In this paper, we introduce quantile coherency to measure general dependence structures emerging in the joint distribution in the frequency domain and argue that this type of dependence is natural for economic time series but remains invisible when only the traditional analysis is employed. We define estimators which capture the general dependence structure, provide a detailed analysis of their asymptotic properties and discuss how to conduct inference for a general class of possibly nonlinear processes. In an empirical illustration we examine the dependence of bivariate stock market returns and shed new light on measurement of tail risk in financial markets. We also provide a modelling exercise to illustrate how applied researchers can benefit from using quantile coherency when assessing time series models.

中文翻译：

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分位数连贯性：循环经济变量之间依存关系的一般度量

在本文中，我们引入分位数相干性来测量频域联合分布中出现的一般依存结构，并认为这种依存关系对于经济时间序列是自然的，但仅采用传统分析时仍不可见。我们定义了估计器，这些估计器捕获了一般的依赖结构，提供了它们的渐近性质的详细分析，并讨论了如何对可能的非线性过程的一般类进行推理。在经验例证中，我们研究了二元股票市场收益的依赖性，并为衡量金融市场尾部风险提供了新的思路。我们还提供了一个建模练习，以说明在评估时间序列模型时应用研究人员如何从分位数相干性中受益。