Forecasting Exchange-Rates via Local Approximation Methods and Neural Networks
AbstractThere 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 short-term course by applying local approximation methods based on both chaotic analysis and neural networks.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 17764.
Date of creation: Dec 1998
Date of revision:
Publication status: Published in EUROPEAN RESEARCH STUDIES 4.1(1998): pp. 5-33
Key Words: Exchange Rates; Forecasting; Neural Networks;
Other versions of this item:
- A.S. Andreou & G.A. Zombanakis & E.F. Georgopoulos & S.D. Likothanassis, 1998. "Forecasting Exchange-Rates via Local Approximation Methods and Neural Networks," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 5-15, October -.
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
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