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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/30939
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/30939


    Title: 信用損失分配之尾端機率估計-同質法與拉普拉斯近似法之比較
    Authors: 蔡旻樺
    Contributors: 劉惠美
    蔡旻樺
    Keywords: 信用風險損失分配
    同質性近似法
    拉普拉斯近似法
    蒙地卡羅模擬
    Date: 2004
    Issue Date: 2009-09-14
    Abstract: 信用風險為金融業經營上最大的風險來源,也是金融業損失的最主要的原因,近日企業紛紛不約而同的強調風險控管的重要性,風險控管更被視為下一波的競爭力,信用風險更是佔銀行各項風險之首。
    本文將著重信用風險損失機率分配之探討,然後針對兩種近似方法,同質性近似與拉普拉斯近似模式以及各種不同的投資組合,研究其與蒙地卡羅之配適情形,並嘗試利用比常態厚尾的t分配,目的是為了找出更加保守的估計方式。
    分析結果顯示,每一種近似法都沒有絕對的好或壞,各有其相對帶來的效益,同質性近似法不需花費很長的時間,且其結果大致與蒙地卡羅模擬相符,相對來說,拉普拉斯近似法所需的時間較長,但是其對於估計很小之違約機率的準確性是非常有幫助的。整體而言,此二種估計法皆可提供風險管理者作為估計違約機率的參考。
    Reference: 一、 中文部份
    1. 何志偉,2004年,「信用損失分配之估計」,國立台北大學統計學系碩士論文。
    2. 卓逸愷,2004年,「下方風險限制下之最適資產配置」,國立高雄第一科技大學風險管理與保險研究所碩士論文。
    3. 洪瑩珊,2004年,「信用風險之衡量方法:Copula函數的應用」,國立清華大學科技管理研究所碩士論文。
    4. 胡志宏,2003年,「新版巴塞爾資本協定對我國金融業信用風險管理之衝擊」,元智大學管理研究所碩士論文。
    5. 陳孟雅,2003年,「Basel II對銀行信用風險管理之影響」,東吳大學國際貿易學系碩士論文。
    6. 黃仁德、陳淑郁,200年,「信用風險衡量-信用風險加成模型」,台灣金融財務季刊,第五輯第三期,pp. 77-111。
    二、 英文部份
    1. Altman, E. I., and A. Saunder. (1998), “Credit risk measurement: Developments over the last 20 years,” Journal of Banking & Finance, Vol. 21, pp. 1721-1742.
    2. Basel Committee on Bank Supervision, “Credit Risk,”
    http://www.riskglossary.com/link/credit_risk.htm
    3. Bluhm, C., L. Overbeck, and C. Wagner. (2002), “Credit Risk Modeling,” Chapman & Hall/CRC, London.
    4. Danielsson, J., C. G. de Vries, and B. N. Jorgensen. (1998), “The Value of Value at Risk: Statistical Financial,Financial and Regulatory Considerations,” FRBNY Economic Policy Review, Vol. 4 , pp. 107-117.
    5. Dembo, A., J. D. Deuschel, and D. Duffie. (2004), “Large Portfolio Losses,” Finance and Stochastics, Vol. 8, pp. 3-21.
    6. Glasserman, P. (2004), “Tail Approximations for Portfolio Credit Risk,” The Journal of Derivatives, pp. 24-42.
    7. Glasserman, P., and J. Li. (2005), “Importance Sampling for Portfolio Credit Risk,” Management Science, forthcoming 2004.
    8. Hopper, G.. P. (1996), “Value at Risk: A new Methodology for Measuring Portfolio Risk,”. Business Review, pp. 19-29.
    9. Huisman, R., K.G. Koedijk, and R. A. J. Pownall. (1998), “VaR-x:Fat Tails in Financial Risk Management”, Journal of Risk, Vol. 1 , pp. 47-61.
    10. Jorion, P. (1996), “Risk2:Measuring the Risk in Value at Risk,” Financial Analysis Journal, Vol. 52, pp. 47-56.
    11. Jorion, P. (2000), “Value at Risk ,” McGraw-Hill, New York.
    12. Löffler, G. (2003), “The effects of estimation error on measures of portfolio credit risk,” Journal of Banking & Finance, Vol. 27, pp. 1427-1453.
    13. 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, Vol. 25, pp. 1635-1664.
    Description: 碩士
    國立政治大學
    統計研究所
    92354005
    93
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0923540051
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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