Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/23565
Authors: 
Abberger, Klaus
Year of Publication: 
2004
Series/Report no.: 
Discussion paper series / Universität Konstanz, Center of Finance and Econometrics (CoFE) 04/03
Abstract: 
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.
Subjects: 
Association
bivariate distribution
chi-plot
copula
correlation
local dependence
tail-dependence
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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