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Scaling models for the severity and frequency of external operational loss data

机译:外部操作损失数据的严重性和频率的缩放模型

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According to Basel II criteria, the use of external data is indispensable to the implementation of an advanced method for calculating operational risk capital. This article investigates how the severity and frequencies of external losses are scaled for integration with internal data. We set up an initial model designed to explain the loss severity by taking into account potential selection bias in the external data. Estimation results show that many variables have significant power in explaining the loss amount. We use them to develop a normalization formula. We develop a zero-inflated count-data model to scale the loss frequency. We compute an operational VaR and we conduct out-of-sample backtesting.
机译:根据巴塞尔协议II的标准,外部数据的使用对于实施用于计算运营风险资本的高级方法是必不可少的。本文研究了如何调整外部损失的严重性和频率以与内部数据集成。我们建立了一个初始模型,旨在通过考虑外部数据中的潜在选择偏差来解释损失的严重性。估计结果表明,许多变量在解释损失金额方面具有重要作用。我们使用它们来开发归一化公式。我们开发了零膨胀计数数据模型来衡量损失频率。我们计算可操作的VaR,然后进行样本外回测。

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