| dc.contributor.advisor | 劉惠美 | zh_TW |
| dc.contributor.advisor | Liu, Hui mei | en_US |
| dc.contributor.author (Authors) | 邱嬿燁 | zh_TW |
| dc.contributor.author (Authors) | Chiou, Yan ya | en_US |
| dc.creator (作者) | 邱嬿燁 | zh_TW |
| dc.creator (作者) | Chiou, Yan ya | en_US |
| dc.date (日期) | 2007 | en_US |
| dc.date.accessioned | 18-Sep-2009 20:10:02 (UTC+8) | - |
| dc.date.available | 18-Sep-2009 20:10:02 (UTC+8) | - |
| dc.date.issued (上傳時間) | 18-Sep-2009 20:10:02 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0095354007 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/36923 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 統計研究所 | zh_TW |
| dc.description (描述) | 95354007 | zh_TW |
| dc.description (描述) | 96 | zh_TW |
| dc.description.abstract (摘要) | 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。因此在本文中我們使用NIG與CSN複合分配之單因子關聯結構模式評價擔保債權憑證分券，在實例分析時得到極佳的評價結果，並且比單因子常態關聯結構模型具有更多的的參數以使模型更符合實際的需求。 | zh_TW |
| dc.description.abstract (摘要) | 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. | en_US |
| dc.description.tableofcontents | Chapter 1 Introductions 11.1. What Does Asset Securitization Means? 21.2. Collateralized Debt Obligations 31.2.1. Synthetic CDOs 41.3. Credit Default Swaps 51.3.1. Credit Default Swaps Index 5Chapter 2 Literature Review 82.1. Binomial Expansion Technique (BET) 82.2. Copula Model 92.3. One Factor Copula Model 92.4. Normal Inverse Gaussian Distribution 112.5. Closed Skew Normal Distribution 11Chapter 3 One Factor Double NIG Copula Model for Pricing CDOs 133.1. The Loss Distribution and Fair CDO Premium 133.2. Copula Method 153.3. One Factor Copula Model 173.4. Main Properties of the NIG Distribution 183.5. LHP Approximation in the One Factor Double NIG Copula Method 21Chapter 4 One Factor Double Mixture Distribution Copula Models for Pricing CDOs 244.1. The Introduction of Closed Skew Normal Distribution 244.2. One Factor Double CSN Copula Model 294.3. One Factor Double Mixture Distribution of NIG and CSN Distribution Copula Model 34Chapter 5 Numerical Results: Pricing the DJ iTraxx 365.1. Price iTraxx Tranches with the Four Models 365.2. The Loss Distributions for Four Models 385.3. Comparison of the Compound and Base Correlation 415.4. Conclusion 43References 45Appendix 48 | zh_TW |
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| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0095354007 | en_US |
| dc.subject (關鍵詞) | 擔保債權憑證 | zh_TW |
| dc.subject (關鍵詞) | 單因子關聯結構模式 | zh_TW |
| dc.subject (關鍵詞) | 多變量封閉常態分配 | zh_TW |
| dc.subject (關鍵詞) | 複合分配 | zh_TW |
| dc.subject (關鍵詞) | collateralized debt obligation | en_US |
| dc.subject (關鍵詞) | one factor copula model | en_US |
| dc.subject (關鍵詞) | closed skew normal distribution | en_US |
| dc.subject (關鍵詞) | mixture distribution | en_US |
| dc.title (題名) | 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 | zh_TW |
| dc.title (題名) | Pricing CDOs with One Factor Double Mixture Distribution Copula Model | en_US |
| dc.type (資料類型) | thesis | en |
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