Risk Estimation With Composite Quantile Regression
Econometrics and Statistics(2022)
摘要
New methods for the estimation of the popular risk measures expected shortfall (ES) and Value-at-Risk (VaR) are introduced. These are based on a novel variant of composite quantile regression (CQR), which allows for the simultaneous estimation of quantiles at several levels at once. An extensive simulation study is performed, along with a data analysis based on two major US market indices and two financial sector stocks. The results suggest that the method has a good finite sample performance. This is the first methodology to use CQR for risk estimation.
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关键词
Composite Quantile Regression,Expected Shortfall,Single-Index,Value-at-Risk
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