Universität zu Köln

Blumentritt, Thomas and Schmid, Friedrich (2014). Nonparametric estimation of copula-based measures of multivariate association from contingency tables. J. Stat. Comput. Simul., 84 (4). S. 781 - 798. ABINGDON: TAYLOR & FRANCIS LTD. ISSN 1563-5163

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Abstract

Nonparametric estimation of copula-based measures of multivariate association in a continuous random vector X = (X-1,...,X-d) is usually based on complete continuous data. In many practical applications, however, these types of data are not readily available; instead aggregated ordinal observations are given, for example, ordinal ratings based on a latent continuous scale. This article introduces a purely nonparametric and data-driven estimator of the unknown copula density and the corresponding copula based on multivariate contingency tables. Estimators for multivariate Spearman's rho and Kendall's tau are based thereon. The properties of these estimators in samples of medium and large size are evaluated in a simulation study. An increasing bias can be observed along with an increasing degree of association between the components. As it is to be expected, the bias is severely influenced by the amount of information available. Additionally, the influence of sample size is only marginal. We further give an empirical illustration based on daily returns of five German stocks.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Blumentritt, Thomas UNSPECIFIED UNSPECIFIED UNSPECIFIED Schmid, Friedrich UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-450249
DOI:	10.1080/00949655.2012.727186
Journal or Publication Title:	J. Stat. Comput. Simul.
Volume:	84
Number:	4
Page Range:	S. 781 - 798
Date:	2014
Publisher:	TAYLOR & FRANCIS LTD
Place of Publication:	ABINGDON
ISSN:	1563-5163
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language CONCORDANCE MEASURES Multiple languages Computer Science, Interdisciplinary Applications; Statistics & Probability Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/45024