英文标题：
《Verification of internal risk measure estimates》
---
作者：
Mark H.A. Davis
---
最新提交年份：
2015
---
英文摘要：
This paper concerns sequential computation of risk measures for financial data and asks how, given a risk measurement procedure, we can tell whether the answers it produces are `correct\'. We draw the distinction between `external\' and `internal\' risk measures and concentrate on the latter, where we observe data in real time, make predictions and observe outcomes. It is argued that evaluation of such procedures is best addressed from the point of view of probability forecasting or Dawid\'s theory of `prequential statistics\' [Dawid, JRSS(A)1984]. We introduce a concept of `calibration\' of a risk measure in a dynamic setting, following the precepts of Dawid\'s weak and strong prequential principles, and examine its application to quantile forecasting (VaR -- value at risk) and to mean estimation (applicable to CVaR -- expected shortfall). The relationship between these ideas and `elicitability\' [Gneiting, JASA 2011] is examined. We show in particular that VaR has special properties not shared by any other risk measure. Turning to CVaR we argue that its main deficiency is the unquantifiable tail dependence of estimators. In a final section we show that a simple data-driven feedback algorithm can produce VaR estimates on financial data that easily pass both the consistency test and a further newly-introduced statistical test for independence of a binary sequence.
---
中文摘要：
本文关注金融数据风险度量的顺序计算，并询问在给定风险度量程序的情况下，我们如何判断它产生的答案是否“正确”。我们区分了“外部”和“内部”风险度量，并专注于后者，即我们实时观察数据、做出预测和观察结果。有人认为，最好从概率预测或Dawid的“序贯统计”理论的角度来评估此类程序【Dawid，JRSS（A）1984】。我们在动态环境中引入了风险度量的“校准”概念，遵循Dawid的弱序和强序原则，并研究了其在分位数预测（VaR——风险值）和均值估计（适用于CVaR——预期短缺）中的应用。研究了这些想法与“可启发性”之间的关系[Gneiting，JASA 2011]。我们特别证明了VaR具有其他任何风险度量所不具有的特殊性质。关于CVaR，我们认为它的主要缺陷是估计量的不可量化尾部依赖性。在最后一节中，我们展示了一个简单的数据驱动反馈算法可以生成金融数据的VaR估计，该算法可以轻松通过一致性测试和新引入的二元序列独立性统计测试。
---
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
--

---
PDF下载：
-->