Clustering the changing nature of currency crises in emerging markets: an exploration with self-organising maps
Peter Sarlin ()
International Journal of Computational Economics and Econometrics, 2011, vol. 2, issue 1, 24-46
Abstract:
Currency crises are a recurring phenomenon. To increase the understanding of their changing nature, this paper analyses the evolution of currency crises and assesses them in the generation framework of theoretical models. The self-organising map (SOM), a neural network-based clustering and visualisation tool, is used for clustering pre-crisis periods for emerging market economies. The clustering results are used for finding differences in crises between decades, whereafter the decade clusters are compared with the theoretical framework. We conclude that for emerging market economies, this paper shows that the crises in the 1970s and 1980s are of a different nature and that the crises in the late 1990s are, in comparison with the preceding decades, determined by weaker warning signals. This illustrates that predicting the Asian crises with a priori models was a difficult task. Further, the empirical results indicate that the generation framework is not as clear-cut as theory points out.
Keywords: currency crisis; early warning; financial instability; SOMs; self-organising maps; clustering; changing nature; emerging markets; neural networks; visualisation; emerging economies. (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.inderscience.com/link.php?id=40575 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijcome:v:2:y:2011:i:1:p:24-46
Access Statistics for this article
More articles in International Journal of Computational Economics and Econometrics from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().