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Applied Computational Intelligence and Soft Computing
Volume 2012, Article ID 410832, 7 pages
Research Article

Modeling Chaotic Behavior of Chittagong Stock Indices

School of Engineering and Computer Science, Independent University, Bangladesh, Dhaka 1212, Bangladesh

Received 18 December 2011; Revised 16 May 2012; Accepted 4 June 2012

Academic Editor: Yi-Chi Wang

Copyright © 2012 Shipra Banik et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Stock market prediction is an important area of financial forecasting, which attracts great interest to stock buyers and sellers, stock investors, policy makers, applied researchers, and many others who are involved in the capital market. In this paper, a comparative study has been conducted to predict stock index values using soft computing models and time series model. Paying attention to the applied econometric noises because our considered series are time series, we predict Chittagong stock indices for the period from January 1, 2005 to May 5, 2011. We have used well-known models such as, the genetic algorithm (GA) model and the adaptive network fuzzy integrated system (ANFIS) model as soft computing forecasting models. Very widely used forecasting models in applied time series econometrics, namely, the generalized autoregressive conditional heteroscedastic (GARCH) model is considered as time series model. Our findings have revealed that the use of soft computing models is more successful than the considered time series model.