Financial forecasting through unsupervised clustering and evolutionary trained neural networks

We present a time series forecasting methodology and applies it to generate one-step-ahead predictions for two daily foreign exchange spot rate time series. The methodology draws from the disciplines of chaotic time series analysis, clustering, artificial neural networks and evolutionary computation...

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Bibliographische Detailangaben

Hauptverfasser:	Pavlidis, N.G., Tasoulis, D.K., Vrahatis, M.N.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Artificial neural networks Chaos Clustering algorithms Economic forecasting Evolutionary computation Feedforward neural networks Neural networks Predictive models State-space methods Time series analysis
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