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A boost in exchange rate forecasting: qualitative variables, technical indicators and parameters selection
José Antonio Sanabria, Germán Sánchez, Núria Agell
310 - 317
10.3233/978-1-60750-061-2-310
Frontiers in Artificial Intelligence and Applications
Volume 202: Artificial Intelligence Research and Development
Abstract

This paper tries to determine, through the use of Support Vector Machines (SVM), the impact that technical indicators, a qualitative variable and the choice of free parameters selection have on a model's forecasting performance, power and accuracy applied to currency exchange rate prediction. This approach was applied to the weekly currency exchange rate between the European euro andc the US dollar. The results obtained show that the proposed factors can significantly impact the model's forecasting performance compared to traditional models where no qualitative information is incorporated.

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