English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 109948/140897 (78%)
Visitors : 46074341      Online Users : 708
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/63192
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/63192


    Title: 信用連結債券評價—Factor Copula模型應用
    Application of Factor Copula Model on the Valuation of Credit-Linked Notes
    Authors: 朱婉寧
    Contributors: 廖四郎
    朱婉寧
    Keywords: 信用連結債券
    違約機率
    Factor Copula模型
    credit-linked notes
    default probability
    Factor Copula Model
    Date: 2012
    Issue Date: 2014-01-02 13:56:12 (UTC+8)
    Abstract: 信用連結債券的價值主要取決於所連結資產池內的資產違約情況,因此過去有許多文獻在評價時會利用Copula模擬各資產的違約時點,或是用Factor Copula估算他們在各時點下的違約機率。而本研究以Gaussian Factor Copula模型為主軸,對資產池違約機率做估計,以得到連結該資產池的信用連結債券價值。但過去文獻較常以給定參數的方式進行評價,本研究進一步利用市場實際資料估出模型參數並加入產業因子,以期達到符合市場的效果。
    本研究利用已知的違約資訊對照模型結果,發現在給定原油價格成長率、產業GDP成長率及CAPM殘差之後,使用Factor Copula模型在資產池小且違約比例過高時容易低估損失,主要原因在於各資產的違約機率並非逼近1。且模型算出的預期損失會隨著距今時間變長而增加,但若資產池實際上沒有更多違約公司,模型的結果就可能會高估損失。而所有的變數又以參考價差對該商品價值的影響最大,因參考價差的數值取決於該公司的信用評等,因此可知信用連結債券價值主要還是與各公司信評有最大相關。
    The value of credit linked notes depends on whether the reference entities in the linked asset pool default or not, so some previous studies used Copula model to simulate the times to default or Factor Copula model to get the default probability. In this paper, with the Gaussian Factor Copula model adopted and industry factors taken into account, the default probability is estimated in order to obtain the value of the credit linked notes. Then, unlike other previous studies using the given parameters, this paper evaluated the parameters by using the model as well as market data, hoping to achieve the goal that results can reflect the real market situation.
    With real default information compared with the modeling results, three findings can be drawn given the growth rate of oil price, the growth rate of industrial GDP and the residuals of CAPM. First, the loss will be underestimated if the asset pool is small and the default proportion is too high mainly because not all the default probability approximates one. Second, expected default probability will be directly proportional to the time period between the present and the expected moment. So if there are not so many defaulting companies, then the loss might be overestimated. Last, the reference spread has the most impact on the product value among all the variables, and as we know, the reference spread of a company depends on its credit rating. Therefore, compared with other factors, credit rating remains the most essential to credit linked notes.
    Reference: 英文部分
    [1] Davis, M. and V. Lo (2001). "Infectious defaults." Quantitative Finance 1: p. 382-397.
    [2] Duan, J.-C. (2010). Clustered Defaults. Risk magazine: p. 87-91.
    [3] Duan, J.-C. and A. Fulop (2012). "Multiperiod Corporate Default Prediction with the Partially-Conditioned Forward Intensity." Working Paper.
    [4] Gregory, J. and J.-P. Laurent (2004). "In the Core of Correlation." Risk 17: p. 87-91.
    [5] Hull, J. and A. White (2004). "Valuation of a CDO and an nth to Default CDS Without Monte Carlo Simulation." Journal of Derivatives 12(2): p. 8-23.
    [6] Hwang, R.-C. (2012). "A varying-coefficient default model." International Journal of Forecasting 28: p. 675-688.
    [7] Jarrow, R. A. and F. YU (2001). "Counterparty Risk and the Pricing of Defaultable Securities." Journal of Finance 56: p. 1765-1799.
    [8] Li, D. X. (2000). "On Default Correlation: A Copula Function Approach." Journal of Fixed Income: p. 41-50.
    [9] Longstaff, F., et al. (2004). "Corporate Yield Spreads: Default Risk or Liquidity? New Evidence from the Credit-Default Swap Market." Working Paper.
    [10] Rosch, D. and B. Winterfeldt (2008). Estimating Credit Contagion in a Standard Factor Model. Risk: p. 78-82.

    中文部分
    [1] 李美儀 (2005). "信用衍生性商品之擔保債權憑證之評價與分析." 國立政治大學金融研究所碩士論文.
    [2] 張耀洲 (2004). "擔保債權憑證之評價-BET、Copula與Factor Copula方法之比較與分析." 國立政治大學金融研究所碩士論文.
    [3] 郭銚倫 (2005). "信用評等分組下之合成型CDO評價." 國立政治大學金融研究所碩士論文.
    Description: 碩士
    國立政治大學
    金融研究所
    100352002
    101
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0100352002
    Data Type: thesis
    Appears in Collections:[金融學系] 學位論文

    Files in This Item:

    There are no files associated with this item.



    All items in 政大典藏 are protected by copyright, with all rights reserved.


    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 ©   - Feedback