Modeling Chaotic Behavior of Chittagong Stock Indices

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ID: 70082
2012
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Abstract
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.
Reference Key
banik2012modelingapplied Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Banik, Shipra;Anwer, Mohammed;Khan, A. F. M. Khodadad;
Journal applied computational intelligence and soft computing
Year 2012
DOI
DOI not found
URL
http://dx.doi.org/10.1155/2012/410832
Keywords
Biology (General) Information technology business economics as a science agriculture finance insurance electronic computers. computer science business mathematics. commercial arithmetic. including tables, etc.

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