Testing large-dimensional correlation

Matthias Arnold, R. Weißbach
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Abstract

This paper introduces a test for zero correlation in situations where the correlation matrix is large compared to the sample size. The test statistic is the sum of the squared correlation coefficients in the sample. We derive its limiting null distribution as the number of variables as well as the sample size converge to infinity. A Monte Carlo simulation finds both size and power for finite samples to be suitable. We apply the test to the vector of default rates, a risk factor in portfolio credit risk, in different sectors of the German economy.
检验大维度相关性
本文介绍了在相关矩阵比样本量大的情况下的零相关检验。检验统计量是样本中相关系数的平方和。当变量数和样本量趋近于无穷时,我们推导出了它的极限零分布。蒙特卡罗模拟发现有限样本的大小和功率都是合适的。我们将测试应用于德国经济不同部门的违约率向量,这是投资组合信用风险的一个风险因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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