博碩士論文 944208013 完整後設資料紀錄

DC 欄位 語言
DC.contributor財務金融學系zh_TW
DC.creator賴映竹zh_TW
DC.creatorYing-chu Laien_US
dc.date.accessioned2007-7-17T07:39:07Z
dc.date.available2007-7-17T07:39:07Z
dc.date.issued2007
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=944208013
dc.contributor.department財務金融學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract隨著時代的變遷與進步,越來越多的金融商品的創新,供公投資大眾或法人更多的選擇去做投資或避險,也因此使得財務槓桿上的風險越來越受到重視;不論新舊巴塞爾協定,均對金融業的投資風險、流動性風險、信用風險…等,多加規範,風險值的計算也日趨廣泛應用,蒙地卡羅模擬即為其中常用的衡量方法,而其中最重要的步驟就是分解相關係數矩陣;目前最常使用的是Cholesky分解法,然而,Cholesky分解法仍對被分解的相關係數矩陣多所限制,僅能分解正定矩陣,為了克服這個問題,我們可以採用Spectral分解法來替代Cholesky分解法,本篇論文即在探討Spectral分解法在風險值的應用,欲證明Spectral分解法能解決Cholesky分解法上的限制問題,應為計算風險值時的較佳選擇。zh_TW
dc.description.abstractSince more and more financial products have been invented, we have more ways to get more variety payoff and hedging. As a result, how to control financial risk becomes more and more important. Monte Carlo Simulation is the most widely used method to conduct value-at-risk. The most important part of computing value-at-risk of an asset portfolio is to derive the default correlation matrix to apply into Monte Carlo Simulation. Generally, we use the Cholesky decomposition to decompose the correlation matrix. However, there are some limitations to the Cholesky decomposition. The Cholesky decomposition cannot be used to decompose a non-positive correlation matrix. Under this circumstance, we may adopt the Spectral decomposition. This paper will show the efficiency of Spectral decomposition when facing the non-positive correlation matrix. Due to having fewer limitations, the Spectral decomposition could be more widely used rather than the Cholesky decomposition.en_US
DC.subject蒙地卡羅模擬zh_TW
DC.subject風險值zh_TW
DC.subjectSpectral分解法zh_TW
DC.subjectCholesky分解法zh_TW
DC.subjectSpectral decompositionen_US
DC.subjectMonte Carloen_US
DC.subjectVaRen_US
DC.subjectCholeskyen_US
DC.titleSpectral分解法在風險值之應用:台灣市場實証zh_TW
dc.language.isozh-TWzh-TW
DC.titleApplying Spectral Decomposition in Value-at-Risk: Empirical Evidence of Taiwan Stock Marketen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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