Dehling, Herold, Vogel, Daniel, Wendler, Martin and Wied, Dominik (2017). TESTING FOR CHANGES IN KENDALL'S TAU. Economet. Theory, 33 (6). S. 1352 - 1387. NEW YORK: CAMBRIDGE UNIV PRESS. ISSN 1469-4360
Full text not available from this repository.Abstract
For a bivariate time series ((X-i, Y-i))(i=1, ... , n), we want to detect whether the correlation between Xi and Yi stays constant for all i = 1, ... , n. We propose a nonparametric change-point test statistic based on Kendall's tau. The asymptotic distribution under the null hypothesis of no change follows from a new U-statistic invariance principle for dependent processes. Assuming a single change-point, we show that the location of the change-point is consistently estimated. Kendall's tau possesses a high efficiency at the normal distribution, as compared to the normal maximum likelihood estimator, Pearson's moment correlation. Contrary to Pearson's correlation coefficient, it shows no loss in efficiency at heavy-tailed distributions, and is therefore particularly suited for financial data, where heavy tails are common. We assume the data ((X-i, Y-i))(i=1, ... , n) to be stationary and P-near epoch dependent on an absolutely regular process. The P-near epoch dependence condition constitutes a generalization of the usually considered L-p-near epoch dependence allowing for arbitrarily heavy-tailed data. We investigate the test numerically, compare it to previous proposals, and illustrate its application with two real-life data examples.
Item Type: | Journal Article | ||||||||||||||||||||
Creators: |
|
||||||||||||||||||||
URN: | urn:nbn:de:hbz:38-210670 | ||||||||||||||||||||
DOI: | 10.1017/S026646661600044X | ||||||||||||||||||||
Journal or Publication Title: | Economet. Theory | ||||||||||||||||||||
Volume: | 33 | ||||||||||||||||||||
Number: | 6 | ||||||||||||||||||||
Page Range: | S. 1352 - 1387 | ||||||||||||||||||||
Date: | 2017 | ||||||||||||||||||||
Publisher: | CAMBRIDGE UNIV PRESS | ||||||||||||||||||||
Place of Publication: | NEW YORK | ||||||||||||||||||||
ISSN: | 1469-4360 | ||||||||||||||||||||
Language: | English | ||||||||||||||||||||
Faculty: | Unspecified | ||||||||||||||||||||
Divisions: | Unspecified | ||||||||||||||||||||
Subjects: | no entry | ||||||||||||||||||||
Uncontrolled Keywords: |
|
||||||||||||||||||||
Refereed: | Yes | ||||||||||||||||||||
URI: | http://kups.ub.uni-koeln.de/id/eprint/21067 |
Downloads
Downloads per month over past year
Altmetric
Export
Actions (login required)
View Item |