This paper emphasis on the importance of default correlation, and also illustrate how the concept is connected with the Basel Ⅱ framework’s intention. Moreover, the paper brought out the different methodologies used by practitioners to arrive at the default correlation calculation, namely, the dispute between asset correlation and equity correlation. Furthermore, based on the model proposed by Hamerle, Liebig, and Scheule (2004), a panel logit model is set up to capture the relationship between the default events and the risk components endured by the specific industry. The model is therefore used to test the applicability of such model using Taiwan’s banking industry data. The result is consistent with our expectation about including the macroeconomic variables which will help to explain the default events happened within the banking industry. But, to my surprise, the proposition about the contemporary systematic random risk effect seems to be insignificant and a fixed effect is suggested to be assumed instead.

Submitted by João Miranda (joao.moraes.miranda@gmail.com) on 2013-09-23T13:58:17Z No. of bitstreams: 1 Um estudo sobre a probabilidade de default para bancos de médio e pequeno porte.pdf: 1263567 bytes, checksum: 4587c672711e5c3b9ae677b492e5f6c4 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-09-23T15:15:26Z (GMT) No. of bitstreams: 1 Um estudo sobre a probabilidade de default para bancos de médio e pequeno porte.pdf: 1263567 bytes, checksum: 4587c672711e5c3b9ae677b492e5f6c4 (MD5) / Made available in DSpace on 2013-09-23T15:41:37Z (GMT). No. of bitstreams: 1 Um estudo sobre a probabilidade de default para bancos de médio e pequeno porte.pdf: 1263567 bytes, checksum: 4587c672711e5c3b9ae677b492e5f6c4 (MD5) Previous issue date: 2013-08-27 / This dissertation aims to find a primary risk metric for banks that can be a specific component in future models of cost of capital. As a secondary objective, this paper discloses a modeling process that can be extended to other banking segments. The set of contributions of this work consists in the vision application, the object of study (banks small and medium sized businesses with low diversification of products or segments in the Brazilian financial system) and the accessibility of the structured modeling process / Esta dissertação tem por objetivo primário encontrar uma métrica de risco para bancos elegível a ser uma componente específica em futuros modelos de custo de capital. Como objetivo secundário, este trabalho descreve um processo de modelagem passível de ser estendido a outros segmentos bancários. O conjunto de contribuições deste trabalho consiste na visão de aplicação, no objeto de estudo (bancos de pequeno e médio porte com baixa diversificação de produtos ou segmentos no sistema financeiro brasileiro) e na acessibilidade do processo de modelagem estruturado

Objective: We consider the following problem from credit risk modeling: Our sample (Xi; Yi), 1 < i < n, consists of pairs of variables. The first variable Xi measures the creditworthiness of individual i. The second variable Yi is the default indicator of individual i. It has two states: Yi = 1 indicates a default, Yi = 0 a non-default. A default occurs, if individual i cannot meet its contractual credit obligations, i. e. it cannot pay back its outstandings regularly. In afirst step, our objective is to estimate the threshold between good and bad creditworthiness in the sense of dividing the range of Xi into two rating classes: One class with good creditworthiness and a low probability of default and another class with bad creditworthiness and a high probability of default. Methods: Given observations of individual creditworthiness Xi and defaults Yi, the field of change point analysis provides a natural way to estimate the breakpoint between the rating classes. In order to account for dependency between the observations, the literature proposes a combination of three model classes: These are a breakpoint model, a linear one-factor model for the creditworthiness Xi, and a Bernoulli mixture model for the defaults Yi. We generalize the dependency structure further and use a generalized link between systematic factor and idiosyncratic factor of creditworthiness. So the systematic factor cannot only change the location, but also the form of the distribution of creditworthiness. Results: For the case of two rating classes, we propose several estimators for the breakpoint and for the default probabilities within the rating classes. We prove the strong consistency of these estimators in the given non-i.i.d. framework. The theoretical results are illustrated by a simulation study. Finally, we give an overview of research opportunities.

This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. The main framework revolves around driving a Monte Carlo simulation with Copluas to predict future revenue scenarios across a portfolio of early-stage technology companies. Three models for a random Gaussian walk, a Linear Dynamic System and an Autoregressive Integrated Moving Average (ARIMA) time series are implemented and evaluated in terms of their portfolio Value-at-Risk influence. The model performance confirms that modeling portfolio risk in Venture Debt is challenging, especially due to lack of sufficient data and thus a heavy reliance on assumptions. However, the empirical results for Value-at-Risk and Expected Shortfall are in line with expectations. The evaluated portfolio is still in an early stage with a majority of assets not yet in their repayment period and consequently the spread of potential losses within one year is very tight. It should further be recognized that the scope in terms of explanatory variables for sales and model complexities has been narrowed and simplified for computational benefits, transparency and communicability. The main conclusion drawn is that alternative approaches to model Venture Debt risk is fully possible, and should improve in reliability and accuracy with more data feeding the model. For future research it is recommended to incorporate macroeconomic variables as well as similar company analysis to better capture macro, funding and sector conditions. Furthermore, it is suggested to extend the set of financial and operational explanatory variables for sales through machine learning or neural networks. / Detta examensarbete är en experimentell studie för kvantitativ modellering av kreditrisk i Venture Debt-portföljer. Givet en brist på tillgänlig konkurs-data från ArK samt från offentligt tillgängliga databaser i kombination med ambitionen att inkludera företag som misslyckas med skuldförpliktelser innan konkurs per se, presenterar vi en metod för riskmodellering baserad på trender i intäkter. Ramverket för modellen kretsar kring Monte Carlo-simulering med Copluas för att estimera framtida intäktsscenarier över en portfölj med tillväxtbolag inom tekniksektorn. Tre modeller för en random walk, ett linjärt dynamiskt system och ARIMA- tidsserier implementeras och utvärderas i termer av deras inflytande på portföljens Value-at- Risk. Modellens prestationer bekräftar att modellering av portföljrisk inom Venture Debt är utmanande, särskilt på grund av bristen på tillräckliga data och därmed ett stort beroende av antaganden. Dock är de empiriska resultaten för Value-at-Risk och Expected Shortfall i linje med förväntningarna. Den utvärderade portföljen är fortfarande i ett tidigt skede där en majoritet av tillgångarna fortfarande befinner sig i en amorteringsfri period och följaktligen är spridningen av potentiella förluster inom ett år mycket snäv. Det bör vidare tillkännages att omfattningen i termer av förklarande variabler för intäkter och modellkomplexitet har förenklats för beräkningsfördelar, transparens och kommunicerbarhet. Den främsta slutsatsen som dras är att alternativa metoder för att modellera risker inom Venture Debt är fullt möjliga och bör förbättras i tillförlitlighet och precision när mer data kan matas in i modellen. För framtida arbete rekommenderas det att inkorporera makroekonomiska variabler samt analys av liknande bolag för att bättre fånga makro-, finansierings- och sektorsförhållanden. Vidare föreslås det att utöka uppsättningen av finansiella och operationella förklarande variabler för intäkter genom maskininlärning eller neurala nätverk.

論文名稱：公司信用風險之衡量 校所組別：國立政治大學金融研究所 畢業時間：九十年度第二學期 提要別：碩士學位論文提要 研究生：林妙宜 指導教授：陳松男博士 論文提要及內容： 信用風險一直是整體金融環境非常重要的一環，銀行授信、商業交易、投資評估，都會對信用風險做仔細的研究與評估。本論文以台灣的公司為樣本，採用會計財務比率與股票價格，主要兩項反映公司體質的資訊，建構信用風險模型，期望能提供台灣公司信用風險衡量上，公正而有效的指標。 以財務比率為基礎的區別分析模型，選取變數為獲利能力指標的常續性EPS、現金流量指標的現金流量對負債、成長率指標的盈餘成長率、償債能力指標的負債比率，與經營能力指標的平均收帳天數，這五項財務比率涵蓋企業繼續經營與財務狀況的各個層面。區別分析模型在財務危機前一年可達正確分類率91．67%。 以股票市場價格為基礎的選擇權模型，可由每日之股票價格求算出預期違約機率，將市場對公司價值的衡量轉化為信用風險的程度，能即時掌握公司體質的變化，做出適當之因應。 關鍵字：信用風險、財務危機、會計資訊、財務比率、區別分析、股票價格、選擇權模型、預期違約機率 / Title of Thesis: Corporate Credit Risk Measurement Name of Institute: Graduate Institute of Money and Banking, NCCU Graduate Date: June, 2002 Name of Student: Lin, Miao-Yi Advisor: Dr. Chen, Son-Nan Abstract: Credit Risk has been the great concern in the financial market. Before the bank grants a loan or the company makes deals and investment, they first consider the credit risk of the conterparty. The empirical study tries to construct the credit risk models based on the public firms in Taiwan. Using financial ratios and stock prices, the two main sources of corporate financial information, we expect to provide a fair and efficient indicator to measure the corporate credit risk in Taiwan. In the discriminant analysis based on accounting data, the model chooses five financial ratios that cover the corporate operation and financial situation. They are earnings per share, operating cash flow to total debt, equity substantial growth rate, and average days to accounts receivable. The discrimanant analysis model can accurately classify 91.67% of the data as being default or solvency one year before the financial distress. In the option pricing model based on stock prices, the expected default probability can be solved by daily stock prices. In this model, how the market values the firm is turned into the level of credit risk, which can help us catch the changes of corporate soundness and make proper responses. Keywords: Credit Risk, Financial Distress, Accounting Data, Financial Ratio, Discrimanant Analysis, Stock Prices, Option Pricing Model, Expected Default Probability

This thesis consists of four self-contained essays on the various topics in finance.  The first essay, The Information Content of The Systematic Risk Structure of Corporate Yields for Future Real Activity: An Exploratory Empirical Investigation, constructs a proxy for the systematic component of the risk structure of corporate yields (or systematic risk structure), and tests how well it predicts real economic activity in the United States. It finds that the systematic risk structure predicts the growth rate of industrial production 3 to 18 months into the future even when other leading indicators are controlled for, outperforming other models. A regime-switching estimation also shows that the systematic risk structure is very successful in identifying and capturing different growth regimes of industrial production.  The second essay, How Much Leverage is Too Much, or Does Corporate Risk Determine the Severity of a Recession? investigates whether financial conditions of the U.S. corporate sector  can explain the probability and severity of recessions. It proposes a measure of corporate vulnerability, the Corporate Vulnerability Index (CVI) constructed as the default probability for the entire corporate sector. It finds that the CVI is a significant predictor of the probability of a recession 4 to 6 quarters ahead, even controlling for other leading indicators, and that an increase in the CVI is also associated with a rise in the probability of a more severe and lengthy recession 3 to 6 quarters ahead.  The third essay, Asian Flu or Wall Street Virus? Tech and Non-Tech Spillovers in the United States and Asia (with Jorge A. Chan-Lau), using TGARCH models, finds that U.S. stock markets have been the major source of price and volatility spillovers to stock markets in the Asia-Pacific region during three different periods: the pre-LTCM crisis period, the “tech bubble” period, and the “stock market correction” period. Hong Kong SAR, Japan, and Singapore were sources of spillovers within the region and affected the United States during the latter period. There is also evidence of structural breaks in the stock price and volatility dynamics induced during the “tech bubble” period.  The fourth essay, Coping with Financial Spillovers from the United States: The Effect of U. S. Corporate Scandals on Canadian Stock Prices, investigates the effect of U.S. corporate scandals on stock prices of Canadian firms interlisted  in the United States. It finds that firms interlisted during the pre-Enron period enjoyed increases in post-listing equilibrium prices, while firms interlisted during the post-Enron period experienced declines in post-listing equilibrium prices, relative to a model-based benchmark. Analyzing the entire universe of Canadian firms, it finds that interlisted firms, regardless of their listing time, were perceived as increasingly risky by Canadian investors after the Enron’s bankruptcy. / Diss. Stockholm : Handelshögskolan, 2003

Made available in DSpace on 2015-03-03T15:22:31Z (GMT). No. of bitstreams: 1 JackelyaAS.pdf: 313251 bytes, checksum: 729c2692ae341877eba59b8ce2bf93dd (MD5) Previous issue date: 2008-03-11 / In this work we study a new risk model for a firm which is sensitive to its credit quality, proposed by Yang(2003): Are obtained recursive equations for finite time ruin probability and distribution of ruin time and Volterra type integral equation systems for ultimate ruin probability, severity of ruin and distribution of surplus before and after ruin / Neste trabalho estudamos um novo modelo de risco para uma empresa que ? sens?vel a classica??o de risco de cr?dito, proposto por Yang(2003): Obtemos equa??es recursivas para a probabilidade de ru?na em tempo nito, distribui??o do tempo de ru?na, sistemas de equa??es integrais do tipo Volterra para severidade e distribui??o conjunta do capital antes e depois da ru?na