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Abstract Details
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Activity Number:
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443
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Type:
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Invited
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Date/Time:
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Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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| Abstract - #300058 |
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Title:
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Expectile Regression with Varying Coefficient
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Author(s):
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Yong Zhou*+
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Companies:
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Chinese Academy of Sciences
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Address:
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Academy of Mathematics and Systems Science, Beijing, 100190, P.R. China
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Keywords:
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Expectile regression ;
Asymmetric least square ;
Varying-coefficient model ;
Local linear regression
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Abstract:
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In this paper, we consider a regression expectile with varying-coefficient function used to characterize the relationship between a response variable and explanatory variable when the behavior of "non-average" (or extreme behavior) individuals is of interest. Regression expectile is an alternative location measure of conditional distribution defined by an asymmetric least squares criterion function to regression quantile. The expectile estimators have properties which are analogous to regression quantile estimators, but are much simpler to compute by iteratively re-weighted asymmetric least squares. In view of the appealing algorithm of the expectile and the link with VaR (value at risk) and ES (expected shortfall), which are popular measures of financial risk, expectile can also to be used to estimate VaR and ES in an indirect way.
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Authors who are presenting talks have a * after their name.
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