A HYBRID COMPUTATIONAL INTELLIGENCE MODEL FOR FOREIGN EXCHANGE RATE FORECASTING

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.

KHASHEI MEHDI; MOKHATAB RAFIEI FARIMAH; BIJARI MEHDI; HEJAZI SEYED REZA

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

Journal Paper

Paper Information

Journal: JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL Year:2011 | Volume:7 | Issue:15 Page(s): 15-29

Download Full-Text

View:

325

Download:

164

Cites:

Information Journal Paper

Title

A HYBRID COMPUTATIONAL INTELLIGENCE MODEL FOR FOREIGN EXCHANGE RATE FORECASTING

Author(s)

KHASHEI MEHDI | MOKHATAB RAFIEI FARIMAH | BIJARI MEHDI | HEJAZI SEYED REZA | Issue Writer Certificate

Keywords

COMPUTATIONAL INTELLIGENCE

ARTIFICIAL NEURAL NETWORKS (ANNS)

FUZZY LOGIC; TIME SERIES FORECASTING

FINANCIAL MARKETS

EXCHANGE RATE

Abstract

COMPUTATIONAL INTELLIGENCE approaches have gradually established themselves as a popular tool for forecasting the complicated FINANCIAL MARKETS. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models proposed in several past decades, it is widely recognized that EXCHANGE RATEs are extremely difficult to forecast. Artificial Neural Networks (ANNs) are one of the most accurate and widely used forecasting models that have been successfully applied for EXCHANGE RATE forecasting. In this paper, a hybrid model is proposed based on the basic concepts of artificial neural networks in order to yield more accurate results than the traditional ANNs in short span of time situations. Three EXCHANGE RATE data sets—the British pound, the United States dollar, and the Euro against the Iran rial-are used in order to demonstrate the appropriateness and effectiveness of the proposed model. Empirical results of EXCHANGE RATE forecasting indicate that hybrid modelis generally better than artificial neural networks and other models presented for EXCHANGE RATE forecasting, in cases where inadequate historical data are available. Therefore, our proposed model can be a suitablealternative model for FINANCIAL MARKETS to achieve greater forecasting accuracy, especiallyin incomplete data situations.

Cites

No record.

References

No record.

Cite

APA: Copy

KHASHEI, MEHDI, MOKHATAB RAFIEI, FARIMAH, BIJARI, MEHDI, & HEJAZI, SEYED REZA. (2011). A HYBRID COMPUTATIONAL INTELLIGENCE MODEL FOR FOREIGN EXCHANGE RATE FORECASTING. JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL, 7(15), 15-29. SID. https://sid.ir/paper/309890/en

Vancouver: Copy

KHASHEI MEHDI, MOKHATAB RAFIEI FARIMAH, BIJARI MEHDI, HEJAZI SEYED REZA. A HYBRID COMPUTATIONAL INTELLIGENCE MODEL FOR FOREIGN EXCHANGE RATE FORECASTING. JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL[Internet]. 2011;7(15):15-29. Available from: https://sid.ir/paper/309890/en

IEEE: Copy

MEHDI KHASHEI, FARIMAH MOKHATAB RAFIEI, MEHDI BIJARI, and SEYED REZA HEJAZI, “A HYBRID COMPUTATIONAL INTELLIGENCE MODEL FOR FOREIGN EXCHANGE RATE FORECASTING,” JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL, vol. 7, no. 15, pp. 15–29, 2011, [Online]. Available: https://sid.ir/paper/309890/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops