Statistical Inference for Expectile-based Risk Measures

被引:35
|
作者
Kraetschmer, Volker [1 ]
Zaehle, Henryk [2 ]
机构
[1] Univ Duisburg Essen, Fac Math, Campus Essen,Thea Leymann Str 9, D-45127 Essen, Germany
[2] Saarland Univ, Dept Math, Campus E24, D-66123 Saarbrucken, Germany
关键词
1-weak continuity; asymptotic normality; bootstrap consistency; expectile-based risk measure; functional delta-method; qualitative robustness; quasi-Hadamard differentiability; statistical estimation; strong consistency; weak dependence; FUNCTIONAL DELTA-METHOD; FRECHET DIFFERENTIABILITY; QUALITATIVE ROBUSTNESS; EMPIRICAL PROCESSES; BOOTSTRAP; ESTIMATORS; STATIONARITY;
D O I
10.1111/sjos.12259
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Expectiles were introduced by Newey and Powell in 1987 in the context of linear regression models. Recently, Bellini et al.revealed that expectiles can also be seen as reasonable law-invariant risk measures. In this article, we show that the corresponding statistical functionals are continuous w.r.t.the 1-weak topology and suitably functionally differentiable. By means of these regularity results, we can derive several properties such as consistency, asymptotic normality, bootstrap consistency and qualitative robustness of the corresponding estimators in nonparametric and parametric statistical models.
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页码:425 / 454
页数:30
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