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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 郭震坤(Cheng-Kun Kuo) | |
dc.contributor.author | Kuan-I Chang | en |
dc.contributor.author | 章冠頤 | zh_TW |
dc.date.accessioned | 2021-06-13T01:32:47Z | - |
dc.date.available | 2010-07-19 | |
dc.date.copyright | 2007-07-19 | |
dc.date.issued | 2007 | |
dc.date.submitted | 2007-07-13 | |
dc.identifier.citation | 參考文獻
Alexander, G. J. and Baptista, A. M., 2004, “A Comparison of VaR and CVaR Constraints on Portfolio Selection with the Mean-Variance Model,” Management Science Vol. 50, No.90, pp1261-1273 Agarwal, R., Rao, R. and Hiraki, T., 1989, “Skewness and kurtosis in Japanese equity returns,” Journal of Financial Research, 12, pp253-260. Artzner, P., F. Delbaen and J. Eber, D. Heath, 1999, “Coherent measure of Risk,” Mathematical Finance Vol. 9, No.3, pp203-228. Basak, S. and A. Shapiro., 2001, “Value-at-risk-based risk management: Optimal policies and asset prices,” Review of Financial Studies 14 pp371–405. Bollerslev, T., 1986, “Generalized Autoregressive Conditional Heteroskedasticity,” Journal of Econometrics, vol.31, pp.307-327. Harris, Richard D. F. and Shen, Jian, 2006, “Hedging and Value at Risk” The Journal of Futures Markets, Vol. 26, No. 4, pp369–390 Hull, J. C. (2006) Options, Futures, and Other Derivatives, Sixth edition, Pearson. Pflug, 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. Scott, R., and Horvath, P., 1980, “On the direction of preference for moments of higher order than the variance,” Journal of Finance, 35, 915–919. Tang, G., and Choi, D., 1998, “Impact of diversification on the distribution of stock returns: International evidence,” Journal of Economics and Business, 22, pp119–127. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/30048 | - |
dc.description.abstract | 論文摘要
隨著金融商品的多樣化,使得資產報酬愈來愈難以估計,因此風險管理受到極大的重視,眾多的風險指標之中,風險值以損失比例或實際金額將風險量化,明確並具體表達出資產的風險。 近年相關研究逐漸增加,衡量風險值模型不斷更新,目前常用的包括變異數-共變異數法(Delta-Normal Method),蒙地卡羅模擬法(Monte-Carlo Simulation Method),歷史模擬法(Historical Simulation Method)。 雖然風險值的評估日益重要,然而許多避險基金的策略,還是使用傳統的最小化變異數避險策略,與是本文將風險值引入,作為避險策略的指標之ㄧ,因此本文將介紹風險值及資產波動性評估計算的方法,實證研究方面,以已開發國家匯率市場做為研究資料,利用匯率的投資,比較最小化變異數避險策略與最小化風險值避險策略下的避險比率,以及日報酬分配特性及績效,並以靜態避險作為樣本內資料,以動態避險作為樣本外資料加以比較。 | zh_TW |
dc.description.abstract | Abstract
With trend of various derivatives financial markets, it is more difficult then before to estimate the assets return. Value at Risk(VaR)is an emerging tool of risk management. In several risk indicators, VaR show the probability loss of asset by money or return rate to quantify risk. It makes risk simply and clearly to understand. With more and more research about VaR, there are several model for estimating VaR including Delta-Normal Method, Monte Carlo Simulation Method, Historical Simulation Method. Although the estimate of VaR become more important, there are still many hedge found managers use standard deviation to measure risk, and use the minimize-variance strategy to hedge. In this paper, the method of taking VaR into hedge strategy will be introduced, and the model which is used to estimate VaR and the volatility of assets will also be discussed. In the sample test, the data comes out from 11 developed countries’ monetary history. They are compared with method of the hedge ratio, performance and statistic of daily return by minimize-variance, minimize-CVaR and minimize-VaR hedgy strategy. The static hedge method for in the sample data and dynamic hedge method for out of sample data are two methods adopted to come out conclusions. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T01:32:47Z (GMT). No. of bitstreams: 1 ntu-96-R94724078-1.pdf: 513953 bytes, checksum: 7dcaa18f8b50f56ca027dea0d5f020d4 (MD5) Previous issue date: 2007 | en |
dc.description.tableofcontents | 目錄
第一章 緒論 1 1.1 研究動機及目的 1 1.2 風險定義 2 1.3 風險管理發展 3 第二章 風險值(Value at Risk)及條件風險值(Conditional Value at Risk) 6 2.1 何謂風險值 6 2.2 條件風險值(Conditional Value at Risk)定義及性質 8 第三章 計算風險值(VaR)方法 12 3.1 局部評價法(Local Valuation Method) 12 3.2 完全評價法(Full Valuation Method) 14 3.3 資產波動性估計 18 3.4風險值驗證 21 第四章 避險策略 23 4.1最小化變異數避險策略 23 4.2最小變異數避險策略分配 25 第五章 實證研究 28 5.1 資料選取 28 5.2 靜態避險 43 5.3 動態避險策略 66 第六章 結論與建議 81 參考文獻 85 | |
dc.language.iso | zh-TW | |
dc.title | 匯率避險策略應用風險值之探討 | zh_TW |
dc.title | Currency Hedge Strategy Using Value at Risk | en |
dc.type | Thesis | |
dc.date.schoolyear | 95-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 李顯峰,雷立芬 | |
dc.subject.keyword | 避險策略,風險值,條件風險值,歷史模擬法, | zh_TW |
dc.subject.keyword | Hedge Stratgy,Value at Risk,Condtional Value at Risk,History simulation method, | en |
dc.relation.page | 86 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2007-07-17 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 國際企業學研究所 | zh_TW |
顯示於系所單位: | 國際企業學系 |
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