Multivariate nonlinear cointegration analysis using artificial neural networks
Arie J. T. M. Weeren, F.A.G. Dumortier, J. E. J. Plasmane · 1997
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.