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研究生：	林惠瑜 Lin, Hui-Yu
論文名稱：	市場信用風險模型與信用評等之關聯 Can Market-Based Credit Risk Model Explain Credit Ratings?
指導教授：	王澤世 Wang, Tse-Shih
學位類別：	碩士 Master
系所名稱：	管理學院 - 財務金融研究所 Graduate Institute of Finance
論文出版年：	2010
畢業學年度：	98
語文別：	英文
論文頁數：	35
中文關鍵詞：	信用風險、KMV模型、違約機率、beta
外文關鍵詞：	Credit Risk, KMV Model, Default Probability, Beta
相關次數：	點閱：89 下載：16
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本篇論文主要探討市場信用風險模型與信用評等之關聯。本研究以信用評等代替違約機率，探討傳統市場信用風險模型中的變數對信用評等之解釋能力；此外，根據CAPM與WACC，我們認為beta會影響公司資產價值成長率，進而影響到市場信用風險模型(KMV)之中的違約機率，beta較大應會使其違約機率較低。在迴歸模型中，我們藉由控制一般會計比率信用風險模型中的變數來檢測市場信用風險模型之變數是否還有其影響力。資料來源方面，本篇採用COMPUSRTAT資料庫中1000家有S&P信用評等的公司為樣本，樣本期間為2003年9月至2009年11月間。實證結果顯示市場信用風險模型可解釋一部分的信用評等，但beta對信用評等的影響與我們預期相反。

The object of this paper is to discuss the relationships between the variables in market-based credit risk models and credit ratings. In this study, we use credit ratings to represent default probability, and examine the explanatory power of the variables in market-based credit risk models. In addition, according to CAPM and WACC, we argue that beta will influence expected growth rate of the firm, and further influence the default probability in KMV. That is, large beta may decrease default probability. In our ordered probit models, we examine the explanatory power of market-based variables by controlling other accounting-ratio-based variables. In this paper, we choose 1000 S&P rated firms in COMPUSTAT and collect the samples from September 2003 to November 2009. The empirical results show that market-based variables have incremental explanatory power on credit ratings, but the effect of beta on credit ratings is inconsistent with our expectation.

Chapter 1 Introduction................................................................................ 1
Chapter 2 Literature review and KMV model ........................................... 6
2.1 Measurement of credit risk by accounting-ratio-based and market-based models ......................................................................................................................... 6
2.2 The application of market-based models......................................................... 8
2.3 Review of default probability under KMV approach ...................................... 9
2.3.1 KMV model .......................................................................................... 9
2.3.2 Default probability and beta ............................................................... 11
Chapter 3 Data and methodology ............................................................. 15
3.1 Sample selection ............................................................................................ 15
3.2 Definition of variables ................................................................................... 16
3.2.1 Credit ratings ...................................................................................... 16
3.2.2 Market-based variables ....................................................................... 16
3.2.3 Accounting-ratio-based variables ....................................................... 18
3.3 Methodology ................................................................................................. 20
Chapter 4 Empirical results ...................................................................... 24
4.1 Summary statistics ......................................................................................... 24
4.2 Regression results .......................................................................................... 25
Chapter 5 Conclusion ............................................................................... 32
References ................................................................................................ 34
                                    

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校內：2013-07-21公開
校外：2015-07-21公開

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