| dc.contributor.advisor | 江彌修 | zh_TW |
| dc.contributor.advisor | Chiang, M.H. | en_US |
| dc.contributor.author (Authors) | 林恩平 | zh_TW |
| dc.creator (作者) | 林恩平 | zh_TW |
| dc.date (日期) | 2005 | en_US |
| dc.date.accessioned | 17-Sep-2009 19:04:01 (UTC+8) | - |
| dc.date.available | 17-Sep-2009 19:04:01 (UTC+8) | - |
| dc.date.issued (上傳時間) | 17-Sep-2009 19:04:01 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0093352036 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/34001 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 金融研究所 | zh_TW |
| dc.description (描述) | 93352036 | zh_TW |
| dc.description (描述) | 94 | zh_TW |
| dc.description.abstract (摘要) | 近年全球市場出現一些以信用違約交換(CDS)為基礎來編列之信用指數(credit indices)，如DJ iTraxx Europe與DJ CDX.NA等，而以這些信用指數為參考資產組合之合成型擔保債權憑證(Synthetic CDO)契約也定期被推出，由於其為標準化契約，故次級市場相當具有流動性，使得全球合成型擔保債權憑證無論在交易量或發行量皆成長快速。 本研究在單因子相關性結構模型之架構下，利用Hull & White (2004)所提出之機率杓斗法則(Probability Bucketing Method)建立合成型擔保債權憑證之評價模型，並於評價之外增加分券(Tranche)風險衡量指標之計算，我們發現額外得到分券之風險衡量指標僅需增加約4%的程式運算時間。本研究之評價模型同時可用於分券避險參數之求算，且不會有蒙地卡羅模擬法(Monte Carlo Simulation)之下避險參數不穩定的情形。我們發現分券已實現之損失會使分券所面對之風險下降，而分券的信用增強(Credit Enhancement)遭受損耗則使分券所面對之風險上升，故權益分券(Equity Tranche)於契約前期所面對之信用風險大於契約後期，次償分券(Mezzanine Tranche)則是於契約後期面對較大之信用風險。關於分券避險，我們可選擇利用標的信用指數或單一資產信用違約(Single-name CDS)交換來進行避險。最後我們對分券進行違約相關性(Correlation)與違約回復率(Recovery Rate)之敏感度分析，發現權益分券的信用價差與資產違約相關性呈反向關係，而與違約回復率呈正向關係；相反的，先償分券(Senior Tranche)的信用價差則與相關係數呈正向關係，與違約回復率呈反向關係；兩參數對次償分券信用價差之影響則沒有一定的趨勢。 | zh_TW |
| dc.description.tableofcontents | 第一章 緒論.................................1 第一節 研究背景.........................1 第二節 研究動機與目的...................9 第三節 研究架構........................10第二章 文獻探討.............................12 第一節 信用風險模型回顧.................12 第二節 擔保債權憑證評價模式.............14 第三節 擔保債權憑證避險參數之求算........22第三章 模型設定............................25 第一節 建立擔保債權憑證評價模型..........25 第二節 合成型擔保債權憑證之風險衡量指標...43 第三節 合成型擔保債權憑證避險參數之求算...47第四章 實證分析.............................52 第一節 合成型擔保債權憑證之評價..........53 第二節 合成型擔保債權憑證之風險分析......63 第三節 合成型擔保債權憑證分券之避險......74 第四節 敏感度分析......................82第五章 結論與建議..........................86 | 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/#G0093352036 | en_US |
| dc.subject (關鍵詞) | 因子相關性結構 | zh_TW |
| dc.subject (關鍵詞) | 合成型擔保債權憑證 | zh_TW |
| dc.subject (關鍵詞) | 分券 | zh_TW |
| dc.subject (關鍵詞) | Factor Copula | en_US |
| dc.subject (關鍵詞) | Synthetic CDO | en_US |
| dc.subject (關鍵詞) | Tranche | en_US |
| dc.title (題名) | 因子相關性結構模型之下合成型擔保債權憑證之評價與避險 | zh_TW |
| dc.title (題名) | The Pricing and Hedging of Synthetic CDO Under Factor Copula Models | en_US |
| dc.type (資料類型) | thesis | en |
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| dc.relation.reference (參考文獻) | 11.Hull, J. and A. White (2004), “Valuation of a CDO and an n-th to default CDS without Monte Carlo simulation”, Journal of Derivatives 12(2), pages 8-48. | zh_TW |
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| dc.relation.reference (參考文獻) | 18.Li, D. X. (2000), “On default correlation: A copula function approach,” The RiskMetrics Group working paper number 99-07 | zh_TW |
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| dc.relation.reference (參考文獻) | 20.Peretyatkin, V. (2006), “HPM+: a fast analytical model to pricing synthetic CDOs”, working paper, Imperial College and Rabobank International | zh_TW |
| dc.relation.reference (參考文獻) | 21.蔡麗君(2005)，隨機違約強度模型下CDO之評價與分析－Copula方法，國立政治大學金融研究所。 | zh_TW |
