One small step for a man
One Giant leap for the mankind

There is no wealth like Knowledge
                            No Poverty like Ignorance
Journal of Emerging Trends in Computing and Information Sciences Logo

Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

Fourth-order Fuzzy Time Series Based on Multi-Period Adaptation Models for Kuala Lumpur Composite Index Forecasting

Full Text Pdf Pdf
Author Lazim Abdullah, Toh Lian Fan
ISSN 2079-8407
On Pages 16-20
Volume No. 2
Issue No. 1
Issue Date January 01, 2011
Publishing Date January 01, 2011
Keywords Fourth-order, fuzzy time series, composite index, multi-period adaptation, forecasting.


Abstract

Forecasting accuracy is one of the most critical issues in fuzzy time-series models. A combination model of higher order fuzzy time series with adaption period was proposed by Chen et al as one of the mechanisms in improving forecasting accuracy. First, second, third and fourth order fuzzy times series based on multi-period adaptation models were successfully tested with stock exchange indexes in Taiwan and Hong Kong. However feasibility of the fourth order model especially the effect of multi-period adaptations to local indexes remains unknown. Therefore the present paper tests the fourth-order based on one, two, three and four-period adaptation model with datasets of Kuala Lumpur Composite Index. With the fourth-order of the adaptation model, it is found that the forecasted index based on two-period adaptation performed better than the other adaptation periods. The fourth-order based on two-period adaption seems perfectly worked with datasets of Kuala Lumpur Composite Index. 

Back

Seperator
    Journal of Computing | Journal of Networks and Communication | Journal Management System | Journal of Systems and Software | ARPN Journal of Science and Technology     
Copyrights
© 2015 Journal of Computing