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    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/49017


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    題名: 考量隨機回復率與風險因子承載係數之CDO評價模型
    Pricing CDO with random recovery rate and random factor loading
    作者: 李慎
    Li, Shen
    貢獻者: 江彌修
    Chiang, Mi Hsiu
    李慎
    Li, Shen
    關鍵詞: 回復率
    風險因子承載係數
    基準違約相關係數
    擔保債權憑證
    隨機回復率
    隱含違約相關係數
    權益分券
    先償分劵
    信用價差
    校準
    CDO
    recovery rate
    random factor loading
    base correlation
    credit spread
    equity tranche
    senior tranche
    implied correlation
    BNP
    super senior tranche
    日期: 2009
    上傳時間: 2010-12-08 01:57:00 (UTC+8)
    摘要: 本研究以Amraoui & Hitier (2008)隨機回復率模型(BNP model)以及Andersen and Sidenius(2004)隨機風險因子承載係數模型(RFL model)為基礎，進行對分劵信用價差、債劵群組累積損失機率分配，以及對基準違約相關係數的影響等分析。我們發現當回復率改成動態後可以反映更多系統風險，權益分劵信用價差絕大多數都會下降。在累積損失機率分配方面加入BNP後變為較平滑；改用RFL則會使機率分配在小額損失處又產生一次起伏；同時考量BNP與RFL會使小額損失發生機率減少、極端損失機率增加。實作三組市場資料時，發現不管市場違約機率高或低，共同考慮BNP與RFL的模型在四個模型中是最適合擬和市價的，顯示在市價的校準上有更多彈性，特別是在承擔名目本金60~100%先償分劵的校準上只有共同考慮BNP與RFL的模型能發揮功效。
    參考文獻: 1.Altman, E., A. Resti and A. Sironi, 2004, “Default Recovery Rates in Credit Risk Modelling: A Review of the Literature and Empirical Evidence”, Economic Notes by Banca Monte dei Paschi di Seina SpA. Pp. 183-208.
    2.Ahluwalia, R. and L. McGinty, 2004, “A Model for Base Correlation Calculation”, JPMorgan, Credit Derivatives Strategy.
    3.Andersen, L. and J. Sidenius, 2004, “Extensions of the Gaussian Copula: Random Recovery and Random Factor Loadings”, The Journal of Gredit Risk, 1(1), pp. 29-70.
    4.Amaroui, S. and S. Hitier, 2008, “Optimal Stochastic Recovery for Base Correlation”. BNP Paribas, June 2008.
    5.Amraoui, S. , L. Cousot , S. Hitier and J. Laurent , 2009 “Pricing CDOs with State Dependent Stochastic Recovery Rates” , working paper.
    6.Bennani, N. , J. Maetz , 2009 ”A Spot stochastic Recovery Extension of the Gaussian Copula” , Munich Personal RePEc Archive.
    7.Ech-Chatbi C., 2008, “CDS and CDO Pricing with Stochastic Recovery” , working paper.
    8.Gaspar, R. M. and I. Slinko , 2007, “ On Recovery and Intensity’s correlation - A new class of credit risk models.” , working paper.
    9.Hull, J. and A. White, 2004, ”Valuation of a CDO and Nth to Default CDS without Monte Carlo Simulation”, Journal of Derivatives, 12(2) (Winter), pp. 8-23.
    10.Krekel, M., 2008, “Pricing distressed CDOs with Base Correlation and Stochastic Recovery”, UniCredit Markets & Investment Banking.
    11.Kakodkar, A., (ed.) 2009, “Coping with The Copula”, Merrill Lynch.
    12.Li, D. X., 2000, “On Default Correlations: a Copula Function Approach”, Journal of Fixed Incom, 9, pp. 43-54.
    13.Lamedica, P. , 2008 ,” The Bermuda Triangle of Super Senior Risk, Structured Credit Strategy” , working paper.
    14.O’Kane, D. and M. Livesey, 2004, “Base Correlation Explained”, Lehman Brothers Quantitative Credit Research Quarterly Report.
    15.Prampolini, A. and M. Dinnis, 2009, “CDO Mapping with Stochastic Recovery”, HSH Nordbank AG.
    16.Torresetti, R. , D. Brigo and A. Pallavicini ,2006, ”Implied correlation in CDO tranches：a Paradigm to be handled with care” , working paper.
    17.Yan,X. , 2008 , “Modelling the Dynamic Relationship between Systematic Default and Recovery Risk” , Quantitative Finance Imperial College Business School ,October 2008.
    18.林恩平，條件獨立假設下合成型擔保債群憑證之評價與避險，台灣財務金融學會，2009
    19.張立民，合成型擔保債權憑證之評價—考量異質分配與隨機風險因子承載係數，政治大學，2007
    描述: 碩士
    國立政治大學
    金融研究所
    97352029
    98
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0097352029
    資料類型: thesis
    顯示於類別:[金融學系] 學位論文

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