Using Neural Nets in Modelling Vector Time Series Available to Purchase

Presents for the first time empirical evidence on the forecasting performance of multi‐layer neural nets in modelling multiple‐input vector time series processes. Compares the results produced by the neural net with those obtained by a robust VARMAX‐algorithm and a multiple‐input state space algorithm for vector‐valued time series processes. The neural net and the VARMAX‐algorithm were programmed in the C‐language and the state space algorithm was programmed in FORTRAN.