PERFORMANCE COMPARISON OF ARIMA REGRESSION MODELS AND NEURAL NETWORKS WITH GENETIC ALGORITHM IN FORECASTING IRAN'S CRUDE OIL PRICES

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ABOUNOORI A.; KHODADADI N.

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Journal: FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT) Year:2012 | Volume:3 | Issue:11 Page(s): 43-62

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Title

PERFORMANCE COMPARISON OF ARIMA REGRESSION MODELS AND NEURAL NETWORKS WITH GENETIC ALGORITHM IN FORECASTING IRAN'S CRUDE OIL PRICES

Author(s)

ABOUNOORI A. | KHODADADI N. | Issue Writer Certificate

Keywords

FORECASTQ2

IRANIAN HEAVY CRUDE OIL PRICEQ1

ARIMA MODELQ2

ARTIFICIAL NEURAL NETWORKQ2

Abstract

This research has been conducted in order to introduce a proper pattern for IRANIAN HEAVY CRUDE OIL PRICEs. The applied data in this research has been dated on third week of April 2002 to fourth week of July 2011 and is composed of 485 observations, which are employed to severance within the sample FORECASTs and out of the sample FORECASTs, in order to estimate model coefficients, almost 90% of observations (about 50 observation) has been used and remained, observations. has employed in out of sample predictions. In this research templates have been used as: An ARTIFICIAL NEURAL NETWORK model based on genetic algorithms and also a Linear regression model. The findings show that ARTIFICIAL NEURAL NETWORK model in out of sample FORECASTs, according to FORECAST error mean square error (MSE) criteria and also Mean squared error criterion (RMSE), have a much better performance comparing to Linear regression model (ARIMA).

Cites

APPLYING THE LINEAR GENETIC ALGORITHM AND NON-LINEAR GENETIC TO INCREASING THE EFFICIENCY OF PREDICTING CORPORATE PROFITABILITY

References

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APA: Copy

ABOUNOORI, A., & KHODADADI, N.. (2012). PERFORMANCE COMPARISON OF ARIMA REGRESSION MODELS AND NEURAL NETWORKS WITH GENETIC ALGORITHM IN FORECASTING IRAN'S CRUDE OIL PRICES. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), 3(11), 43-62. SID. https://sid.ir/paper/197901/en

Vancouver: Copy

ABOUNOORI A., KHODADADI N.. PERFORMANCE COMPARISON OF ARIMA REGRESSION MODELS AND NEURAL NETWORKS WITH GENETIC ALGORITHM IN FORECASTING IRAN'S CRUDE OIL PRICES. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)[Internet]. 2012;3(11):43-62. Available from: https://sid.ir/paper/197901/en

IEEE: Copy

A. ABOUNOORI, and N. KHODADADI, “PERFORMANCE COMPARISON OF ARIMA REGRESSION MODELS AND NEURAL NETWORKS WITH GENETIC ALGORITHM IN FORECASTING IRAN'S CRUDE OIL PRICES,” FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), vol. 3, no. 11, pp. 43–62, 2012, [Online]. Available: https://sid.ir/paper/197901/en

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