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Using Exponentially Weighted Quantile Regression to Estimate Value at Risk and Expected Shortfall

Abstract:

We propose exponentially weighted quantile regression (EWQR) for estimating time-varying quantiles. The EWQR cost function can be used as the basis for estimating the time-varying expected shortfall associated with the EWQR quantile forecast. We express EWQR in a kernel estimation framework, and then modify it by adapting a previously proposed double kernel estimator in order to provide greater accuracy for tail quantiles that are changing relatively quickly over time. We introduce double ker...

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James Taylor More by this author
Publication date:
2008
URN:
uuid:38955808-49c6-49e4-ba79-8b155b45112c
Local pid:
oai:eureka.sbs.ox.ac.uk:1711

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