Application of support vector machines in financial time series forecasting

This paper deals with the application of a novel neural network technique, support vector machine (SVM), in financial time series forecasting. The objective of this paper is to examine the feasibility of SVM in financial time series forecasting by comparing it with a multi-layer back-propagation (BP...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Omega (Oxford) 2001-08, Vol.29 (4), p.309-317
Hauptverfasser:	Tay, Francis E.H, Cao, Lijuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Artificial intelligence Back propagation BP neural network Computer science control theory systems Connectionism. Neural networks Exact sciences and technology Financial performance Forecasting Forecasting techniques Generalization Mean square errors Neural networks Operational research and scientific management Operational research. Management science Risk theory. Actuarial science Structural risk minimization principle Studies Support vector machines Support vector machines Structural risk minimization principle BP neural network Generalization Symmetry Time series
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!