An Empirical Analysis of Risk Measures using Quantile Regression
2016
Hochschulschrift
Zugriff:
104
This paper presents a comprehensive empirical analysis of a set of left-tail measures (LTMs): the mean and standard deviation of a loss larger than the VaR (MLL and SDLL) and the VaR. The data we use for estimating the LTMs are the daily return of the S&P500 Index from January 1963 to December 2015 and T50 Index from July 2003 to December 2015. We estimate the value-at-risk using the quantile regression model and the other two traditional method. We want to compare the value-at-risk from the three models that were analyzed from two angles: risk prediction and investment. In risk prediction, the empirical results indicate the quantile regression’s LTMs overvalued. The VaRiance-CoVaRiance Method is undervalued because of the back test more than 12.5. In investment, the Sharpe ratio daily investment using LTMs is higher than the traditional method.
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An Empirical Analysis of Risk Measures using Quantile Regression
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Autor/in / Beteiligte Person: | LIU,WEI-CHIN ; 劉偉欽 |
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Veröffentlichung: | 2016 |
Medientyp: | Hochschulschrift |
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