Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Financial forecasting through unsupervised clustering and evolutionary trained neural networks
AU - Pavlidis, Nicos
AU - Tasoulis, DK
AU - Vrahatis, Michael N.
PY - 2003
Y1 - 2003
N2 - We present a time series forecasting methodology and applies it to generate one-step-ahead predictions for two daily foreign exchange spot rate time series. The methodology draws from the disciplines of chaotic time series analysis, clustering, artificial neural networks and evolutionary computation. In brief, clustering is applied to identify neighborhoods in the reconstructed state space of the system; and subsequently neural networks are trained to model the dynamics of each neighborhood separately. The results obtained through this approach are promising.
AB - We present a time series forecasting methodology and applies it to generate one-step-ahead predictions for two daily foreign exchange spot rate time series. The methodology draws from the disciplines of chaotic time series analysis, clustering, artificial neural networks and evolutionary computation. In brief, clustering is applied to identify neighborhoods in the reconstructed state space of the system; and subsequently neural networks are trained to model the dynamics of each neighborhood separately. The results obtained through this approach are promising.
U2 - 10.1109/CEC.2003.1299377
DO - 10.1109/CEC.2003.1299377
M3 - Conference contribution/Paper
SN - 0-7803-7804-0
VL - 4
SP - 2314
EP - 2321
BT - IEEE Congress on Evolutionary Computation
PB - IEEE
ER -