WP 2015-09 Empirical Likelihood Inference for Haezendonck-Goovaerts Risk Measure

AUTHORS: Liang Peng, Xing Wang and Yanting Zheng

Abstract. Recently Haezendonck-Goovaerts risk measure is receiving much attention in actuarial science with applications in the study of optimal portfolio and optimal reinsurance policy. Nonparametric estimation is proposed by Ahn and Shyamalkumar (2014), where the derived asymptotic limit can be employed to construct an interval for the Haezendonck-Goovaerts risk measure. In this paper, we propose an alternative empirical likelihood inference for this risk measure. A simulation study shows the good performance of the proposed method.