NDLI: Nonstationarity and data preprocessing for neural network predictions of an economic time series

Content Provider	IEEE Xplore Digital Library
Author	Virili, F. Freisleben, B.
Copyright Year	2000
Description	Author affiliation: Dept. of Bus. Inf. Syst., Siegen Univ., Germany (Virili, F.)
Abstract	The presence of stochastic or deterministic trends in economic time series can be a major obstacle for producing satisfactory predictions with neural networks. In this paper, we demonstrate the effects of nonstationarity on neural network predictions using the time series of the mortgage loans purchased in the Netherlands. We present different preprocessing techniques for removing nonstationarity, and evaluate their properties by producing multi-step predictions using a linear stochastic forecasting model and a neural network. The results indicate that detecting nonstationarity and selecting an appropriate preprocessing technique is highly beneficial for improving the prediction quality.
Starting Page	129
Ending Page	134
File Size	565618
Page Count	6
File Format	PDF
ISBN	0769506194
ISSN	10987576
DOI	10.1109/IJCNN.2000.861446
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-27
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data preprocessing Neural networks Economic forecasting Stochastic processes Loans and mortgages Predictive models Electronic mail Equations Electric shock Information systems
Content Type	Text
Resource Type	Article

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Nonstationarity and data preprocessing for neural network predictions of an economic time series