Directional forecasting in financial time series using support vector machines: The USD/Euro exchange rate
In this paper, we present a novel machine learning based forecasting system of the EU/USD exchange rate directional changes. Specifically, we feed an overcomplete variable set to a Support Vector Machines (SVM) model and refine it through a Sensitivity Analysis process. The dataset spans from 1/1/1999 to 30/11/2011; the data of the last 7 months are reserved for out-of-sample testing. Results show that the proposed scheme outperforms various other machine learning methods treating similar scenarios.
|Date of creation:||27 Jan 2012|
|Contact details of provider:|| Postal: Department of Economics, University Campus, Komotini, 69100, Greece|
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