政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/118241
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文笔数/总笔数 : 113392/144379 (79%)
造访人次 : 51224579      在线人数 : 894
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻
    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/118241


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/118241


    题名: 擔保貸款憑證之評價:使用Factor Copula方法
    Using Factor Copula Method to Price Collateralized Loan Obligation
    作者: 吳佳璇
    贡献者: 林士貴
    蔡政憲

    吳佳璇
    关键词: 關聯函數
    因子關聯函數
    單因子模型
    擔保債權憑證
    擔保貸款憑證
    Copula
    One factor model
    Factor copula
    CDO
    CLO
    日期: 2018
    上传时间: 2018-07-03 17:26:46 (UTC+8)
    摘要: 擔保債權憑證在1996後蓬勃發展,但卻在2008年成為全球金融風暴的問題之一,在沉寂幾年後近幾年來德意志銀行(Deutsche Bank)、高盛集團(Goldman Sachs)、摩根大通(JP Morgan)、法國興業銀行(Societe Generale)及花旗銀行(Citi Bank)等都曾嘗試復推擔保債權憑證商品,顯示這類商品其對於買賣方皆是吸引人的。隨著擔保債權憑證發行量的攀升,此商品的評價更顯其重要,本文使用因子關聯函數模型(Factor Copula),其優點為計算快速,並加入市場因子來當客觀標準,避免關聯函數法應用在不同市場資產情況下的不合理假設。實證部分以Venture在2016年發行的擔保貸款憑證為例,進行評價求得分券之公平溢酬,並針對評價過程提出可改善的地方。
    The Collateralized Debt Obligation(CDO) boomed after 1996, but it became one of the problems of the global financial crisis in 2008. After a few years of silence, Deutsche Bank, Goldman Sachs, JPMorgan, France Societe Generale and Citi Bank have tried to reintroduce CDO, showing that CDO are attractive to buyers and sellers. With the increase in the issuance of CDO, the pricing of this commodity is even more important. This paper uses Factor Copula model, which has the advantages of fast calculation, adds market factors as objective criteria, and avoid the unreasonable assumption that the correlation function method is applied to different market assets. The empirical part uses the CLO issued by Venture in 2016 as an example to evaluate the fair premium of the tranche, and propose improvements to the pricing process.
    參考文獻: [1] 林彥儒(2015)。Copula模型在信用連結債券的評價與實證分析。未出版之博(碩士)論文,國立政治大學,金融學系研究所,台北市。
    [2] 段登宇(2008)。擔保債權憑證CDO之訂價與分析-單因子模型及機率水桶法之應用未出版之博(碩士)論文,世新大學,財務金融學系,台北市。
    [3] 廖四郎、李福慶,(2005)。擔保債權憑證之評價-Copula分析法。
    [4] 蔡宗翰,(2006)。抵押債權憑證之評價:Factor Copula 與JLT模型之應用。未出版之博(碩士)論文,國立清華大學,統計學研究所,新竹市。
    [5] 戴嘉雄,(2006)。擔保債權憑證之信用價差評價- Copula分析法。未出版之博(碩士)論文,國立中山大學,財務管理學系碩士在職專班,高雄市。

    [1] Andersen, L. and J. Sidenius(2004). “Extensions to the Gaussian copula:random recovery and random factor loadings”, working paper, Bank of America.
    [2] Anson M. J. P., F. J. Fabozzi, M. Choudhry and R. R. Chen(2004). “Credit derivatives-instruments, applications, and pricing”, John Wiley &Sons, Incorporated.
    [3] Belkin, B., S. Suchover, and L. Forest (1998). “A one-parameter representation of credit risk and transition matrices”, Credit Metrics Monitor, 1(3), pages 46-56.
    [4] Black, F. and Cox, J. C. (1976). “Valuing corporate securities:some effects of bond indenture provisions”, Journal of Finance ,31, pages 351-367.
    [5] Carey M.(1998). “Creditrisk in private debt portfolios,” Journal of Finance, 53, pages1363-1387.
    [6] Cifuentes, A.,and Connor G.O. (1996) . “The Binomial expansion method applied to CBO/CLO analysis”, Moody`s Investors Service Special Report.
    [7] Cifuentes, A.,and Connor G.O. (1998) . “The double Binomial method and it’s application to a special case of CBO structures”, Moody`s Investors Service Special Report.
    [8] Das, S., Fong, G. and Geng, G. (2001). “The impact of correlated default risk on credit portfolios,"Journal of Fixed Income, 11, pages 9-19.
    [9] Duffie, D. and K. Singleton (1999). “Modeling term structure of defaultable bonds”, Review of Financial Studies, 12, pages 687-720.
    [10] Darrell, D. and Gârleanu N., (2001). “Risk and valuation of collateralized debt obligations”, Financial Analysts Journal, pages 41-59.
    [11] Galiani, S.S. (2003). “Copula functions and their application in pricing and risk managing multiname credit derivative product”, working paper.
    [12] Gregory, J. and J. P. Laurent (2004). “In the core of correlation”, Risk, pages 87-91.
    [13] Gibson, M. (2004). ”Understanding the risk of synthetic CDOs”, Finance and Economics Discussion Series, 36, Federal Reserve Board.
    [14] Giesecke, K.(2001). “Structural modeling of correlate defaults with incomplete information,"working paper, Humboldt University.
    [15] Goodman, L.S. (2002). “Synthetic CDOs: an introduction”, The Journal of Derivatives, 9(3), pages 60-72.
    [16] Gupton, G.M., C.C. Finger, and M. Bhatia (1997). “CreditMetrics-technical document”, Morgan Guaranty Trust Company.
    [17] Hull, J. and A. White (2004). “Valuation of a CDO and an n-th to default CDS without Monte Carlo simulation”, The Journal of Derivatives, 12(2), pages 8-48.
    [18] Introduction of Credit Derivatives, Chuang, M.C. , Retrieved June 06 2018, from https://drive.google.com/file/d/0B1qrE20J1V2YdGw4V05IeThURmM/view
    [19] Jarrow, R., D. Lando, and S. Turnbull (1997). “A Markov model for the term structure of credit spread”, The Review of Financial Studies, 10, pages 481-523.
    [20] Jarrow, R., and S. Turnbull (1995). “Pricing Derivatives on Financial Subject to Credit Risk”, Journal of Finance, 50, pages 53-68.
    [21] Jarrow, R., and F. Yu (2001). “Counterparty risk and pricing of defaultable securities”, Journal of Finance, 56, pages 1765-1799.
    [22] Lando, D. (1998). “On Cox processes and credit risky securities,” Review of Derivatives Research, Vol.2, pages 99-120.
    [23] Laurent, J-P. and J. Gregory (2003). “Basket default swaps, CDO’s and factor copulas”, Working Paper, ISFA Actuarial School, University of Lyon.
    [24] Li, D.X. (2000). “On Default Correlation: A Copula approach”, Journal of Fixed Income, 9, pages 43-54.
    [25] Li, D.X. (2002). “Valuing synthetic CDO tranches using copula function approach”, The RiskMetrics Group working paper.
    [26] Merton, R.C., (1974). “On the pricing of corporate debt: The risk structure of interest rates”, Journal of Finance, 29, pages 449-470.
    [27] Schonbucher J. and D. Schubert (2001), “Copula-dependent default risk in intensity models”, working paper, Department of Statistics, Bonn University.
    [28] Sklar, A. (1959). “Fonctions de repartition an dimensions et leurs marges”, Publication of the Institute of Statistics of the University of Paris, 8, pages 229-231.
    [29] Vasicek, O. A. (1997). “The loan loss distribution”, Working Paper, KMV.
    描述: 碩士
    國立政治大學
    金融學系
    105352031
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0105352031
    数据类型: thesis
    DOI: 10.6814/THE.NCCU.MB.006.2018.F06
    显示于类别:[金融學系] 學位論文

    文件中的档案:

    档案 大小格式浏览次数
    203101.pdf1080KbAdobe PDF222检视/开启


    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈