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Dynamical Hierarchical Tree in Currency Markets


Juan Gabriel Brida


Free University of Bolzano

Wiston Adrián Risso


University of Siena - Department of Economics

David Matesanz Gómez


Universidad de Oviedo - Economfa Aplicada

February 1, 2007

Expert Systems with Applications, Vol. 36, pp. 7721-7728, 2009

Abstract:     
In this paper we introduce a new method to describe dynamical patterns of the real exchange rate movements time series and to analyze contagion in currency crisis. The method combines the tools of Symbolic Time Series Analysis with the nearest neighbor single linkage clustering algorithm. Data symbolization allows to obtain a metric distance between two different time series that is used to construct an ultrametric distance. By analyzing the data of various countries, we derive a hierarchical organization, constructing minimal-spanning and hierarchical trees. From these trees we detect different clusters of countries according to their proximity. We show that the derived clusters corresponds with the geographical location of the countries. The obtained classification of countries can be used to study the contagion phenomena in currency crisis.

Number of Pages in PDF File: 20

Keywords: Symbolic Time Series Analysis, real exchange rate, hierarchical tree

JEL Classification: C10, C14, F31

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Date posted: February 20, 2007 ; Last revised: June 19, 2011

Suggested Citation

Brida, Juan Gabriel, Risso, Wiston Adrián and Matesanz Gómez, David , Dynamical Hierarchical Tree in Currency Markets (February 1, 2007). Expert Systems with Applications, Vol. 36, pp. 7721-7728, 2009. Available at SSRN: http://ssrn.com/abstract=963773

Contact Information

Juan Gabriel Brida (Contact Author)
Free University of Bolzano ( email )
Via Sernesi 1
39100 Bolzano
Italy
Wiston Adrián Risso
University of Siena - Department of Economics ( email )
Piazza S. Francesco, 7
Siena, I-53100
Italy
00390577235058 (Phone)
David Matesanz Gómez
Universidad de Oviedo - Economfa Aplicada ( email )
United States
0034985104847 (Phone)
Feedback to SSRN (Beta)


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