Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall
Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall
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DOI：
10.1111/j.0960-1627.2004.00184.x
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发表时间：
2004-01
影响因子：
1.6
通讯作者：
O. Scaillet
中科院分区：
文献类型：
--
作者：
O. Scaillet
我们考虑一种非参数方法来估计预期亏损，即在损失大于给定分位数的情况下，金融资产组合的预期损失。在满足强混合条件的平稳过程的背景下，我们得到了关于投资组合配置的期望缺口及其一阶导数的核估计的渐近性质。一个实证说明了一个股票投资组合。另一个实证例子涉及火灾保险损失的数据。
We consider a nonparametric method to estimate the expected shortfall—that is, the expected loss on a portfolio of financial assets knowing that the loss is larger than a given quantile. We derive the asymptotic properties of the kernel estimators of the expected shortfall and its first‐order derivative with respect to portfolio allocation in the context of a stationary process satisfying strong mixing conditions. An empirical illustration is given for a portfolio of stocks. Another empirical illustration deals with data on fire insurance losses.