A simple graphical method to explore tail-dependence in stock-return pairs

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CoFE Discussion Paper ; No. 04/03

Classification and Topics

• Classification: Wirtschaft
• Subject: Association ; bivariate distribution ; chi-plot ; copula ; correlation ; local dependence ; tail-dependence ; Kapitalertrag ; Value at Risk ; Statistische Methode ; chi-plot

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Abberger, Klaus
• Event: Veröffentlichung
• (who): University of Konstanz, Center of Finance and Econometrics (CoFE)
• (where): Konstanz
• (when): 2004

Further information

• Handle: http://hdl.handle.net/10419/23565
• URN: urn:nbn:de:bsz:352-opus-11707
• Last update: 10.03.2025, 11:45 AM CET