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研究生: 陳玉婷
Yu-ting Chen
論文名稱: 抵押債權受益憑證評等方法之探討-高溢酬投組與低溢酬投組之比較
An Investigation of Collateralized Debt Obligation Rating Methodologies- High Premium Portfolio vs. Low Premium Portfolio
指導教授: 史綱
Gang Shyy
張傳章
Chuang-Chang Chang
口試委員:
學位類別: 碩士
Master
系所名稱: 管理學院 - 財務金融學系
Department of Finance
畢業學年度: 95
語文別: 英文
論文頁數: 56
中文關鍵詞: 抵押債權受益憑證信評機構評等套利評等模型
外文關鍵詞: Rating Arbitrage, Rating Model, Collateralized debt obligations, Rating Agency
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  • 抵押債權受益憑證是由許多債務憑證組成的信用風險商品,近年來,其發展已經成為全球固定收益證券市場重要的一部分。在本論文中,我們先概述抵押債權受益憑證發展狀況,接著介紹三大信評公司-穆迪、標準普爾、惠譽- 如何對押債權受益憑證分券進行評等,這三家信評公司各自發展出自己的評等模型,這些模型當中有相似也有相異之處。
    然後,利用50檔信用違約交換組成合成型抵押債權受益憑證,標的資產分成高溢酬與低溢酬的投資組合,分別放入標準普爾與惠譽的評等模型做比較,最後簡述評等套利。


    Collateralized debt obligations, CDOs, are credit risk products backed by a pool of debt obligations. Over recent years, CDOs have become an important part of the global fixed income market. In this paper, we first describe the overview of CDOs. Then we introduce how rating agencies - Moody’s, S&P and Fitch - determine the rating of a CDO tranche. Each of them has their own methodologies, some are similar and some are different.
    Next, we construct two synthetic CDOs with one is high premium portfolio and the other is low premium portfolio. Put the required information into S&P’s and Fitch’s rating software and compare these results. Finally, we use these result to make some short discussions about rating arbitrage.

    1. Introduction 1 2. Overview of CDOs 3 3. Rating Agency’s CDO Rating Methodologies 6 3.1 Rating Measure: Expected Loss vs. Probability of Default Approaches to Rating CDO 7 3.2 Modeling Approach 8 3.2.1 Moody’s Binomial Expansion Technique 8 3.2.2 S&P’s CDO Evaluator Model 17 3.2.3 Fitch’s Default VECTOR Model 23 4. A Case Study of Simulation 30 4.1 Data Description 31 4.2 Portfolio Formation 31 4.3 Simulation Result 33 4.3.1 Simulation PartⅠ: 2005/3/21 and 2007/3/21 34 4.3.2 Simulation PartⅡ: 2003/3/21, 2005/3/21 and 2007/3/21 43 4.4 Rating Arbitrage 46 5. Conclusion 48 Reference 50 Appendix A: Summary of Reference Entities 53

    [1]Bluhm, C. (2003), “CDO Modeling: Techniques, Examples and Applications”,
    Working Paper.
    [2]Cifuentes, A., and G. O’Connor (1996), “The binomial expansion method applied to CBO/CLO analysis”, Moody’s Special Report.
    [3]Cifuentes, A., and C. Wilcox (1998), “The double binomial method and its application to a special case of CBO structures”, Moody’s Special Report.
    [4]Dan diBartolomeo (1998), “A Review of Moody’s Methods Used to Assign Credit
    Ratings to Collateralized Loan Obligations”, Northfield Information Services.
    [5]Douglas J. Lucas, Laurie S. Goodman, Frank J. Fabozzi, Collateralized debt obligations: structures and analysis, 2nd ed. , Hoboken, N.J. :J. Wiley & Sons, 2006.
    [6]Domenico Picone, “Collateralized Debt Obligations”, City University Business School, London Royal Bank of Scotland.
    [7]Duffie, D., and N. Garleanu (2001), “Risk and Valuation of Collateralized Debt Obligations,” Financial Analysts Journal, vol. 57, No. 1, pp. 41–59.
    [8]Fender, Ian, and John Kiff (2004), “CDO Rating Methodology: Some Thoughts on Model Risk and Its Implications,” BIS Working Papers, No. 163.
    [9]Frank.J. Fabozzi, Laurie S.Goodman (Eds.), Investing in Collateralized debt obligation, 2001.
    [10]Frank Partnoy (2006),“How and Why Credit Rating Agencies are Not Like Other Gatekeepers?”, San Diego Legal Studies Paper, No. 07-46.
    [11]Gill K.,R. Gambel, R.V. Hrvatin, H. Katz, G. Ong and D. Carroll (2004),”Global rating criteria for collateralized debt obligations”, structured finance, Fitchratings .
    [12]J. Garcia, T. Dwyspelaere, L. Leonard, T. Alderweireld and T. Van Gestel (2005), “Comparing BET and Copulas for Cash Flows CDO’s”, working paper
    [13]K. Gilkes, N. Jobst (2005), “CDO Evaluator Version 3.0: Technical Document”, S&P Structured Finance
    [14]Lucas, Douglas (2001),”CDO handbook”, Global structured finance research, JP Morgan.
    [15]Paul, M., C., Yomtov (2000), “The Lognormal Method Applied to ABS Analysis”, Moody''s Investors Service
    [16]Peretyatkin, Vlad, and William Perraudin (2002), “EL and DP Approaches to Rating CDOs and the Scope for ‘Ratings Shopping’,” in Credit Ratings—Methodologies, Rationale and Default Risk, ed. by M.K. Ong (London: Risk Books).
    [17]Satjayit Das, Credit derivatives: CDOs and structured credit products, 3rd ed., Singapore; Hoboken, NJ: John Wiley & Sons (Asia), 2005.
    [18]Standard & Poor’s (2002): “Global Cash Flow and Synthetic CDO Criteria“,
    S&P Structured Finance.
    [19]Sten Bergan (2002),“CDO Evaluator and Portfolio Benchmarks ”, The securitization Conduit, Vol.5, No.1-4.
    [20]The Fitch Default VECTOR Model- User Manual, Fitch Ratings Report, June 2006.
    [21]The CDO Evaluator Handbook, S&P Structured Finance, February 2006.
    [22]Zhu W., D. Yan, D. Castro, and S. McGarvey (2003), “CDO Rating Methodologies Review”, Fixed Income Strategy, Merrill Lynch
    [23]Witt (2004), “Moody’s Correlated Binomial Default Distribution”, Moody''s Investors Service.
    [24]林淑瑛 (2004), 信用衍生性金融商品之研究CB Asset Swap及CDO, 國立中央大學財務金融所博士論文

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