DocumentCode
700758
Title
Multivariate nonlinear cointegration analysis using artificial neural networks
Author
Weeren, A.J.T.M. ; Dumortier, F. ; Plasmane, J.E.J.
Author_Institution
UFSIA (Univ. of Antwerp), Antwerp, Belgium
fYear
1997
fDate
1-7 July 1997
Firstpage
1939
Lastpage
1944
Abstract
In system identification we are often confronted with non-stationary timeseries. In the area of econometrics the method of cointegration analysis has become the most popular way to deal with models involving nonstationary data. The main disadvantage of the methodology based on cointegration is that it is basically a linear method and hence it is only capable to find linear relationships. Therefore. in this paper we propose a new method for nonlinear multivariate cointegration analysis.
Keywords
econometrics; exchange rates; neural nets; time series; artificial neural networks; econometrics; linear method; linear relationships; multivariate nonlinear cointegration analysis; nonstationary time-series; system identification; Analytical models; Artificial neural networks; Error correction; Exchange rates; Feedforward neural networks; Yttrium; Modelling; Neural nets; Nonlinear identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ECC), 1997 European
Conference_Location
Brussels
Print_ISBN
978-3-9524269-0-6
Type
conf
Filename
7082388
Link To Document