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    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/34001


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    題名: 因子相關性結構模型之下合成型擔保債權憑證之評價與避險
    The Pricing and Hedging of Synthetic CDO Under Factor Copula Models
    作者: 林恩平
    貢獻者: 江彌修
    Chiang, M.H.
    林恩平
    關鍵詞: 因子相關性結構
    合成型擔保債權憑證
    分券
    Factor Copula
    Synthetic CDO
    Tranche
    日期: 2005
    上傳時間: 2009-09-17 19:04:01 (UTC+8)
    摘要: 　　近年全球市場出現一些以信用違約交換(CDS)為基礎來編列之信用指數(credit indices)，如DJ iTraxx Europe與DJ CDX.NA等，而以這些信用指數為參考資產組合之合成型擔保債權憑證(Synthetic CDO)契約也定期被推出，由於其為標準化契約，故次級市場相當具有流動性，使得全球合成型擔保債權憑證無論在交易量或發行量皆成長快速。
    　　本研究在單因子相關性結構模型之架構下，利用Hull & White (2004)所提出之機率杓斗法則(Probability Bucketing Method)建立合成型擔保債權憑證之評價模型，並於評價之外增加分券(Tranche)風險衡量指標之計算，我們發現額外得到分券之風險衡量指標僅需增加約4%的程式運算時間。本研究之評價模型同時可用於分券避險參數之求算，且不會有蒙地卡羅模擬法(Monte Carlo Simulation)之下避險參數不穩定的情形。
    我們發現分券已實現之損失會使分券所面對之風險下降，而分券的信用增強(Credit Enhancement)遭受損耗則使分券所面對之風險上升，故權益分券(Equity Tranche)於契約前期所面對之信用風險大於契約後期，次償分券(Mezzanine Tranche)則是於契約後期面對較大之信用風險。關於分券避險，我們可選擇利用標的信用指數或單一資產信用違約(Single-name CDS)交換來進行避險。最後我們對分券進行違約相關性(Correlation)與違約回復率(Recovery Rate)之敏感度分析，發現權益分券的信用價差與資產違約相關性呈反向關係，而與違約回復率呈正向關係；相反的，先償分券(Senior Tranche)的信用價差則與相關係數呈正向關係，與違約回復率呈反向關係；兩參數對次償分券信用價差之影響則沒有一定的趨勢。
    參考文獻: 1.Altman, E.I., B. Brady, A. Resti and A. Sironi(2004),“The link between default and recovery rate: theory, empirical evidence and implications”, Journal of Business
    2.Andersen, L., J. Sidenius, and S. Basu (2003), “All your hedges in one basket”, Risk magazine, November 2003.
    3.Andersen, L. and J. Sidenius (2004), “Extensions to the Gaussian copula：random recovery and random factor loadings”, working paper, Bank of America.
    4.Black, F. and J. C. Cox (1976), “Valuing corporate securities：some effects of bond indenture provisions”, Journal of Finance 31, pages 351-367.
    5.Bluhm, C., L. Overbeck and C. Wagner (2002), “An introduction to credit risk modeling”, Chapman & Hall.
    6.Burtschell, X., J.-P. Laurent. and J. Gregory (2005), “A comparative analysis of CDO pricing models”, working papers, BNP-Paribas.
    7.Cifuentes, A. and G. O’Connor (1996), “The binomial expectation method applied to CBO/CLO analysis,” Moody’s Special Report, Dec 13th 1996
    8.Gibson, M. (2004), “Understanding the risk of synthetic CDOs”, FEDS Discussion Papers, no. 2004-36, Board of Governors of the Federal Reserve System.
    9.Greenberg, A., D. O’Kane and L. Schloegl (2004), “LH+: a fast analytical model for CDO hedging and risk management,” Lehman Brothers Quantitative Credit Research Quarterly Report.
    10.Hellqvist, M. (2005), “Comparison of approximation methods for combinations of differently distributed random variables”, Mat-2.108 Independent research project in applied mathematics, Helsinki University of Technology.
    11.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), pages 8-48.
    12.Hull, J. and A. White (2005), “The perfect copula”, working paper, Joseph L. Rotman School of Management, University of Toronto..
    13.Jarrow, R., D. Lando, and S. Turnbull (1997), “A Markov model for the term structure of credit spread”, Review of Financial Studies 10, pages 481- 523.
    14.Jarrow, R. and S. Turnbull (1995), “Pricing derivatives on financial securities subject to credit risk”, Journal of Finance 50, pages 53- 85.
    15.Jarrow, R. and F. Yu (2001), “Counterparty risk and the pricing of defaultable securities”, The Journal of Finance 56, pages 1765- 1799.
    16.Laurent, J.P. and J. Gregory (2003), “Basket default swaps, CDO’s and factor copulas”, working paper, ISFA Actuarial School, University of Lyon
    17.Laurent, J.P. and J. Gregory (2004), “In the core of correlation”. Risk magazine, October, pp. 87-91
    18.Li, D. X. (2000), “On default correlation: A copula function approach,” The RiskMetrics Group working paper number 99-07
    19.Merton, R. (1974), “On the pricing of corporate debt：The risk structure of interest　rates,” Journal of Finance 29, pages 449-470.
    20.Peretyatkin, V. (2006), “HPM+: a fast analytical model to pricing synthetic CDOs”, working paper, Imperial College and Rabobank International
    21.蔡麗君(2005)，隨機違約強度模型下CDO之評價與分析－Copula方法，國立政治大學金融研究所。
    描述: 碩士
    國立政治大學
    金融研究所
    93352036
    94
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0093352036
    資料類型: thesis
    顯示於類別:[金融學系] 學位論文

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