A hybrid approach for modeling financial time series
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 9, Issue 4 (31 Jul. 2012), pp.327-335, 9 p.
Publisher
Publication Date
2012-07-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
The problem we tackle concerns forecasting time series in financial markets.
Auto Regressive Moving-Average (ARMA) methods and computational intelligence have also been used to tackle this problem.
We propose a novel method for time series forecasting based on a hybrid combination of ARMA and Gene Expression Programming (GEP) induced models.
Time series from financial domains often encapsulate different linear and non-linear patterns.
ARMA models, although flexible, assume a linear form for the models.
GEP evolves models adapting to the data without any restrictions with respect to the form of the model or its coefficients.
Our approach benefits from the capability of ARMA to identify linear trends as well as GEP’s ability to obtain models that capture nonlinear patterns from data.
Investigations are performed on real data sets.
They show a definite improvement in the accuracy of forecasts of the hybrid method over pure ARMA and GEP used separately.
Experimental results are analyzed and discussed.
Conclusions and some directions for further research end the paper.
American Psychological Association (APA)
Barbulescu, Alina& Bautu, Elena. 2012. A hybrid approach for modeling financial time series. The International Arab Journal of Information Technology،Vol. 9, no. 4, pp.327-335.
https://search.emarefa.net/detail/BIM-305189
Modern Language Association (MLA)
Barbulescu, Alina& Bautu, Elena. A hybrid approach for modeling financial time series. The International Arab Journal of Information Technology Vol. 9, no. 4 (Jul. 2012), pp.327-335.
https://search.emarefa.net/detail/BIM-305189
American Medical Association (AMA)
Barbulescu, Alina& Bautu, Elena. A hybrid approach for modeling financial time series. The International Arab Journal of Information Technology. 2012. Vol. 9, no. 4, pp.327-335.
https://search.emarefa.net/detail/BIM-305189
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 334
Record ID
BIM-305189