Journal Paper

Paper Information

video

sound

Persian Version

View:

723

Download:

219

Cites:

5

Information Journal Paper

Title

FORECASTING EXCHANGE RATE WITH ARTIFICIAL NEURAL NETWORK (ANN) AND AUTOREGRESSIVE INTEGRATED MOVING AVERAGE PROCESS (ARIMA)

Pages

 Start Page 107 | End Page 130

Keywords

AUTOREGRESSIVE INTEGRATED MOVING AVERAGE PROCESS (ARIMA)Q2
ARTIFICIAL NEURAL NETWORK (ANN)Q3

Abstract

 One of the traditional methods for forecasting is time series analyzing, which based on tow assumption: stationary and linearity. There is Suspicion to working by the traditional models. One of the substitute methods is Artificial Neural Network (ANN) which sometimes shows good potential ability for forecasting time series. In this paper, after reviewing the recent studies on ability of Autoregressive Integrated Moving Average Process (ARIMA) and ANN, tow models for forecasting the exchange rate between march 2006 and February 2009 in Iran are compared. The results show that ANN has a better estimate than ARIMA. In this research, the MATLAB and Central bank data are utilized.

Cites

References

Related Journal Papers

Related Seminar Papers

  • No record.
  • Related Plans

  • No record.