论文标题
在重尾损失的情况下，有条件尾巴期望的估计器得到了改善
Improved Estimator of the Conditional Tail Expectation in the case of heavy-tailed losses
论文作者
论文摘要
在本文中，我们调查了极值方法论，以提出改进条件尾尾期望（$ cte $）的估计器，以实现具有有限平均值但无限差异的损失分布。目前的工作基于降低了重量化分布的偏置估算值的新估计量。在一项模拟研究中，建立并检查了所提出的估计量的渐近正态性。此外，我们将估计器与已知的旧估计器进行比较，从偏差和平方误差进行比较。
In this paper, we investigate the extreme-value methodology, to propose an improved estimator of the conditional tail expectation ($CTE$) for a loss distribution with a finite mean but infinite variance. The present work introduces a new estimator of the $CTE$ based on the bias-reduced estimators of high quantile for heavy-tailed distributions. The asymptotic normality of the proposed estimator is established and checked, in a simulation study. Moreover, we compare, in terms of bias and mean squared error, our estimator with the known old estimator.
