Universität zu Köln

Grothe, Oliver, Schnieders, Julius and Segers, Johan ORCID: 0000-0002-0444-689X (2014). Measuring association and dependence between random vectors. J. Multivar. Anal., 123. S. 96 - 111. SAN DIEGO: ELSEVIER INC. ISSN 0047-259X

Full text not available from this repository.

Abstract

Measures of association are suggested between two random vectors. The measures are copula-based and therefore invariant with respect to the univariate marginal distributions. The measures are able to capture positive as well as negative association. In case the random vectors are just random variables, the measures reduce to Kendall's tau or Spearman's rho. Nonparametric estimators, based on ranks, for the measures are derived. Their large-sample asymptotics are derived and their small-sample behavior is investigated by simulation. The measures are applied to characterize strength and direction of association of northern and southern European bond markets during the recent Euro crisis as well as association of stock markets with bond markets. (C) 2013 Elsevier Inc. All rights reserved.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Grothe, Oliver UNSPECIFIED UNSPECIFIED UNSPECIFIED Schnieders, Julius UNSPECIFIED UNSPECIFIED UNSPECIFIED Segers, Johan UNSPECIFIED orcid.org/0000-0002-0444-689X UNSPECIFIED
URN:	urn:nbn:de:hbz:38-452449
DOI:	10.1016/j.jmva.2013.08.019
Journal or Publication Title:	J. Multivar. Anal.
Volume:	123
Page Range:	S. 96 - 111
Date:	2014
Publisher:	ELSEVIER INC
Place of Publication:	SAN DIEGO
ISSN:	0047-259X
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language EMPIRICAL COPULA PROCESSES; MULTIVARIATE; TESTS; MODEL; TAU Multiple languages Statistics & Probability Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/45244