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Published online by Cambridge University Press:  25 November 2011


We propose a new test against a change in correlation at an unknown point in time based on cumulated sums of empirical correlations. The test does not require that inputs are independent and identically distributed under the null. We derive its limiting null distribution using a new functional delta method argument, provide a formula for its local power for particular types of structural changes, give some Monte Carlo evidence on its finite-sample behavior, and apply it to recent stock returns.

Research Article
Copyright © Cambridge University Press 2011

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Financial support by Deutsche Forschungsgemeinschaft (SFB 823, Statistik nichtlinearer dynamischer Prozesse) is gratefully acknowledged. We are grateful to the co-editor Benedikt M. Pötscher, three anonymous referees, Matthias Arnold, Roland Fried, Werner Ploberger, Christoph Rothe, Tatiana Vlasenco, Daniel Vogel, and Henryk Zähle for helpful criticism and comments.



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