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擔保債權憑證（Collateralized Debt Obligation：CDO）為近年來發展迅速的資產擔保證券（Asset Backed Security）之一。其架構主要有一固定收益債權之債券或貸款組合，經由特殊目的公司（Special Purpose Vehicle, SPV）將此債權或貸款群組加以重組證券化包裝後，再依不同信用品質來區分各種等級之分券（Tranche）銷售給投資人，債權產生的現金流量就依照證券發行所設定之條件付息給一般投資人。
在CDO整個架構上，信用風險為整個商品架構上影響最大的部分，因此首先需建構單一資產之違約模式，與債權群組之違約相關性，進而計算證券化之後所應該給予投資人之分券溢酬。其中，本文主要探討資產群組的聯合違約相關性與建構聯合違約機率分配，在文獻上以copula方法最廣為大眾接受，而copula方法在模型上的選擇，會影響評價之準確性與操作上的效率，且由文獻指出選擇方式上並無一固定之準則。本文利用factor copula來建構資產群組織聯合違約機率分配，再予以評價，並比較factor copula在模式的調整上是否有顯著差異，進而尋求較佳的評價方式。

In recently years, credit derivatives become more and more popular. Collateralized Debt Obligation is one of the credit derivatives and the trading volumes are growing fast.
CDO is backed by a pool of portfolio and then tranched. When pricing CDO, it is an important thing that gets the correlation amount the portfolio that consists lots kind of assets. Copula method is one of the most efficient way to solve this problem.
In this paper, we provide factor copula to price the premium of CDO. By comparing many types of factor copula, we want to find out which types of factor copula are useful and efficient.

第一章 緒論 1
第一節、擔保債權憑證（CDO）簡介 1
第二章 文獻回顧 8
第一節、信用風險模型 8
第三章 評價模式 11
第一節、模式介紹 11
第二節、其他Factor Copula模式介紹 16
第四章 Copula函數 20
第一節、Copula介紹 20
第二節、相關性 26
第五章 實證說明 28
第一節、方法說明 28
第二節、CDO評價方式 29
第三節、實證方法說明 33
第六章 結論 42
參考文獻 43

中文部分
1、林鴻坤，『利用Merton模型衡量擔保債權憑證（CDO）違約風險』，2004年，台灣大學財務金融研究所碩士論文。
2、廖四郎、李福慶，『擔保債權憑證之評價—Copula分析法』。
3、張耀洲，『擔保債權憑證之評價—BET、Copula與Factor Copula方法之比較與分析』，2005年，政治大學金融研究所碩士論文。
4、呂建霖，『信用衍生性商品—CDO之評價與分析』，2005年，政治大學金融研究所碩士論文。

英文部分
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3、Anna Kalemanova, Bernd Schemid, and Ralf Werner, (2007)“The Normal Inverse Gaussian Distribution for Synthetic CDO Pricing.” The Journal of Derivatives, (Spring), 80-93.
4、Annelis Lüscher, (2005) “Symthetic CDO Pricing Using the Double Normal Inverse Gaussian Copula With Stochastic Factor Loadings.”
5、Collateralized Debt Obligation Pricing Method Introduction, working paper, S&P.
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23、Vladislav Peretyatkin, (2006)“HPM+: A Fast Analytical Model to Price Synthetic CDOs.”, working paper.
24、X. Burtschell, J. Gregory, J-P. Laurent, (2005)“Beyond the Gaussian Copula: Stochastic and Local Correlation”, working paper.