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On loss functions and ranking forecasting performances of multivariate volatility models

机译:多元波动率模型的损失函数和排序预测性能

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摘要

The ranking of multivariate volatility models is inherently problematic because when the unobservable volatility is substituted by a proxy, the ordering implied by a loss function may be biased with respect to the intended one. We point out that the size of the distortion is strictly tied to the level of the accuracy of the volatility proxy. We propose a generalized necessary and sufficient functional form for a class of non-metric distance measures of the Bregman type which ensure consistency of the ordering when the target is observed with noise. An application to three foreign exchange rates is provided
机译:多元波动率模型的排名存在固有的问题,因为当不可观测的波动率由代理代替时,损失函数所隐含的排序可能会相对于预期波动。我们指出,失真的大小严格取决于波动率代理的准确性水平。我们为布雷格曼(Bregman)类型的一类非度量距离度量提出了一种通用的必要和充分的函数形式,该度量形式可确保在用噪声观察目标时确保顺序的一致性。提供了三种汇率的申请

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