Discrete Dynamics in Nature and Society
Volume 5 (2000), Issue 2, Pages 121-137
doi:10.1155/S1026022600000479
In search of a warning strategy against exchange-rate attacks: Forecasting tactics using artificial neural networks
1University of Patras, Department of Computer Engineering and Informatics, and Artificial Intelligence
Research Center (U.P.A.I.R.C.), Greece
2Bank of Greece, Research Department, Greece
3University of Patras, Department of Computer Engineering and Informatics, Artificial Intelligence Research Center (U.P.A.I.R.C.) and Computer Technology Institute, Greece
4Bank of Greece, Research Department, 21 Panepistimiou str., Athens 10250, Greece
Received 30 December 1999
Copyright © 2000 A. S. Andreou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
“Heart attacks and devaluations are not predictable and, certainly, are never preannounced”. (The usual remark made by government spokesmen shortly after a domestic currency devaluation has taken place.)
The contribution that this paper aspires to make is the prediction of an oncoming attack against the domestic currency, something that is expected to increase the possibilities of successful hedging by the authorities. The analysis has focused on the Greek Drachma, which has suffered a series of attacks during the past few years, thus offering a variety of such “shock” incidents accompanied by frequent interventions by the authorities. The prediction exercised here is performed in a discrete dynamics environment, based on the daily fluctuations of the interbank overnight interest rate, using artificial neural networks enhanced by genetic algorithms. The results obtained on the basis of the forecasting performance have been considered most encouraging, in providing a successful prediction of an oncoming attack against the domestic currency.