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Forecasting Exchange Rates Using Neural Networks for Technical Trading Rules
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Philip Hans Franses
Published/Copyright:
January 1, 1998
We examine the performance of artificial neural networks (ANNs) for technical trading rules for forecasting daily exchange rates. The main conclusion of our attempt is that ANNs perform well, and that they are often better than linear models. Furthermore, the precise number of hidden layer units in ANNs appears less important for forecasting performance than is the choice of explanatory variables.
Keywords: technical analysis; neural networks
Published Online: 1998-1-1
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Articles in the same Issue
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- Testing the Expectations Theory of the Term Structure of Interest Rates Using Model-Selection Methods
- Forecasting Exchange Rates Using Neural Networks for Technical Trading Rules
- Early News is Good News: The Effects of Market Opening on Market Volatility
- GARCH for Irregularly Spaced Financial Data: The ACD-GARCH Model
- The Current Depth-of-Recession and Unemployment-Rate Forecasts
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