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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/36923
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/36923

    Title: 探討單因子複合分配關聯結構模型之擔保債權憑證之評價
    Pricing CDOs with One Factor Double Mixture Distribution Copula Model
    Authors: 邱嬿燁
    Chiou, Yan ya
    Contributors: 劉惠美
    Liu, Hui mei
    Chiou, Yan ya
    Keywords: 擔保債權憑證
    collateralized debt obligation
    one factor copula model
    closed skew normal distribution
    mixture distribution
    Date: 2007
    Issue Date: 2009-09-18 20:10:02 (UTC+8)
    Abstract: 依據之前的文獻研究,市場上主要是在LHP (Large Homogeneous Portfolio) 假設下利用單因子常態關聯結構模式(One factor double Gaussian copula model) 評價擔保債權憑證 (Collateralized debt obligation, CDO)。但這會造成擔保債權憑證的評價與市場報價的差距過大,且會造成base correlation偏斜的情況。Kalemanova et al. (2007) 提出用Normal inverse Gaussian (NIG) 取代常態分配評價擔保債權憑證,此模型不但計算快速而且可以準確估計權益分券 (equity tranche) 的價格,但是它也過於高估了其它的分券的價格。
    在本文中使用多變量封閉常態分配(Closed skew normal, 簡稱CSN) 分配取代NIG分配作擔保債權憑證分券的評價,CSN分配具有常態分配的性質,其線性組合仍具有封閉性的特質,且具有較多的參數以控制分配的偏態與峰態。但是與單因子常態關聯結構模式相同,多變量封閉常態分配的單因子關聯結構模式仍然無法估計的很準確,僅有在最高等級分券(senior tranche)的評價上有明顯的改進。
    This article extends the Large Homogeneous Portfolio (LHP) and one factor double Gaussian copula approach for pricing CDOs. In the literature, the one factor double Gaussian copula model under LHP assumption fails to fit the prices of CDO tranches, moreover, it leads to the implied base correlation skew. Some researchers proposed using one factor double NIG copula model to price CDO tranches. It not only economizes on time but also fits the equity tranches exactly, but NIG models do not price other tranches well simultaneously. On the other hand, we substitute the NIG distribution with the Closed Skew normal (CSN) distribution. This family also has properties similar to the normal distribution, which is closure under convolution, and has extra parameters to control the shape. By using this model we get a better fit in the senior tranches, but it seriously overprices subordinate tranches. Thus we consider a mixture distribution of NIG and CSN distributions. The employments of this mixture distribution are comparatively well, and furthermore it brings more flexibility to the dependence structure.
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    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0095354007
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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