Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/60043
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dc.contributor.advisor蔡政憲zh_TW
dc.contributor.author曾于芳zh_TW
dc.creator曾于芳zh_TW
dc.date2009en_US
dc.date.accessioned2013-09-04T07:00:26Z-
dc.date.available2013-09-04T07:00:26Z-
dc.date.issued2013-09-04T07:00:26Z-
dc.identifierG0097358018en_US
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/60043-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description風險管理與保險研究所zh_TW
dc.description97358018zh_TW
dc.description98zh_TW
dc.description.abstract台灣風險基礎資本額制度實施至今已將近七年,但風險係數卻從未調整,本研究主要針對股票指數與匯率之風險係數探討其是否有更新之必要,藉由1986年12月至2009年12月之資料,利用GARCH模型及EGARCH模型進行風險係數之估計,除了和風險基礎資本額制度相同,以風險值為考量外,另外加入條件尾端期望值,並比較其與風險值之差別。\n 實證結果發現,僅部分財務時間序列有顯著之槓桿效果,因此使用GARCH模型估計風險係數較為合適;所估計之風險係數,無論是股價指數或是匯率,其估計結果皆比現行標準高出許多。zh_TW
dc.description.abstractIn Taiwan, Risk-based capital (RBC) is set up in 2003. From 2003 until now, no matter how the economical environment has changed, the risk factors have remained all the same.This research mainly focuses on the risk factors of stock index and foreign exchange and wants to know if the risk factors need to be changed. The data this research encompasses is from December 1986 to December 2009.The risk factors are estimated by GARCH model and EGARCH model, utilizing not only the VaR but also the conditional tail expectation (CTE).\n From the result, only a few financial time series have shown leverage effect, therefore it is indeed more appropriate to apply GARCH model in risk factors estimation. Moreover, the risk factors from the result of this research, whether it is stock index or foreign exchange rate, are significantly higher than the risk factors standard applicable in Taiwan at the present.en_US
dc.description.tableofcontents1. 緒論 1\n 1.1 研究動機及目的 1\n 1.2 研究架構 3\n2. 各監理制度介紹 4\n 2.1 台灣RBC制度 4\n 2.2 美國RBC制度 6\n 2.3 歐盟Solvency II 制度 10\n 2.4 Basel II 制度 13\n3. 資料說明與研究方法 17\n 3.1 資料選取與範圍 17\n 3.1.1股價指數 17\n 3.1.2匯率 17\n 3.2 實證方法與說明 18\n 3.2.1單根檢定 18\n 3.2.2 GARCH 模型 19\n 3.2.3 EGARCH 模型 20\n 3.2.4 模型選擇準則 21\n 3.2.5 時間序列模擬 21\n 3.2.6 風險值與條件尾端期望值 21\n4. 實證結果與分析 24\n 4.1 股票指數 24\n 4.1.1敘述性統計分析與單根檢定 24\n 4.1.2 模型估計 25\n 4.1.3 風險係數之估計 26\n 4.2 匯率 33\n 4.2.1 敘述性統計分析與單根檢定 33\n 4.2.2 模型估計 34\n 4.2.3 風險係數之估計 35\n5. 結論與建議 40\n 5.1 結論 40\n 5.2 建議 42\n參考文獻 43\n附錄 44zh_TW
dc.format.extent459357 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen_US-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0097358018en_US
dc.subject風險基礎資本額制度zh_TW
dc.subject風險值zh_TW
dc.subject條件尾端期望值zh_TW
dc.subjectRBCen_US
dc.subjectGARCHen_US
dc.subjectEGARCHen_US
dc.subjectVaRen_US
dc.subjectETLen_US
dc.subjectCTEen_US
dc.title台灣保險業資產風險係數之探討zh_TW
dc.titleThe study on the asset risk factor of insurance industry in Taiwanen_US
dc.typethesisen
dc.relation.reference1. 行政院金融監督管理委員會保險局,人身保險業資本適足性報告,2009年\n2. 李進生、林允永、謝文良、蔣旨坪、陳達新、盧陽正,風險管理-風險值(VaR)理論與應用,新竹:清蔚科技,2001年。\n3. 陳嘉敏,衡量銀行市場風險-VaR與ETL模型的應用,政治大學金融研究所碩士論文,2007年。\n4. 黃芳文,歐盟「Solvency II」淺談,風險與保險雜誌,第10期,2006年,35-38。\n5. Basel Committee on Banking Supervision, 2006, International Convergence of Capital Measurement and Capital Standards.\n6. Bollerslev, T., 1986, Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, 31, 3, 307-327\n7. Engle, R., 2001, GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics, Journal of Economic Perspectives, 15, 4, 157-168.\n8. Engle, R. F., 1982, Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, 50, 4, 987-1008\n9. European Commission, 2008, QIS4 Technical Specifications.\n10. Jorion, P., 2007, Value at Risk – the new benchmark for managing financial risk, McGraw-Hill, third edition.\n11. National Association of Insurance Commissioners, 2008, 2008 Life Risk-Based Capital Report.\n12. Nelson, D. B., 1991, Conditional Heteroskedasticity in Asset Returns: A New Approach, Econometrica, 59, 2, 347-370.\n13. Zivot , E. and Jiahui Wang, 2006, Modelling Financial Time Series with S-PLUS, second edition.zh_TW
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