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Extreme canonical correlations and high-dimensional cointegration analysis

机译:极端的规范相关和高维协整分析

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摘要

We prove that the extreme squared sample canonical correlations between a random walk and its own innovations almost surely converge to the upper and lower boundaries of the support of the Wachter distribution when the sample size and the dimensionality go to infinity proportionally. This result is used to derive previously unknown analytic expressions for the Bartlett-type correction coefficients for Johansens trace and maximum eigenvalue tests in a high-dimensional VAR(1). An analysis of cointegration among a large number of log exchange rates illustrates the usefulness of our theoretical results. (C) 2019 Elsevier B.V. All rights reserved.
机译:我们证明,当样品尺寸和维数转到无限程度,随机步行和自身创新之间的极端平方样的样本相关性几乎肯定会收敛到Wachter分布的支持的上下边界,并按比例地转到无限程度。 该结果用于从高维var(1)中的约翰斯轨迹和最大特征值测试的Bartlett型校正系数衍生先前未知的分析表达式。 大量日志汇率之间的协整分析说明了我们理论结果的有用性。 (c)2019年Elsevier B.V.保留所有权利。

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