Please use this identifier to cite or link to this item:
Abberger, Klaus
Year of Publication: 
Series/Report no.: 
Discussion paper series / Universität Konstanz, Center of Finance and Econometrics (CoFE) 04/03
For a bivariate data set the dependence structure can not only be measured globally, for example with the Bravais-Pearson correlation coefficient, but the dependence structure can also be analyzed locally. In this article the exploration of dependencies in the tails of the bivariate distribution is discussed. For this a graphical method which is called chi-plot and which was introduced by Fisher and Switzer (1985, 2001) is used. Examples with simulated data sets illustrate that the chi-plot is suitable for the exploration of dependencies. This graphical method is then used to examine stock-return pairs. The kind of tail-dependence between returns has consequences, for example, for the calculation of the Value at Risk and should be modelled carefully. The application of the chi-plot to various daily stock-return pairs shows that different dependence structures can be found. This graph can therefore be an interesting aid for the modelling of returns.
bivariate distribution
local dependence
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
1.09 MB

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.