Nonparametric Inference for VaR, CTE, and Expectile with High-Order Precision-Reference-Cited by-同舟云学术

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Nonparametric Inference for VaR, CTE, and Expectile with High-Order Precision

Published:2019-05-09 Issue:3 Volume:23 Page:364-385
ISSN:1092-0277
Container-title:North American Actuarial Journal
language:en
Short-container-title:North American Actuarial Journal

Author:

Shen Zhiyi¹,Liu Yukun²,Weng Chengguo²

Affiliation:

1. Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada

2. Key Laboratory of Advanced Theory and Application in Statistics and Data Science — MOE School of Statistics, East China Normal University, Shanghai, China

Funder

National Natural Science Foundation of China

Chinese Ministry of Education

Natural Sciences and Engineering Research Council of Canada

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10920277.2019.1566075

Reference35 articles.

1. Asymptotic theory for the empirical Haezendonck–Goovaerts risk measure

2. Modeling loss data using composite models

3. Empirical likelihood for value-at-risk and expected shortfall

4. Generalized quantiles as risk measures

5. Adjusted Empirical Likelihood and its Properties

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Estimating Copula-Based Extension of Tail Value-at-Risk and Its Application in Insurance Claim;Risks;2022-05-30

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