
arXiv: 1206.5070
A CUSUM type test for constant correlation that goes beyond a previously suggested correlation constancy test by considering Spearman's rho in arbitrary dimensions is proposed. Since the new test does not require the existence of any moments, the applicability on usually heavy-tailed financial data is greatly improved. The asymptotic null distribution is calculated using an invariance principle for the sequential empirical copula process. The limit distribution is free of nuisance parameters and critical values can be obtained without bootstrap techniques. A local power result and an analysis of the behavior of the test in small samples is provided.
Applications of statistics to actuarial sciences and financial mathematics, FOS: Computer and information sciences, Measures of association (correlation, canonical correlation, etc.), Asymptotic distribution theory in statistics, Mathematics - Statistics Theory, robustness, Statistics Theory (math.ST), structural break, Methodology (stat.ME), Time series, auto-correlation, regression, etc. in statistics (GARCH), FOS: Mathematics, copula, mixing, Computational methods for problems pertaining to statistics, multivariate sequential rank order process, Statistics - Methodology, 62G10, 62G35, 91B84
Applications of statistics to actuarial sciences and financial mathematics, FOS: Computer and information sciences, Measures of association (correlation, canonical correlation, etc.), Asymptotic distribution theory in statistics, Mathematics - Statistics Theory, robustness, Statistics Theory (math.ST), structural break, Methodology (stat.ME), Time series, auto-correlation, regression, etc. in statistics (GARCH), FOS: Mathematics, copula, mixing, Computational methods for problems pertaining to statistics, multivariate sequential rank order process, Statistics - Methodology, 62G10, 62G35, 91B84
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