| dc.contributor.advisor | 林信助 | zh_TW |
| dc.contributor.author (Authors) | 李承儒 | zh_TW |
| dc.creator (作者) | 李承儒 | zh_TW |
| dc.date (日期) | 2005 | en_US |
| dc.date.accessioned | 11-Sep-2009 17:06:47 (UTC+8) | - |
| dc.date.available | 11-Sep-2009 17:06:47 (UTC+8) | - |
| dc.date.issued (上傳時間) | 11-Sep-2009 17:06:47 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0093351037 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/30039 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 國際經營與貿易研究所 | zh_TW |
| dc.description (描述) | 93351037 | zh_TW |
| dc.description (描述) | 94 | zh_TW |
| dc.description.abstract (摘要) | 利用風險值作為投資組合的風險管理工具，必須考慮金融資產報酬率通常具有厚尾、高峰、波動叢聚以及資產間訊息與波動性的變化也會交互影響等現象；因此實證上通常以多變量GARCH模型作為估計投資組合變異數矩陣的方法。然而多變量GARCH模型卻存在有維度上的詛咒，當投資組合包含資產數增加時會加重參數估計上的困難度。另一種估計波動率的方法，稱為實現波動率，能比多變量GARCH模型更簡易地處理投資組合高維度的問題。本文即以實現波動率、BEKK多變量GARCH模型與CCC模型，並以中鋼、台積電、國泰金為研究對象，比較三種方法估計風險值的表現。而實證結果得到利用實現波動率確實適合應用在風險值的估計上，且在表現上有略勝一籌的現象。 | zh_TW |
| dc.description.tableofcontents | 1 前言 2 風險值、多變量GARCH模型與實現波動率 2.1 風險值觀念介紹與計算方法 2.1.1 變異數-共變異數法 2.1.2 歷史模擬法 2.1.3 蒙地卡羅模擬法 2.2 多變量GARCH模型 2.2.1 CCC模型 2.2.2 BEKK模型 2.3 實現波動率 3 實證研究 3.1 檢定方法 3.1.1 二項分配檢定 3.1.2 概似比檢定 3.1.3 條件涵蓋檢定法 3.2 資料來源 3.3 實證結果 3.3.1 實現波動率 3.3.2 CCC與BEKK模型 3.3.3 風險值回顧測試 4 結論與建議 4.1 結論 4.2 研究限制與未來研究方向 參考文獻 附錄 | zh_TW |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0093351037 | en_US |
| dc.subject (關鍵詞) | 風險值 | zh_TW |
| dc.subject (關鍵詞) | 多變量GARCH模型 | zh_TW |
| dc.subject (關鍵詞) | 實現波動率 | zh_TW |
| dc.subject (關鍵詞) | value at risk | en_US |
| dc.subject (關鍵詞) | multivariate garch | en_US |
| dc.subject (關鍵詞) | realized volatility | en_US |
| dc.title (題名) | 以實現波動率估計投資組合風險值 | zh_TW |
| dc.title (題名) | Value at Risk of Portfolio with Realized Volatility | en_US |
| dc.type (資料類型) | thesis | en |
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