WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 17, 2018
Prediction Stock Market Exchange Prices for the Reserve Bank of Australia Using Auto-Regressive with eXogenous Input Neural Network Model
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Abstract: Financial forecasting is one of the challenging fields of research due to its wide commercial applications and high risks that could happen to courtiers economies if fail to deal with various changes in the market. Stock Market found to be a dynamic, non-linear and complex process in nature. It is usually affected by many factors such as economic conditions, bank exchange rate, investors’ expectations, governmental events, and of course Wars in various areas of the world. The process of prediction/forecasting of money exchange rate help organizations, governments and business market to make decisions; it is essential for determining information about future markets. This paper introduces the basic idea of developing mathematical models for currency exchange rate using Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) models. The data set used in the experiments collected during January 4, 2010 to December 31, 2013. Number of criterion were used to validate the developed model’s performance. The NN model show promising results.
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Keywords: Prediction, Stock Market Exchange Prices, Reserve Bank of Australia, Artificial Neural Networks
Pages: 79-88
WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 17, 2018, Art. #9