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Contribution à l'étude des méthodes quantitatives d'aide à la décision –appliquées aux indices du marché d'actions

Abstract : This thesis is divided into two parts: first, it concerns the study of different quantitative methods used for decision making support in all situations. Second, study and analysis of the stock market index in Egypt. Indeed, the Egyptian stock market is considered to be inefficient with respect to the international stock markets. According to this, we expect that it is very difficult to use the traditional forecasting methods to predict the trend of the stock market index. In order to predict the Cairo & Alexandria Stock Exchanges (CASE), the Box-Jenkins Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) methods were applied to predict the stock market index of (CASE) in Egypt. For this purpose, we have used the stock market index samples for the CASE collected from 1992-2005 (3311 daily time series observation). The traditional forecasting method ARIMA was found to be not able to predict the CASE stock market index. However, the ANN prediction method was found to be able to follow the real trend of the index. This was confirmed by the Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE). Hence, neural networks for weekly prediction of financial stock markets are efficient. Consequently, the individual investor could make the most of the use of this forecasting method for his decision especially in the stock market.
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Submitted on : Monday, September 7, 2009 - 3:03:39 PM
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Kreit Zakwan. Contribution à l'étude des méthodes quantitatives d'aide à la décision –appliquées aux indices du marché d'actions. Sciences de l'Homme et Société. Université Montesquieu - Bordeaux IV, 2007. Français. ⟨tel-00413979⟩

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