Volume 23, Issue 4 (IJIEPR 2012)                   IJIEPR 2012, 23(4): 261-268 | Back to browse issues page

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Khashei M, Mokhatab Rafiei F, Bijari M. Overview and Comparison of Short-term Interval Models for Financial Time Series Forecasting. IJIEPR. 2012; 23 (4) :261-268
URL: http://ijiepr.iust.ac.ir/article-1-463-en.html
1- ,PhD student of Industrial Engineering, Isfahan University of Technology Isfahan, Iran
2- , Assistant professor of Industrial Engineering, Isfahan University of Technology Isfahan, Iran
3- , Associated professor of Industrial Engineerin, Isfahan University of Technology Isfahan, Iran
Abstract:   (4290 Views)

  In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficient once in financial markets. In this paper, the performance of four interval time series models including autoregressive integrated moving average (ARIMA), fuzzy autoregressive integrated moving average (FARIMA), hybrid ANNs and fuzzy (FANN) and Improved FARIMA models are compared together. Empirical results of exchange rate forecasting indicate that the FANN model is more satisfactory than other those models. Therefore, it can be a suitable alternative model for interval forecasting of financial time series.

 

 

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Type of Study: Research | Subject: Other Related Subject
Received: 2012/09/8 | Published: 2012/11/15

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