Hierarchical structure of the German stock market

Authors:
J. Gabriel Brida;W. Adrián Risso
Affiliations:
School of Economics and Management, Free University of Bolzano, Italy;Department of Economics, University of Siena, Italy
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

Enormous quantity of information affects stock returns every day producing their almost random behavior. Nonetheless, some information can be recovered by using symbolic methods and constructing minimal spanning trees (MST) and hierarchical trees (HT). The introduced method is applied to the main German companies that appear in the DAX30 index. A structural topology is constructed for this stock market and compared with the method introduced by Mantegna. Conducting bootstrap simulations, we detect a structural break in the evolution of the global distance.