currently, the famous KMV Model in practically is the extension of application of Merton¡¦s Model. Merton¡¦s model is not only based on a strict and comprehensive theory but also used market information stock price as an important variance to evaluate the credit risk. This makes credit risk to be a real-time monitored at a much higher frequency. This advantage has made it widely applied by the academic and business circle for a long time. According to this research topics: (1) Credit risk holds geographical and culture character. Though credit risk evaluating model introduced from the foreign, yet it still has to be modified locally and it also needs more supports from local theory and practical case study. (2)Structural model is based on ¡§look-forward¡¨ analysis. It implies market-based information contents. (3) After prudent and careful analytical consideration about domestic capital market, the electronic business is the mainstream of domestic stock market, and also the competitive business for Taiwan in the world, meantime, electronic business has a higher level of sensitivity in three phases of profit, prosperity and risk. So that, I choose electronic companies in the public stock market as my research target and time frame is across 2004 to 2006, by means of KMV model which is a mainstream of structural model to evaluate credit risk, developed by Moody¡¦s Co. USA. I also referred to ¡§Small and Medium Enterprise Credit Guarantee Fund Main Guarantee Business Default Probability and Credit Risk Valuation Research Report¡¨, authored by C. J. Kuo (2006) for the variable definition and selections giving very thorough considerations. As I proceed a series of research in using EDF (Expected Default Frequency) of KMV model as well as a number of empirical investigation procedures in integrity and individual electronic business. I find out that EDF of KMV model it can obtain the prominent effect in credit risk and the prediction ability in advance. This paper can provide research result as a reference to risk-manager and to assist investors and governor to discern the depth of risks that the enterprise involved and then to decide the policy of strategy investment and level of risk management. Eventually to minimize the cost of credit checking and enterprise capitals, while to maximize the managerial efficiency and the profitability is the contribution of this paper could be.

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It is the key what determined the future of a company the economic behavior practiced from the commercial credit, and the performance of a customer decides the probability of the bad debt from the account receivable. To avoid the bad running of a business unit from terrible cash flow from account receivable, and lead to financial crisis or failure, I try to dig in the problem of the business to give credit failure. Finally, I hope to run a system of crisis prediction to avoid this kind of problem. Try to use the KMV Model on the companies which were listed on the stock exchange market belonged to the Printed Circuit Board (PCB) industry from 2004 to 2006. The result of verification ,the Distance-to-Default(DD) average is about 3.4982; and the Expected-Default-Frequency(EDF) probability average locates on 0.0084. In addition , used the size of capitalization and the analysis of financial ratios to evaluate the internal credit line system in a clinical way, and upgrade the risk management of credit, risk judgment measurement to decrease the loss in the meanwhile.

Made available in DSpace on 2016-03-15T19:33:04Z (GMT). No. of bitstreams: 1 Daniela Rezende de Paula.pdf: 383337 bytes, checksum: 2c7c9d004a174c0b9a286928d37a9eef (MD5) Previous issue date: 2010-03-01 / Fundo Mackenzie de Pesquisa / Sales of new cars in Brazil have increased significantly in the last decade, with average growth of 10% per year. Government incentives, such as tax reduction, were used as a forcing agent for the segment during the crisis period between 2008 and 2009. With the continuation of strong market, funding also increase . The objective of this research is to test, based on a study Securato (2003), who adapted the KMV model to study the probability of default for private companies, which is the default risk associated with the financing of vehicles, using as variables the relationship between debt and payment to the contractor for the good and the devaluation of the prices of passenger cars and light commercial market. The adaptation of the KMV model, however, showed no predictive ability for the market of auto finance. / As vendas de veículos novos no Brasil vêm aumentando significativamente na última década, com crescimento médio de 10% ao ano. Incentivos governamentais, como a redução da carga tributária, foram usados como agentes impulsionares para o segmento durante o período de crise entre 2008 e 2009. Com a manutenção do mercado aquecido, os financiamentos também cresceram. O objetivo desta pesquisa é testar, baseando-se em um estudo de Securato (2003), que adaptou o modelo KMV para estudar a probabilidade de inadimplência em empresas de capital fechado, qual é o risco de inadimplência associado ao financiamento de veículos, usando como variáveis a relação entre dívida contratada e pagamento à vista do bem e a desvalorização dos preços dos veículos de passeio e comerciais leves no mercado. A adaptação do modelo KMV, entretanto, não mostrou capacidade preditiva para o mercado de financiamento de automóveis.

The thesis is focused on the options of quantifying credit risk by using the concept of the KMV model. The introduction outlines the basic approaches to measuring credit risk. In the following chapters is specified the nature of KMV model with the focus on its application in the Czech capital market. Self-calibration of the KMV model is made in this part. The analytical part related to the quantification of credit risk using the KMV model is implemented on selected companies which are traded on the Prague Stock Exchange. The results obtained are consequently confronted with the official rating degrees of agency Moody's.

This thesis establishes an information system which combines three credit risk models through Service-Oriented Architecture (SOA). The system requires the bank user inputting finance-related data and selecting options to generate a series of credit risk related results, including the probabilities of default, the recovery rates, the expected market value of assets, the volatilities of the expected market value of assets, the default points, the default distances, and four indexes from principal components analyses. In addition to exhibiting the numerical results, graphical results are also available for the user. Three credit risk models joining this system are the Moody¡¦s KMV Model with Default Point Modified, the Risk-Neutral Probability Measure Model, and the Time-Varying Jointly Estimated Model. Several previous researches have demonstrated the validity of these credit risk models, hence the purpose of this study is not to examine the practicability of these models, but to see if these models are capable of connecting each other effectively and eventually establishing a process to evaluate the credit risk of enterprises and industries by the use of testing samples. Testing samples are data from Taiwan Small and Medium Enterprise Credit Guarantee Fund. The finance-related data includes the loan amounts, the book value of assets, the data used to calculate the default point threshold (such as the short-term debt and the long-term debt), and the financial ratios with regard to growth ability (such as the revenue growth rate and the profit growth rate before tax), operation ability (such as the accounts receivable turnover rate and the inventory turnover rate), liability-paying ability (such as the current ratio and the debt ratio), and profitability (such as the return on assets and the return on equity). In addition to inputting the finance-related data, the system also require the user selecting the industrial category, the default point threshold, the way data being weighted, the data period, and the borrowing rates from the option page for every enterprise in order to acquire the results. Among the computing process, user is required to select weighted average method, either weighted by loan amounts or weighted by market value of assets, to obtain ¡§the weighted average probability of default of the industry¡¨ and ¡§the weighted average recovery rate of the industry¡¨ which are both used by the Time-Varying Jointly Estimated Model. This study also makes use of quartiles to simulate the situation when the user is near the bottom and top of the business cycle. Furthermore, the ¡§Supremum Strategy¡¨ and the ¡§Infimum Strategy¡¨ are added to this study to let the user realize the best condition and the worse condition of the ¡§Time-Varying Industrial Marginal Probabilities of Default¡¨.