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標題: 分量迴歸在風險值估計與回測檢定的應用
Applications of Quantile Regressions on the Estimations and Backfit Tests for VaR
作者: 邱建豪
Chiu, Chien-Hao
關鍵字: 風險值;Value at Risk;分量迴歸;穩健性;回溯測試;Quantile Regression;robust;Backfit test
出版社: 財務金融系所
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Value at Risk(VaR) is a widely used measure of the risk of loss on a specific protfolio of financial assets. The Basel Capital
Accord beginning in 1999, gave further push to the use of VaR. Now, there are many kinds of methods to caculate the VaR, such as
parametric methods, semi-parametric methods and non-parametric methods. This paper introduces some useful methods to
calculate VaR.
In literature, the semi-parametric method - Quantile regression is a robust method. In this thesis, we compare
five different Value-at-Risk methods, which contain two quantile regression methods, through an empirical exercise. In the empirical exercis, we estimate VaR for returns of TSEC weighted index and returns of SHASHR index. Then we will use Backfit test to check accuracy of these VaR models. The empirical results show that the Quantile regression methods are better to estiamte VaR.
其他識別: U0005-0702201315571300
Appears in Collections:財務金融學系所

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