Technical Indicators for Forex Forecasting: A Preliminary Study

Conference paper

DOI: 10.1007/978-3-319-20469-7_11

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9142)
Cite this paper as:
Yong Y.L., Ngo D.C., Lee Y. (2015) Technical Indicators for Forex Forecasting: A Preliminary Study. In: Tan Y., Shi Y., Buarque F., Gelbukh A., Das S., Engelbrecht A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science, vol 9142. Springer, Cham


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.


Forex forecasting Technical analysis Linear regression line Artificial Neural Network Dynamic Time Warping 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computing and Information SystemsSunway UniversityBandar SunwayMalaysia

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