FORECASTING OF CRUDE OIL PRICES USING NEURAL NETWORKS AND OECD INVENTORIES

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

POURKAZEMI M.H.; ASADI MOHAMMAD BAGHER

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Economic Research Year:2009 | Volume:44 | Issue:88 Page(s): 25-46

Download Full-Text

Persian Verion

View:

2,028

Download:

Cites:

Information Journal Paper

Title

FORECASTING OF CRUDE OIL PRICES USING NEURAL NETWORKS AND OECD INVENTORIES

Author(s)

POURKAZEMI M.H. | ASADI MOHAMMAD BAGHER | Issue Writer Certificate

Keywords

FORECASTINGQ2

CRUDE OIL PRICEQ2

NEURAL NETWORKSQ2

ARIMAQ3

INVENTORIESQ2

Abstract

On one hand, oil is the greatest energy resource in the world and, on the other hand, because of the role of oil revenue in the economics of oil producer countries, such as Iran, it is vital for these countries. So it is necessary to recognize different affective parameters on oil market for these countries. In this research, we try to forecast oil price as an important variable in worldwide oil market by using NEURAL NETWORKS and ARIMA model. The results of dynamic forecasts have shown that in all cases neural network has better results than ARIMA model. In addition, the results of this research have shown that by use of OECD INVENTORIES as an added input in model and doing a bivariate FORECASTING (for the first time in Iran) the error of oil prices forecasts will reduce.

Cites

References

Cite

APA: Copy

POURKAZEMI, M.H., & ASADI, MOHAMMAD BAGHER. (2009). FORECASTING OF CRUDE OIL PRICES USING NEURAL NETWORKS AND OECD INVENTORIES. TAHGHIGHAT-E-EGHTESADI, 44(88), 25-46. SID. https://sid.ir/paper/12029/en

Vancouver: Copy

POURKAZEMI M.H., ASADI MOHAMMAD BAGHER. FORECASTING OF CRUDE OIL PRICES USING NEURAL NETWORKS AND OECD INVENTORIES. TAHGHIGHAT-E-EGHTESADI[Internet]. 2009;44(88):25-46. Available from: https://sid.ir/paper/12029/en

IEEE: Copy

M.H. POURKAZEMI, and MOHAMMAD BAGHER ASADI, “FORECASTING OF CRUDE OIL PRICES USING NEURAL NETWORKS AND OECD INVENTORIES,” TAHGHIGHAT-E-EGHTESADI, vol. 44, no. 88, pp. 25–46, 2009, [Online]. Available: https://sid.ir/paper/12029/en

Related Journal Papers