Symbolic hierarchical analysis in currency markets: An application to contagion in currency crises

In this paper we introduce a new method to describe dynamical patterns of the real exchange rate co-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 us obtaining 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 this methodology permits us to construct a structural and dynamic topology that is useful to study interdependence and contagion effects among financial time series.

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