Title :
A neural network to predict multiple economic time series
Author :
Vishwakarma, Keshav P.
Author_Institution :
Sch. of Econ., La Trobe Univ., Bundoora, Vic., Australia
fDate :
27 Jun- 2 Jul 1994
Abstract :
Presents a fresh approach to the analysis of multiple economic time series. To model their common movement, the author resorts to the state space framework of dynamic systems theory and makes use of a neural network to account for nonlinear evolution of the system over time. This mathematical formulation allows not only the identification of business cycles in given data but it furnishes out-of-sample forecasts as well
Keywords :
commerce; economics; neural nets; time series; business cycles; dynamic systems theory; multiple economic time series; neural network; nonlinear evolution; out-of-sample forecasts; state space framework; Business; Economic forecasting; Economic indicators; Employment; Monitoring; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Time series analysis; Turning;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374929
