英文标题：
《Backtesting Lambda Value at Risk》
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作者：
Jacopo Corbetta and Ilaria Peri
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最新提交年份：
2017
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英文摘要：
  A new risk measure, the lambda value at risk (Lambda VaR), has been recently proposed from a theoretical point of view as a generalization of the value at risk (VaR). The Lambda VaR appears attractive for its potential ability to solve several problems of the VaR. In this paper we propose three nonparametric backtesting methodologies for the Lambda VaR which exploit different features. Two of these tests directly assess the correctness of the level of coverage predicted by the model. One of these tests is bilateral and provides an asymptotic result. A third test assess the accuracy of the Lambda VaR that depends on the choice of the P&L distribution. However, this test requires the storage of more information. Finally, we perform a backtesting exercise and we compare our results with the ones from Hitaj and Peri (2015)
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中文摘要：
最近，从理论角度提出了一种新的风险度量，即lambda风险值（lambda VaR），作为风险值（VaR）的推广。Lambda-VaR因其潜在的解决VaR若干问题的能力而具有吸引力。在本文中，我们针对Lambda-VaR提出了三种利用不同特征的非参数回溯测试方法。其中两项测试直接评估模型预测的覆盖水平的正确性。其中一个测试是双边的，提供了一个渐进的结果。第三项测试评估了Lambda VaR的准确性，该准确性取决于损益分布的选择。然而，该测试需要存储更多信息。最后，我们进行了一次回溯测试，并将结果与Hitaj和Peri（2015）的结果进行了比较
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Risk Management        风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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