Andreou, Andreas S. and Zombanakis, George A. and Georgopoulos, E. F. and Likothanassis, S. D. (1998): Forecasting ExchangeRates via Local Approximation Methods and Neural Networks. Published in: European Research Studies , Vol. 1, No. 4 (December 1998): pp. 533.

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Abstract
There has been an increased number of papers in the literature in recent years, applying several methods and techniques for exchange  rate prediction. This paper focuses on the Greek drachma using daily observations of the drachma rates against four major currencies, namely the U.S. Dollar (USD), the Deutsche Mark (DM), the French Franc (FF) and the British Pound (GBP) for a period of 11 years, aiming at forecasting their shortterm course by applying local approximation methods based on both chaotic analysis and neural networks.
Item Type:  MPRA Paper 

Original Title:  Forecasting ExchangeRates via Local Approximation Methods and Neural Networks 
Language:  English 
Keywords:  Key Words: Exchange Rates, Forecasting, Neural Networks 
Subjects:  C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C45  Neural Networks and Related Topics 
Item ID:  17764 
Depositing User:  Dr. GEORGE ZOMBANAKIS 
Date Deposited:  10. Oct 2009 05:56 
Last Modified:  14. Nov 2013 12:28 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/17764 