Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities studied by Jones and Zitikis (2003). A simulation study shows the advantages of the new method over the normal approximation method and the naive bootstrap method.
Bibliographical noteFunding Information:
We thank an associate editor and the two reviewers for their helpful comments. Peng’s research was supported by NSA grant H98230-10-1-0170 and NSF grant DMS-1005336 , Qi’s research was supported by NSA grant H98230-10-1-0161 and NSF grant DMS-1005345 , and Yang’s research was partly supported by the Key National Basic Research Program (973 Program) of China ( 2007CB814905 ) and the Key Program of National Natural Science Foundation of China (Grant No. 11131002 ).
- Confidence interval
- Jackknife empirical likelihood
- Risk measure