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A multivariate test against spurious long memory

机译:对杂散长记忆的多变量测试

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This paper provides a multivariate score-type test against spurious long memory. We prove the consistency of the test against the alternatives of random level shifts and smooth trends. The test statistic is based on the weighted sum of the partial derivatives of the multivariate local Whittle likelihood function. To apply the test to fractionally cointegrated series, the test statistic is calculated for the linearly transformed system after estimating the cointegrating matrix. We derive the limiting distribution and show consistency of this procedure. The test is applied to log-absolute returns and log-realized volatilities of the S&P 500, DAX, FTSE, and NIKKEI. (C) 2017 Elsevier B.V. All rights reserved.
机译:本文提供了一个针对虚假长记忆的多变量评分类型测试。我们证明了测试与随机水平移动和平滑趋势的一致性。检验统计量基于多元局部Whittle似然函数偏导数的加权和。为了对分数协整序列进行检验,在估计协整矩阵后,计算线性变换系统的检验统计量。我们推导了极限分布,并证明了这个过程的一致性。该测试适用于标准普尔500指数、DAX指数、FTSE指数和日经指数的对数绝对收益率和对数实际波动率。(C) 2017爱思唯尔B.V.版权所有。

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