淡江大學覺生紀念圖書館 (TKU Library)

系統識別號 U0002-0303200812292100
中文論文名稱 擔保債權憑證之評價分析
英文論文名稱 Valuation of Collateralized Debt Obligations
校院名稱 淡江大學
系所名稱(中) 管理科學研究所博士班
系所名稱(英) Graduate Institute of Management Science
學年度 96
學期 1
出版年 97
研究生中文姓名 李福慶
研究生英文姓名 Fu-Ching Lee
學號 889560065
學位類別 博士
語文別 中文
口試日期 2008-01-19
論文頁數 68頁
口試委員 指導教授-廖四郎
中文關鍵字 擔保債權憑證分析  Copula  Factor Copula  隨機違約率模型 
英文關鍵字 Copula  Factor Copula  CDO Tranche  Strochastic hazard rate process 
中文摘要 自2002年底起,國際主要投資機構開始將投資重心轉向新奇信用衍生性CDO指數型分券(index tranche),例如標準化CDO指數型分券(index tranche)與CDO-Squared分券等。台灣金融產業目前正值轉型期,銀行業者不但面臨低利帶來經營壓力外,同時亦需規避評等較差之企業貸款的信用風險。此外,由於公司債連鎖違約與逆浮動結構債的鉅額損失,導致債券的投資資本轉向CDO市場。因此,此一環境背景下恰為發行CDO之良好契機。
從1997年發生東南亞金融危機,乃至1998年韓國的亞洲金融危機,造成許多跨國企業紛紛裁員、關廠、甚至倒閉,造成一連串的金融危機連鎖效應。由此可知,公司間或產業間之榮枯是相互關聯的,公司的破產機率除受債信評等高低所影響外,且均受總體經濟因素所影響。因此,本文嘗試以copula與factor copula方法來探究CDO資產池內標的間的違約相關性,以準確地估算CDO各分券之信用價差。

本研究之主要目的在於能更真實地捕捉CDO資產池的違約行為,在回復率隨機的假設設,採用CIR 隨機違約率模型與KMV-Merton Model合成的factor copula模型來評價指數型分券,同時利用兩階段probability bucketing方法來評價寶來證券所發行的第一檔CDO2。
本文與Hull and White (2004)模式double student’s t factor copula 模型作一比較,發現
採用兼具CIR 隨機違約率與隨機回復率模式將產生相對於Hull and White(2004) 模式來得
低之各分券信用價差。此即意味著違約率與回復率之常數假設是不合理的因為CDS 契約
英文摘要 After 2002, many originators turn to consider various bespoke tranches of other CDOs (including standardized contract of CDS Index) as underlying of collateral for both raising the return of its tranches and diversifying underlying of its collateral. The type of exotic CDOs is referred to as Synthetic CDO-Squared. Currently, the Taiwanese financial industry is going through a period of transformation. The banks face not only the pressure of operating pressures owing to declining interest rate, but also the pressure to control credit risk on loans. Additionally, the crisis resulting from successive corporate bond default events and a huge loss of inverse floating structured notes have led to the switch of financial investments from bond mutual funds to Collateralized Debt Obligation (CDO) markets in Taiwan.
The Southeast Asian financial crisis occurred in year 1997, followed by the Asian financial crisis of affecting S. Korea of 1998. They both resulted in numerous multinational enterprises laying off employees, shutting down factories, and even going bankrupt, and caused widespread financial pain. For risk management and valuation of multi-name credit derivatives, the estimation of the default dependence is considered an extremely important factor. Default dependency may be influenced by both overall economy factor, sectoral and firm-specific factors.
For hybrid portfolio of the first CDO-Squared issued by the Polaris Securities Group in Taiwan, we propose hybrid factor copula model which involves CIR stochastic intensity model and KMV-Merton Model developed by Leland (2004) under random recovery rate environment to price CDO-Squared.
Compared with the double student’s t factor copula method developed by Hull and White (2004), we find that the proposed model which uses CIR intensity rate, random recovery rate of various secured-level brackets, and double student’s t copula produces fair credit spreads of tranches lower than the Hull and White (2004) model except 15%~30% tranche. The assumptions of positive mean-reverting hazard rate and stochastic recovery rates of various classifications are more realistic since CDS has daily market quotes of different maturities, and thus market trading can expose credit spread information of obligors.
論文目次 目錄
2.2 Copula方法簡介..…15
第三章擔保債券憑證平方之評價--- Factor Copula分析法
3.2 CDO評價模式設定32
表2-2 Empirical Kendall’s (τ)之相關係數矩陣…..22
表3-1PROBIT 模式相關係數………..42
表3-4信用均數復歸速度參數 之敏感度分析…….44
表3-5CDO2信用均數復歸速度參數 之敏感度分析…….45
圖3-213~7%指數分券信用價差變化……… 45
參考文獻 參考文獻
Andersen, L., J. Sidenius, and S. Basu (2003), All your hedges in one basket, Risk 16, pp.67-72.
Andersen, L. and J. Sidenius (2005), Extensions to the Gaussian Copula:random recovery and random factor loadings, Journal of Credit Risk 1(1), pp. 29-70.
Anson M.J.P., F.J. Fabozzi, M.Choudhry and R.R.Chen (2004), Credit derivatives—instruments, applications, and pricing, John Wiley &Sons, Inc.
Belkin, B., S. Suchower, and L.R. Forest (1998), A one-parameter representation of credit risk and transition metrics, CreditMetrics Monitor, 3rd Quarter 1998, pp.46-56.
Black, F. and J. C. Cox (1976), “Valuing corporate securities: some effects of bond indenture provisions,” Journal of Finance 31, pp.351-367.
Bluhm, C., L. Overbeck and C. Wagner (2002), An introduction to credit risk modeling, Chapman & Hall
Brigo, D. and A. Alfonsi (2005), Credit default swap calibration and derivatives pricing with the SSRD Stochastic Intensity Model, Finance and Stochastics 9(1), pp.29–42.
Brigo, D. and F. Mercurio (2001), Interest rate models: theory and practice. Springer Verlag.
Carey M. (1998), “Credit risk in private debt portfolios,” Journal of Finance 53(.4), pp. 1363-1387.
Cherubini, U., E. Luciano and W. Vecchiato (2004), Copula methods in finance, John Wiley & Sons, Ltd.
Choudhry, M.(2004),”Structured credit products-credit derivatives & synthetic securitization ”, Wiley Finance
Cifuentes, A. and G. O’Connor (1996), The binomial expectation method applied to CBO/CLO analysis, Moody’s Special Report, Dec 13th 1996
Crosbie, P.J. and J.R. Bohn (2002), ”Modeling default risk”, Moody’s KMV
Crouhy, M., D. Galai and R. Mark (2000), ”A comparative analysis of current credit risk models”, Journal of Banking and Finance,24, pp.59-117.
Davis, M. and V. Lo (2001), “Infectious defaults,” Quantitative Finance 1, pp. 382-387.
Delianedis, G. and R. Geske (1998), "Credit risk and risk neutral default probabilities: information about migrations and defaults," University of California at Los Angeles, Anderson Graduate School of Management 1114, Anderson Graduate School of Management, UCLA.
Duffie, D. and K. Singleton (1999), “Modeling term structure of defaultable bonds,” Review of Financial Studies, 12, pp. 687-720.
Duffie, D. and N. Garleanu (2001), “Risk and valuation of collateralized debt obligations,” Finance Analysis Journal 57(1), pp. 41-59.
Frey, R. and A. J. McNeil (2001), “Modeling dependent defaults,” Working Paper, Department of Mathematics, ETH Zurich.
Galiani, S.S. (2003), “Copula functions and their application in pricing and risk managing multiname credit derivative product”, working paper,
Garcia, J.,T. Dwyspelaere, L. Leonard, T. Alderweireld and T.V. Gestel (2005),”Comparing bet and cash flows CDO’s ”, working paper
Giesecke, K. (2001), “Structural modeling of correlated defaults with incomplete information,” working paper, Humboldt University.
Giesecke, K. and S. Weber (2004), “Cyclical correlations, credit contagion, and portfolio losses,” Journal of Banking and Finance 28(12), pp.3009-3036.
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 , 13th Sep. 2004
Gordy,M.B.(2000),”A comparative anatomy of credit risk models”, Journal of Banking and Finance,24, pp. 119-149.
Gupton, G.M.,C.C. Finger and M. Bhatia (1997), “ CreditMetrics -technical document”, Morgan Guaranty Trust Company
Gupton, G.M. (2004),”Portfolio credit risk models”, credit derivatives –the definitive guide edited by Jon Gregory, Risk Books
Huang, J.Z. and M. Huang (2003), How much of the corporate-treasury yield spread is due to credit risk?, working paper, GSB, Stanford University.
Hull, J. and A. White (2004), “Valuation of a CDO and an n-th to default CDS without Monte Carlo simulation,” Journal of Derivatives 12(2), pp.8-48.
Hurst,R.R.(2001),”CDOs backed by ABS and commercial real estate”, Investing in collateralized debt obligations, edited by Frank J. Fabozzi and Laurie S. Goodman
Jarrow, R., D. Lando, and S. Turnbull (1997), “A Markov model for the term structure of credit spread,” Review of Financial Studies 10, pp.481- 523.
Jarrow, R. and S. Turnbull (1995), “Pricing derivatives on financial securities subject to credit risk,” Journal of Finance 50 , pp.53- 85.
Jarrow, R. and F. Yu (2001), “Counterparty risk and the pricing of defaultable securities,” The Journal of Finance 56, pp.1765- 1799.
Kim, J. (1999), A way to condition the transition matrix on wind, CreditMetrics Monitor, 1st Quarter 1999, pp.1-12.
Lando, D. (1998), “On Cox processes and credit risky securities,” Review of Derivatives Research, Vol.2, pages 99-120.
Laurent, J.P and J. Gregory (2005), Basket default swaps, CDOs and Factor Copulas, Journal of Risk 7(4), pp.103-22..
Leland, H.E. (2004), Predictions of expected default frequencies in structural models of debt, working paper.
Lee, C.W., C.K. Kuo and J.L. Urrutia (2004), “A Poisson model with common shocks for CDO valuation,” The Journal of Fixed Income 14(3), pp.72-82.
Li, D.X. (2000), “On default correlation: A copula function approach,” The RiskMetrics Group working paper number 99-07
Li, D.X. (2002), “Valuing synthetic CDO tranches using copula function approach,” The RiskMetrics Group working paper
Lin, S.Y. (2004), “Two essays on credit derivatives: CB asset swap and CDO”, Working Paper
Marshall, A.W. and I. Olkin (1988),”Families of multivariate distributions,” Journal of the American Statistical Association, pp.834-841
Meneguzzo, D. and W. Vecchiato (2004), “Copula Sensitivity in Collateralized Debt Obligations and Basket Default Swaps,” The Journal of Futures Markets, Vol. 24(1), pp.37-70.
Merton, R. (1974), “On the pricing of corporate debt: The risk structure of interest rates,” Journal of Finance 29, pp.449-470.
Mina, J. (2001) ,“Mark-to-market, oversight, and sensitivity analysis of CDO’s”, working paper number 01-02, RiskMetrics Group Dec 2001
Moody’s (2001),” Default and recovery rates of corporate bond issuers:2000”,Moody’s Investor Service, February 2001
Moody’s (2006), Default and Recovery Rates of Corporate Bond Issuers, 1920-2005, Special Comment
Perraudin, W. (2004), Structured credit products- pricing, rating, risk management and BaselⅡ, Risk Books
Picone, D.(2004),”A survey of CDOs and their use in bank balance sheet management”, Structured Credit Products-pricing,rating,risk management and BaselⅡ edited by William Perraudin.
Rogge E. and J. Schonbucher (2003), “Modeling dynamic portfolio credit risk,” working paper.
Schorin, C. and S. Weinreich (2001),”Introduction to collateralized debt obligations”,Investing in collateralized debt obligations, edited by Frank J. Fabozzi and Laurie S. Goodman
Schonbucher J. and D. Schubert (2001), “Copula-dependent default risk in intensity models,” working paper, Department of Statistics, Bonn University.
Sklar, A. (1959), “Fonctions de repartition a n dimensions et leurs marges,” Pub. Inst. Statisr. Univ. Paris, 8, pp.229-231.
Voort, M. (2004), Double default correlation, working paper, Econometric Institute
Wilde, T. (1997), “CreditRisk+: a credit risk management framework”, Credit Suisse First Boston
Zhou, C. (2001), “An analysis of default correlations and multiple defaults,” The Review of Financial Studies, Vol. 14(2), pp.555-576.
  • 同意紙本無償授權給館內讀者為學術之目的重製使用,於2009-03-06公開。
  • 不同意授權瀏覽/列印電子全文服務。

  • 若您有任何疑問,請與我們聯絡!
    圖書館: 請來電 (02)2621-5656 轉 2281 或 來信