Summary
In this chapter, a new hierarchical hybrid wavelet — artificial neural network strategy for exchange rate prediction is introduced. The wavelet analysis (the Mallat’s pyramid algorithm) is utilised for separating signal components of various frequencies and then separate neural perceptrons perform prediction for each separate signal component. The strategy was tested for predicting the US dollar/Polish zloty average exchange rate. The achieved accuracy of prediction of value alterations direction is equal to 90%.
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Bielecki, A., Hajto, P., Schaefer, R. (2008). Hybrid Neural Systems in Exchange Rate Prediction. In: Brabazon, A., O’Neill, M. (eds) Natural Computing in Computational Finance. Studies in Computational Intelligence, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77477-8_12
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DOI: https://doi.org/10.1007/978-3-540-77477-8_12
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