Title :
A new criterion of NN structure selection for financial forecasting
Author :
Perrone, Antonio L. ; Basti, Gianfranco
Author_Institution :
Pontifical Lateran Univ., Rome, Italy
Abstract :
For the evaluation and the selection of the optimal neural net (NN) structure complexity, as a function of the minimization either of the approximation error or of the generalization error, we discuss briefly the minimum description length (MDL) method. Because of the theoretical and practical limitations of this criterion-overall for stochastic time series previsions-we shortly introduce our new dynamic sampling window (DSW) method for the optimal NN structure definition for financial forecasting
Keywords :
finance; forecasting theory; minimisation; neural net architecture; time series; DSW method; MDL method; NN structure selection criterion; approximation error minimization; dynamic sampling window method; financial forecasting; generalization error minimization; minimum description length method; optimal neural net structure complexity; stochastic time series previsions; Approximation error; Cost function; Laboratories; Length measurement; Minimization methods; Neural networks; Phase estimation; Predictive models; Sampling methods; Stochastic processes;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.830778
