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研究生: 邵惠敏
Shao, Hui Min
論文名稱: 離散型動態回復率模型之建構與應用
Discrete dynamic recovery rate modeling and its application
指導教授: 江彌修
學位類別: 碩士
Master
系所名稱: 商學院 - 金融學系
Department of Money and Banking
論文出版年: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 66
中文關鍵詞: 動態回復率合成型擔保債權憑證損失分配系統性風險
外文關鍵詞: dynamic recovery rate, CDO, loss distribution, systematic risk
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  • 本文主要研究動態回復率之建構。並搭配使用機率勺斗法,將資產之離散損失分配建構出合成型擔保債權憑證分劵損失分配。歸納出離散動態回復率對合成型擔保憑證分劵之風險承擔與信用價差變化。本文發現在動態回復率中,即使在相同條件下有一樣預期損失,能使其債權群組損失分配之標準差較固定回復率小,且可使投資組合巨額損失部份產生厚尾分配現象。動態回復率對各分劵面臨共同存活與違約機率具有緩和或增強分劵承擔風險之作用。在單因子高斯連繫結構靜態違約下,透過隨機回復率能增加動態系統性風險因子之描繪。類似於將系統風險因子分配由標準常態分配改成t分配或是債權群組間違約相關係提高。


    第一章 緒論 4
    第二章 文獻探討 7
    第一節 回復率介紹 7
    第二節 文獻回顧 10
    第三章 基本假設與模型設定 15
    第一節 合成型擔保債權憑證評價模型 15
    第二節 因子連繫模型(Factor Copula) 17
    第三節 Krekel 動態回復率模型 18
    第四節 Charaf 動態回復率模型 21
    第五節 機率勺斗法 27
    第四章 數值結果與分析 30
    第一節 回復率敏感度分析 31
    第二節 違約機率與違約條件下損失之關係 33
    第三節 債權群組累積損失分配 37
    第四節 動態回復率下各分劵風險特徵 45
    第五節 動態回復率對違約相關性之影響 51
    第六節 動態回復率對分劵系統風險之影響 55
    第五章 結論 58

    江彌修、岳夢蘭、林恩平,2009,「條件獨立假設下合成型擔保債權憑證之評價與避險」,《財務金融學刊》第17期,1-40
    江彌修、岳夢蘭、李蕙君,2008,「雙層保護合成型擔保債權憑證之評價與風險特徵研究」,《經濟論文》第36卷第3期,277-314
    Altman, E., Brady, B., Resti, A. and Andrea S., 2001, “Analyzing and Explaining Default Recovery Rates”, ISDA Research Report
    Altman, E., Resti, A. and Sironi, A., 2004, “Default Recovery Rates in Credit Risk Modeling: A Review of the Literature and Empirical Evidence”, Economic Notes by Banca Monte dei Paschi di Seina SpA, 183-208
    Altman, E. and Fanjul, G., 2004, “Defaults and Returns in the High-Yield Bond Market: Analysis through 2003”, working paper
    Altman, E., Brady, B., Resti, A. and Sironi, A, 2005,”The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications”, Journal of Business, 75(6), 2203-2227
    Altman, E., 2006, “Default recovery rates and LGD in Credit Modeling and Practice: An Updated Review of the Literature and Empirical Evidence”, working paper, New York University
    Amaroui, S. and Hitier, S., 2008, “Optimal Stochastic Recovery for Base Correlation”, working paper, BNP Paribas
    Amraoui, S., Hitier, S. and Laurent, J.P., “Pricing CDOs with State Dependent Stochastic Recovery Rates”, working paper, BNP Paribas
    Andersen, L. and Sidenius, J., 2004, “Extensions of the Gaussian Copula: Random Recovery and Random Factor Loadings”, The Journal of Credit Risk, 1, 29-70.
    Bakshi, G., Madan, D. and Zhang, F., 2001, “Understanding the Role of Recovery in Default Risk Models: Empirical Comparisons and Implied Recovery Rates”, Finance and Economics Discussion Series, 2001-37, Federal Reserve Board of Governors, Washington D.C.
    Duffie, D. and Singleton, K.J., 1999, “Modeling Term Structures of Defaultable Bonds”, Review of Financial Studies 12, 687-720.
    Duffie, D., 1998, “Defaultable term structure models with fractional recovery of par”, Graduate School of Business, Stanford University.
    Duffie, D and Singleton, K.J., 1999, ”Modeling the Term Structures of Defaultable Bonds”, Review of Financial Studies, 12, 687-720
    Ech-Chatbi C., 2008, “CDS and CDO Pricing with Stochastic Recovery”, working Paper
    Frye, J., 2000a, “Collateral Damage”, Risk, 13(4), 1-94
    Frye, J., 2000b, “Depressing Recoveries”, Risk, 13(11), 108-11
    Fridson, M. S., Garman, C. M. and Okashima, K., 2000, “Recovery rates: the search for meaning”, Merril Lynch & Co., High Yield Research
    Gupton, G.M., Gates, D. and Carty, L.V., 2000, “ Bank loan loss given default, Moody’s Investor Services”, Global Credit Research, November
    Hamilton, D.T., Gupton, G.M. and Berthault, A., 2001, “Default and recovery rates of corporate bond issuers: 2000”, Moody’s Investor Services, February
    Hull, J. and White, A., 2004, ”Valuation of a CDO and Nth to Default CDS without Monte Carlo Simulation”, Journal of Derivatives, 8-23.
    Hui, L., 2009,” On Models of Stochastic Recovery for Base Correlation”, working paper
    Jarrow, R., Lando, D. and Turnbull, S., 1997, “A Markov Model for the Term Structure of Credit Risk Spreads”, Review of Finance Studies, 481-523.
    Jarrow, Robert A. and Stuart M. Turnbull, 1995,” Pricing derivatives on securities subject to credit risk”, Journal of Finance 50, 53-86.
    Jokivuolle, E. and Peura, S., 2003, “A Model for Estimating Recovery Rates and Collateral Haircuts for Bank Loans”, working paper
    Kim, I.J., Ramaswamy, K. and Sundaresan, S., 1993, “Does default risk in coupons affect valuation of corporate bonds?: A contingent claims model”, Financial Management, 22:3, 117-131
    Krekel, M., 2008, “Pricing distressed CDOs with Base Correlation and Stochastic Recovery”, UniCredit Markets & Investment Banking
    Laurent, J.P. and Gregory, J., 2003, “Basket Default Swaps, CDO’s and Factor Copula”, working paper
    Li, D., 2000, “On Default Correlations: a Copula Function Approach”, Journal of Fixed Income, 9, 43-54.
    Li, H.,2009, “On Models of Stochastic Recovery for Base Correlation” MPRA Paper
    Longstaff, F.A. and Eduardo S. S., 1995, “A simple approach to valuing risk fixed and floating rate debt”, Journal of Finance, 89, 789-819.
    Mark, C. and Gordy, M. 2004, “Measuring systematic risk in recoveries on defaulted debt 1: firm-level ultimate LGDs “, Federal Reserve Board, working Paper
    Sanjiv R. Das, S.R. and Hanouna, P., 2009, “Implied Recovery”, working paper

    Schleifer, A. and Vishny, R., 1992, ” Liquidation values and debt capacity: a market equilibrium approach”, Journal of Finance, 47, 1343-1366.
    Zhou, C., 2001, “The term structure of credit spreads with default risk”, Journal of Banking and Finance 25, 2015-2040

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