Advances and Applications in Statistics
Volume 36, Issue 2, Pages 131 - 150
(October 2013)
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A COMPARISON BETWEEN THE MODELS ARIMA/ GARCH AND ARTIFICIAL NEURAL NETWORKS IN MODELING FINANCIAL RETURNS TO THE ARAB REPUBLIC OF EGYPT MARKET SECURITIES
Rania Ahmed Hamed Mohamed
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Abstract: Modeling and forecasting returns in the financial market are important issues in finance, they have a great importance especially for the investors, policy makers, banks, and others. The main objective of our paper is to compare the performance of the ARMA/GARCH model and the artificial neural networks (ANNs) to determine which model does a better performance in modeling Financial Returns in the Arab Republic of Egypt Market in the period from 01/01/2002 to 01/24/2011. The results showed that ANN model outperforms the ARMA/GARCH model in deviation performance criteria. |
Keywords and phrases: autoregressive moving average (ARMA), generalized autoregressive conditional heteroscedasticity (GARCH), artificial neural network (ANN), back propagation. |
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