Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
第36回ISCIE「確率システム理論と応用」国際シンポジウム(2004年11月, 埼玉鳩山)
A Feed Forward Artificial Neural Nework for the Stock Market Forecasting Using Conventional Forecasts as Input Variables
T.K.K.R. MediliyegedaraL.H.P. Gunaratne
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2005 年 2005 巻 p. 194-198

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In this study, First, Milanka Price Index (MPI) of the Colombo Stock Exchange (CSE) was forecast using Linear Moving average (LMA), Simple Exponential Smoothing (SES) and Adaptive Response Religh's Single exponential Smoothing (ARRSES). Then, a Feed - Forward Artificial Neural Network (FFANN) approach was developed where the inputs of the neural network are the forecasted values from conventional forecasting techniques. Mean Absolute Percentage Error (MAPE) and Prediction Error Variance (PEV) were employed to measure the performance of LMA, SES, ARRESES and the proposed FFANN method. Finally, the results of the conventional approaches have been compared with that of the proposed FFANN approach.
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© 2005 ISCIE Symposium on Stochastic Systems Theory and Its Applications
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