Volume 3, Issue 8 (6-2012)                   jemr 2012, 3(8): 119-140 | Back to browse issues page

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Naderi E, Abbasi-Nejad H. Chaos Analysis, Wavelet Decomposition and the Performance of Neural Network Models in Forecasting Tehran Stock Exchange Index. jemr 2012; 3 (8) :119-140
URL: http://jemr.khu.ac.ir/article-1-508-en.html
1- Tehran University , naderi.ec@ut.ac.ir
2- Tehran University
Abstract:   (12349 Views)

This study investigates predictability, chaos analysis, wavelet decomposition and the performance of neural network models in forecasting the return series of the Tehran Stock Exchange Index (TEDPIX). For this purpose, the daily data from April 24, 2009 to May 3, 2012 is used. Results show that TEDPIX series is chaotic and predictable with nonlinear effect. Also, according to obtained inverse of the largest lyapunov exponent, we are able to predict the future values of the series up to 31 days. Besides, our findings suggest that multi-layer feed forward neural network model and fuzzy model based on decomposed data, are of superior performances in predicting the return series. It is worth mentioning that, among these models, MFNN reveals the best performance.

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Type of Study: Applicable | Subject: پولی و مالی
Received: 2012/07/14 | Accepted: 2012/11/12 | Published: 2012/09/15

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