Clustering the changing nature of currency crises in emerging markets: an exploration with self-organising maps Online publication date: Tue, 07-Jun-2011
by Peter Sarlin
International Journal of Computational Economics and Econometrics (IJCEE), Vol. 2, No. 1, 2011
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Economics and Econometrics (IJCEE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook