Abounoori, Abbas Ali and Mohammadali, Hanieh and Gandali Alikhani, Nadiya and Naderi, Esmaeil (2012): Comparative study of static and dynamic neural network models for nonlinear time series forecasting.

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Abstract
During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis different types of these models have been used in forecasting. Now, there is this question that which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this, the present paper made a comparison between static and dynamic neural network models in forecasting the return of Tehran Stock Exchange (TSE) index in order to find the best model to be used for forecasting this series (as a nonlinear financial time series). The data were collected daily from 25/3/2009 to 22/10/2011. The models examined in this study included two static models (Adaptive NeuroFuzzy Inference Systems or ANFIS and Multilayer Feedforward Neural Network or MFNN) and a dynamic model (nonlinear neural network autoregressive model or NNAR). The findings showed that based on the Mean Square Error and Root Mean Square Error criteria, ANFIS model had a much higher forecasting ability compared to other models.
Item Type:  MPRA Paper 

Original Title:  Comparative study of static and dynamic neural network models for nonlinear time series forecasting 
English Title:  Comparative Study of Static and Dynamic Neural Network Models for Nonlinear Time Series Forecasting 
Language:  English 
Keywords:  Forecasting, Stock Market, dynamic Neural Network, Static Neural Network. 
Subjects:  C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C45  Neural Networks and Related Topics C  Mathematical and Quantitative Methods > C6  Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C60  General G  Financial Economics > G1  General Financial Markets > G14  Information and Market Efficiency ; Event Studies ; Insider Trading G  Financial Economics > G1  General Financial Markets > G17  Financial Forecasting and Simulation 
Item ID:  46466 
Depositing User:  esmeil naderi 
Date Deposited:  22 Apr 2013 20:25 
Last Modified:  26 Sep 2019 08:17 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/46466 