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Currency Exchange Rate Forecasting with Neural Networks
Nasution, Bona Patria ; Agah, Arvin
Nasution, Bona Patria
Agah, Arvin
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Abstract
This paper presents the prediction of foreign currency exchange rates using artificial neural networks. Since neural networks can generalize from past experience, they represent a significant advancement over traditional trading systems, which require a knowledgeable expert to define trading rules to represent market dynamics. It is practically impossible to expect that one expert can devise trading rules that account for, and accurately reflect, volatile and rapidly changing market conditions. With neural networks, a trader may use the predictive information alone or with other available analytical tools to fit the trading style, risk propensity, and capitalization. Numerous factors affect the foreign exchange market, as they will be described in this paper. The neural network will help minimize these factors by simply giving an estimated exchange rate for a future day (given its previous knowledge gained from extensive training). Because the field of financial forecasting is too large, the scope in this paper is narrowed to the foreign exchange market, specifically the value of the Japanese Yen against the United States Dollar, two of the most important currencies in the foreign exchange market.
Description
This is the published version. Copyright De Gruyter
Date
2000
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Publisher
De Gruyter
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Keywords
Artificial neural networks, Prediction, Financial markets
Citation
Nasution, Bona Patria, and Arvin Agah. "Currency Exchange Rate Forecasting with Neural Networks." Journal of Intelligent Systems 10.3 (2000): n. pag. http://dx.doi.org/10.1515/JISYS.2000.10.3.219