Abstract
This study presents a neural network & web-based decision support system (DSS) for foreign exchange (forex) forecasting and trading decision, which is adaptable to the needs of financial organizations and individual investors. In this study, we integrate the back-propagation neural network (BPNN)- based forex rolling forecasting system to accurately predict the change in direction of daily exchange rates, and the Web-based forex trading decision support system to obtain forecasting data and provide some investment decision suggestions for financial practitioners. This research reveals the structure of the DSS by the description of an integrated framework, and meantime we find that the DSS is integrated, user-oriented by its implementation, and practical applications reveal that this DSS demonstrates very high forecasting accuracy and its trading recommendations are reliable.
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© 2004 Springer-Verlag Berlin Heidelberg
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Lai, K.K., Yu, L., Wang, S. (2004). A Neural Network and Web-Based Decision Support System for Forex Forecasting and Trading. In: Shi, Y., Xu, W., Chen, Z. (eds) Data Mining and Knowledge Management. CASDMKM 2004. Lecture Notes in Computer Science(), vol 3327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30537-8_27
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DOI: https://doi.org/10.1007/978-3-540-30537-8_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23987-1
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