Journal
NEUROCOMPUTING
Volume 61, Issue -, Pages 439-447Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2004.04.002
Keywords
non-stationary time series; overfitting; artificial neural networks; asymptotic stationary; autoregressive model
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The use of artificial neural networks (ANN) has received increasing attention in the analysis and prediction of financial time series. Stationarity of the observed financial time series is the basic underlying assumption in the practical application of ANN on financial time series. In this paper, we will investigate whether it is feasible to relax the stationarity condition to non-stationary time series. Our result discusses the range of complexities caused by non-stationary behavior and finds that overfitting by ANN could be useful in the analysis of such non-stationary complex financial time series. (C) 2004 Elsevier B.V. All rights reserved.
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