Exchange rate forecasting through distributed time-lagged feedforward neural networks

Pavlidis, N. G. and Tasoulis, D. K. and Androulakis, G. S. and Vrahatis, Michael N. (2004) Exchange rate forecasting through distributed time-lagged feedforward neural networks. In: Supply Chain And Finance :. World Scientific Publishing Co., pp. 283-298. ISBN 9789812562586

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Abstract

Throughout the last decade, the application of Artificial Neural Networks in the areas of financial and economic time series forecasting has been rapidly expanding. The present chapter investigates the ability of Distributed Time Lagged Feedforward Networks (DTLFN), trained through a popular Differential Evolution (DE) algorithm, to forecast the short-term behavior of the daily exchange rate of the Euro against the US Dollar. Performance is contrasted with that of focused time lagged feedforward networks, as well as with DTLFNs trained through alternat ive algorithms.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
Publisher Copyright: © 2004 by World Scientific Publishing Co. Re. Ltd.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2600
Subjects:
?? artificial neural networksdifferential evolution algorithmstime series predictiongeneral mathematicsgeneral economics,econometrics and financegeneral business,management and accountinggeneral engineering ??
ID Code:
225198
Deposited By:
Deposited On:
21 Oct 2024 11:20
Refereed?:
No
Published?:
Published
Last Modified:
21 Oct 2024 23:28