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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/33920
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/33920


    Title: 信用風險尾巴機率之研究
    Authors: 楊立民
    Contributors: 劉惠美
    楊立民
    Keywords: 信用風險損失分配
    同質估計法
    蒙地卡羅法
    Date: 2004
    Issue Date: 2009-09-17 18:48:48 (UTC+8)
    Abstract:   由於整體金融環境的改變,資金的放款與融貸業務日益蓬勃,信用風險造成的呆帳問題成為銀行所承擔最大的風險來源之一,巴塞爾資本適足協定要求各銀行對其債權訂定風險權數,本文提出的同質性估計法即為內建評等法的應用。
      為探討投資組合在發生極大損失的尾端機率,我們從估計損失分配的尾巴衰退率著手,先以Glasserman於2004提出的同質法估計為基礎,並將獨特風險改變為t分配的假設下進行估計。此外,考慮到經濟現象的損失大多偏向厚尾分配,故導入Fréchet分配於獨特風險中,並藉以調整同質法進行估計。進一步我們使用蒙地卡羅模擬法來做為配適好壞比較的依據,模擬次數為100000次,以瞭解在常態分配、t分配及Fréchet分配的假設下尾端機率估計的優劣。
      結果發現,不同的獨特風險分配假設下,並沒有一致最佳的估計方法,在各群體同質性很高的投資組合中,t分配的估計是較為準確的,而且對於假設獨特風險在Fréchet分配時,不管何種投資組合,t分配同質法都能表現得不錯,相形之下,常態分配同質法的估計往往過於高估損失機率。另外,在損失設定在很小的水準時,不管何種同質估計法對損失機率都不太能估計得很準確。
    Reference: 中文部份
    1. 元大京華證券,2005,風險管理e學苑,http://riskmgmt.yuanta.com.tw/。
    2. 阮建豐,2002,「利用混合模型估計風險值的探討」,國立政治大學統計研究所碩士論文。
    3. 黃向義,2001,「極值理論應用於風險值估計」,國立臺北大學統計研究所碩士論文。
    4. 賴柏志,2003,「關聯結構在信用風險管理之運用」,金融聯合徵信中心,http://www.jcic.org.tw/。
    英文部份
    [1] Bassi, F., P. Embrechts, and M. Kafetzaki. (1998). Risk management and quantile estimation. in Adler, R. J. Feldman, R. E. Taqqu, M. S. (Eds.). A Practical Guide to Heavy Tails, 111-130. Birkhäuser, Boston.
    [2] Bluhm, C., L. Overbeck, and C. Wagner. (2002). An Introduction to Credit Risk Modeling. Chapmen & Hall/CRC, London.
    [3] Dembo, A., and O. Zeitouni. (1998). Large Deviations Techniques and Applications, 2nd ed. Springer-Verlag, New York.
    [4] Fisher, R. A., and L. H. C. Tippett. (1928). Limiting forms of the frequency distribution of the largest or smallest member of a sample. Proceedings Cambridge Philosophical Society, 24:180-190.
    [5] Glasserman, P. (2003). Monte Carlo Methods in Financial Engineering. Springer, New York.
    [6] Glasserman, P. (2004). “Tail approximations for portfolio credit risk”, The Journal of Derivatives, 4:24-43.
    [7] Heffernan, J., and J. Tawn. (2003). Extreme Value Theory. Powerpoint. Lancaster University.
    [8] Jorion, P. (2000). Value at Risk, 2nd ed. McGrall-Hill, New York.
    [9] Kalkbrenner, M., H. Lotter, and L. Overbeck. (2004). “Sensible and efficient capital allocation for credit portfolios.” Risk, 17:S19-S24.
    [10] Leadbetter, M. R., G. Lindgren, and H. Rootzén. (1983). Extremes and related properties of random sequences and processes. Springer, Berlin.
    [11] Li, D. (2000). “On default correlation: A copula function approach.” The Journal of Fixed Income, 9:43-54.
    [12] Lucas, A., P. Klaassen, P. Spreij, and S. Straetmans. (2001). “An analytic approach to credit risk of large corporate bond and loan portfolios.” Journal of Banking & Finance, 25:1635-1664.
    [13] Nocedal, J., and M. Wright. (1999). Numerical Optimization. Springer-Verlag, New York.
    [14] Sklar, A. (1959). Fonctions de répartition à n dimensions et leur marges. Publ. Int. Stat Univ., Paris, 8:229–231.
    [15] Trück, S., and J. Peppel. (2003). Credit Risk Models in Practice – A Review. Physica Veriag, Heidelberg.
    Description: 碩士
    國立政治大學
    統計研究所
    92354020
    93
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0923540202
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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