Testing large-dimensional correlation

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. --testing correlation,n-p-asymptotics,portfolio credit risk