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Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/57553
DC FieldValueLanguage
dc.contributor.advisor陳威光<br>郭維裕zh_TW
dc.contributor.author藍婉如zh_TW
dc.creator藍婉如zh_TW
dc.date2011en_US
dc.date.accessioned2013-04-01T06:37:11Z-
dc.date.available2013-04-01T06:37:11Z-
dc.date.issued2013-04-01T06:37:11Z-
dc.identifierG0099352016en_US
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/57553-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description金融研究所zh_TW
dc.description99352016zh_TW
dc.description100zh_TW
dc.description.abstract金融市場中個別資產的風險感染效果越趨嚴重，使得傳統資產配置理論下的投資組合面臨極大的虧損。有鑑於此，若能在投資組合模型中納入考量此種擴散效果，將可更加分散風險以增進投資組合的效率性，並進一步降低投資組合面臨極端虧損的可能性。因此，要如何納入此一風險擴散效果，以在良好的風險控管下進行資產配置，將可能遭受的損失降至最低，是本論文主要探討的問題。\n本研究延伸Adrian, Brunnermeierz (2009) CoVaR的概念，納入考量系統性風險因素，透過CoVaR模型衡量系統性風險擴散時，造成個別標的資產報酬率變動的程度，並將Markowitz的效率前緣加以改良，建構更具效率性的Mean-CoVaR資產配置模型，以計算新的最適配置權重與最適投資組合。此外，本研究也就Mean-CoVaR資產配置模型與傳統Markowitz(1952)所提出的Mean-Variance模型進行探討與比較。\n綜合本研究之實證結果，Mean-Variance模型雖然能使投資組合報酬率的波動度最小，但在面臨極端系統性風險下，其績效表現卻不如Mena-CoVaR模型所建構出的投資組合；因此，在傳統的Mean-Variance模型下，若能以CoVaR取代Variance所建構出新的Mean-CoVaR投資組合模型，納入大盤風險可能的擴散效果下，將可有效降低投資組合在大盤崩跌時的虧損程度，以維持較佳的投資績效。zh_TW
dc.description.tableofcontents表目錄 i\n圖目錄 ii\n第一章 緒論 1\n第一節 研究背景 1\n第二節 研究動機與目的 2\n第二章 文獻探討 4\n第一節 風險值之相關文獻 4\n第二節 資產配置之相關文獻 8\n第三章 研究方法 12\n第一節 Mean-Variance模型 12\n第二節 Mean-CoVaR模型 16\n第四章 實證研究 23\n第一節 資料描述 23\n第二節 實證結果分析 27\n第三節 樣本外測試 38\n第五章 結論 41\n參考文獻 42zh_TW
dc.language.isoen_US-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0099352016en_US
dc.subjectCoVaRzh_TW
dc.subject資產配置zh_TW
dc.titleCoVaR在資產配置下之應用zh_TW
dc.titleAn Application of CoVaR on Asset Allocationen_US
dc.typethesisen
dc.relation.referenceAdrian, Tobias and Markus K. Brunnermeier (2009), “CoVaR,” Federal Reserve Bank of New York Staff Report 348.\nAlexander, G. J. and A. M. Baptista (2004), “A Comparison of VaR and CVaR Constraints on Portfolio Selection with the Mean-Variance Model,” Management Science Vol. 50, No.90, pp1261-1273.\nArtzner, P., F. Delbaen and J. Eber, D. Heath (1999), “Coherent measure of Risk,” Mathematical Finance, Vol.9, No.3, pp203-228.\nBrook, A., D. Kendrick and A. Meeraus (1988), “GAMS-A User’s Guide,” The Scientific Press, Redwood City, CA.\nCampbell, R., R.Huisman and K. Koedijk(2001), “Optimal portfolio selection in a value at risk framework,” Journal of Banking and Finance 25, 1789–1804.\nChernozhukov,V. and L. Umantsev (2001), “Conditional Value-at-Rissk：Aspects of Modeling and Estimation,” Empirical Economics, Vol. 26, Issue 1, pp. 271-292.\nChopra, V.K. and W.T. Ziemba (2001),“The Effect of Errors in Means,Variances,and Covariances on Optimal Portfolio,” Choice Journal of Portfolio Management,19,6-11.\nDuarte, Jr., A. M. and S. D. R. Alcantara (1999), “Mean-Value-at-Risk Optimal Portfolios with Derivatives,” Derivatives Quarterly, Vol. 6, pp. 56-64.\nDuffie, D. and J. Pan (1997), “An overview of value at risk,” Journal of Derivatives, Spring 1997, Vol. 4, No.3, pp. 7-49.\nEngle, R.F. and S. Manganelli (2004), “CAViaR：Conditional Value at Risk by Quantile Regression,” Journal of Business & Economic Statistics, Oct 2004, Vol.22, Issue 4, pp. 367-381.\n\nHendricks, D. (1996), “Evaluation of Value-at-Risk Models Using Historical Data,” Federal Reserve Bank of New York Economic Policy Review, Vol. 2, pp. 39-69.\nJorion, P. (1996), “Value at Risk: The New Benchmark for Controlling Derivatives Risk,” McGraw-Hill.\nJ. P. Morgan/Reuters (1996), RiskMetrics TM -Technical Document. Fourth Edition.\nKataoka, S., (1963), “A stochastic programming model,” Econometrica, 181-196.\nKoenker, R., and G. W. Bassett (1978), “Regression Quantiles,” Econometrica, Jan19878, Vol. 46, Issue 1, pp.33-50. \nLongin, F.M. (1996),“The Asymptotic Distribution of Extreme Stock Market Returns,” Journal of Business, vol.69.\nMarkowitz, H. (1952), “Portfolio selection,” Journal of Finance, Vol. 7, pp.77-91.\nMausser, H. and D. Rosen (1998), “Beyond VaR: From Measuring Risk to Managing Risk,” ALGO Research Quarterly, Vol. 1, pp. 5-20.\nPflug, G. Ch. (2000), “Some Remarks on the Value-at-Risk and the Conditional Value-at-Risk,” In. Uryasev S. (Ed.) Probabilistic Constrained Optimization: Methodology and Applications, Kluwer Academic Publishers.\nRockafellar, R. T. and S. Uryasev (2000), “Optimization of Conditional Value-at-Risk,” Journal of Risk, Vol. 2, pp. 21-41.\nRoy, A.D. (1952), “Safety First and the Holding of Assets,”Econometric, 431-449.\nUryasev, S. (2000), “Conditional Value-at-Risk: Optimization Algorithms and Applications,” Financial Engineering News.\nWilliam T. Ziemba (Winter 1993), “The Effect of Errors in Means, Variances, and Covariances on Optimal Portfolio Choice,” J. Portfolio Management, , 6-11.\n李吉元，民國九十二年六月，「風險值限制下最適資產配置」，成功大學財務金融研究所碩士班論文。\n洪幸資，民國九十三年六月，「控制風險值下的最適投資組合」，政治大學金融研究所碩士班論文。\n許倫維，民國九十五年六月，「探討在Mean-Variance 模型下，VaR或CVaR的條件限制對投資組合選擇的影響」，清華大學科技管理研究所碩士班論文。\n黃惠萱，民國九十五年六月，「最適資產配置模型績效之研究- M-V與M-CVaR模型之比較」，銘傳大學財務金融學系研究所碩士班論文。\n陳怡君，民國一零零年七月，「CoVaR風險值對金融機構風險值管理之重要性-以臺灣控股公司為例」，政治大學金融研究所碩士班論文。\n張吟綺，民國九十四年六月，「考慮景氣循環與風險值下的最適資產配置之實證研究」，交通大學經營管理研究所碩士班論文。\n蔡依婷，民國九十九年六月，「追蹤指數與控管CVaR之投資組合規畫模型」，政治大學應用數學系研究所碩士班論文。\n鄭互維，民國九十六年六月，「應用Mean-VaR模型於最適化油品煉製組合」，交通大學經營管理研究所碩士班論文。zh_TW
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