A Comparison of Bayesian Methods and Artificial Neural Networks for Forecasting Chaotic Financial Time Series

Faculty Commerce Year: 2012
Type of Publication: ZU Hosted Pages:
Authors:
Tamer Mohamed Hassan Ibrahiem Shahwan
Journal: Journal of Statistics Applications & Probability Journal of Statistics Applications & Probability Volume:
Keywords : , Comparison , Bayesian Methods , Artificial Neural Networks    
Abstract:
Most recent empirical work implies that the presence of low-dimensional deterministic chaos increases the complexity of the financial time series behavior. In this study we propose the Generalized Multilayer Perceptron (GMLP), and the Bayes
    
     
 
       

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