- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 410832, 7 pages
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.
- B. Mandelbrot, “The variation of certain speculative prices,” Journal of Business, vol. 36, pp. 394–419, 1963.
- E. F. Fama, “The behavior of stock market prices,” Journal of Business, vol. 38, pp. 34–105, 1965.
- D. A. Hsu, R. B. Miler, and D. W. Wichern, “On the stable paretian behavior of stock market prices,” Journal of the American Statistical Association, vol. 69, pp. 108–113, 1974.
- D. Kim and S. J. Kon, “Alternative models for the conditional heteroskedasticity of stock returns,” Journal of Business, vol. 67, pp. 563–598, 1994.
- R.F. Engle, “Autoregressive conditional heteroscedasticity with estimates of the variance of UK Inflation,” Econometrica, vol. 50, pp. 987–1008, 1982.
- T. Bollerslev, “Generalized autoregressive conditional heteroskedasticity,” Journal of Econometrics, vol. 31, no. 3, pp. 307–327, 1986.
- S. Banik, M. Anwer, K. Khan, R. A. Rouf, and F. H. Chanchary, “Neural network and genetic algorithm approaches for forecasting bangladeshi monsoon rainfall,” in Proceedings of the 11th International Conference on Computer and Information Technology (ICCIT '08), December 2008.
- J. S. R. Jang, “ANFIS: adaptive-network-based fuzzy inference system,” IEEE Transactions on Systems, Man and Cybernetics, vol. 23, no. 3, pp. 665–685, 1993.
- D. F. Cook and M. L. Wolfe, “A back-propagation neural network to predict average air temperatures,” AI Applications in Natural Resource Management, vol. 5, no. 1, pp. 40–46, 1991.
- A. Abraham, N. S. Philip, and P. Saratchandran, “Modeling chaotic behavior of stock indices using intelligent paradigms,” International Journal of Neural, Parallel and Scientific Computations, vol. 11, no. 1-2, pp. 143–160, 2003.
- J. Kamruzzaman and R. A. Sarker, “Comparing ANN based models with ARIMA for prediction of forex rates,” Bulletin of the American Schools of Oriental Research, vol. 22, no. 2, pp. 2–11, 2003.
- G. E. P. Box and G. Jenkins, Time Series Analysis: Forecasting and Control, Cambridge University Press, Cambridge, UK, 1970.
- S. Banik, F. H. Chanchary, R. A. Rouf, and K. Khan, “Modeling chaotic behavior of Dhaka Stock Market Index values using the neuro-fuzzy model,” in Proceedings of the 10th International Conference on Computer and Information Technology (ICCIT '07), pp. 80–85, December 2007.
- C. R. Nelson and C. R. Plosser, “Trends and random walks in macroeconmic time series. Some evidence and implications,” Journal of Monetary Economics, vol. 10, no. 2, pp. 139–162, 1982.
- W. F. Mitchell, “Testing for unit roots and persistence in OECD unemployment rates,” Applied Economics, vol. 25, no. 12, pp. 1489–1501, 1993.
- R. S. McDougall, “The seasonal unit root structure in New Zealand macroeconomic variables,” Applied Economics, vol. 27, pp. 817–827, 1995.
- W. H. Greene, Econometric Analysis, Prentice Hall, Upper Saddle River, NJ, USA, 7th edition, 2008.
- S. Banik, Testing for Stationarity, Seasonality and Long Memory in Economic and Financial Time Series [Ph.D. thesis], School of Business, La Trobe University, Bundoora, Australia, 1999, Unpublished.
- S. Banik and P. Silvapulle, “Testing for seasonal stability in unemployment series: international evidence,” Empirica, vol. 26, no. 2, pp. 123–139, 1999.
- S. E. Said and D. A. Dickey, “Testing for unit roots in autoregressive-moving average models of unknown order,” Biometrika, vol. 71, no. 3, pp. 599–607, 1984.
- P. C. B. Phillips and P. Perron, “Testing for a unit root in time series regression,” Biometrika, vol. 75, no. 2, pp. 335–346, 1988.
- R. L. Thomas, Modern Econometrics: An Introduction, Addision-Wesley, New York, NY, USA, 1997.
- J. N. Holland, Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, Mich, USA, 1975.
- Y. H. Lee, S. K. Park, and D. E. Chang, “Parameter estimation using the genetic algorithm and its impact on quantitative precipitation forecast,” Annales Geophysicae, vol. 24, no. 12, pp. 3185–3189, 2006.
- J. R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, Mass, USA, 1992.
- Z. Wei, W. U. Zhi-ming, and Y. Gen-Ke, “Genetic programming-based chaotic time series modeling,” Journal of Zhejiang University, vol. 5, no. 11, pp. 1432–1439, 2004.
- H. Pohlheim, Documentation for Genetic and Evolutionary Algorithm Toolbox for Use with MATLAB, 2005.