Abstract
Traders and economists are often at odds with regards to the approach taken towards Forex financial market forecasting. Methods originating from the Artificial Intelligence (AI) area of study have been used extensively throughout the years in predicting the trading pattern as it is deemed to be robust enough to handle the uncertainty associated with Forex trading time series data. Herein this paper, the effects of different input types, in particular: close price as well as various technical indicators derived from the close price are investigated to determine its effects on the Forex trend predicted by an intelligent machine learning module.
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CITATION STYLE
Yong, Y. L., Ngo, D. C. L., & Lee, Y. (2015). Technical indicators for Forex forecasting: A preliminary study. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9142, pp. 87–97). Springer Verlag. https://doi.org/10.1007/978-3-319-20469-7_11
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