A hybrid genetic algorithm and particle swarm optimization based fuzzy times series model for TAIFEX and KSE-100 forecasting

Authors:
Tahseen A. Jilani;Usman Amjad;Nikos Mastorakis
Affiliations:
Department of Computer Science, University of Karachi, Karachi, Pakistan and Faculty of Engineering, Technical University of Sofia, Balgaria;Department of Computer Science, University of Karachi, Karachi, Pakistan and Faculty of Engineering, Technical University of Sofia, Balgaria;Department of Computer Science, University of Karachi, Karachi, Pakistan and Faculty of Engineering, Technical University of Sofia, Balgaria
Venue:
BICA'12 Proceedings of the 5th WSEAS congress on Applied Computing conference, and Proceedings of the 1st international conference on Biologically Inspired Computation
Year:
2012

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Abstract

In this paper we proposed a new evolutionary fuzzy time series forecasting model for Taiwan Futures Exchange (TIAFEX) and Karachi Stock Exchange (KSE-100) forecasting. Our proposed method is based on two-factor high order fuzzy logical relation groups. A hybrid algorithm composed of genetic algorithm (GA) and Particle swarm optimization (PSO) is used to adjust interval length in universe of discourse for TAIFEX and KSE-100 forecasting with the objective of increasing forecasting accuracy and minimizing forecasting error rate.