STOCK INDEX PREDICTION BY MODELING

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.

HEYBATI FARSHAD; MOUSAVI SEYYED MOSTAFA

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

Journal Paper

Paper Information

Journal: ECONOMIC RESEARCH REVIEW Year:2010 | Volume:10 | Issue:7 (SUPPLEMENT) Page(s): 61-72

Download Full-Text

Persian Verion

View:

2,550

Download:

Cites:

Information Journal Paper

Title

STOCK INDEX PREDICTION BY MODELING

Author(s)

HEYBATI FARSHAD | MOUSAVI SEYYED MOSTAFA | Issue Writer Certificate

Keywords

Not Registered.

Abstract

Even though now a days most of the financial markets are moving toward efficiency, but the be life in market predication has not reduced. The stock market as a complex and adaptive system is more consistent with what is known in other sciences, such as physics and biology, and appears to be more descriptive of actual markets activity. This theory is able to conclude some facts that predict the direction of market in the world. The best tools are the ones that could work, think, and decide like smart humans in this complex market environment. Artificial intelligent system is one of these systems that is designed and modeled according to human brain which is able to recognize, learn, decide, and predict very complex patterns.Stock markets, with all the internal and external events, are still predictable were formed in this research. With collection of all the monthly reports and resources from 2001 to 2005 which include: economical, financial, political variables and market behaviour, companies performance predication, substitution markets and monthly average index movement.All of which we could have put to neural networks (RBF) and neural fuzzy networks (ANFIS) to test. After the training of 550 inputs and then test with 50 inputs, the result of which showed that with the help (ANFIS) we could predict 98% of Iranian stock market.

Cites

No record.

References

No record.

Cite

APA: Copy

HEYBATI, FARSHAD, & MOUSAVI, SEYYED MOSTAFA. (2010). STOCK INDEX PREDICTION BY MODELING. ECONOMIC RESEARCH REVIEW, 10(7 (SUPPLEMENT)), 61-72. SID. https://sid.ir/paper/67123/en

Vancouver: Copy

HEYBATI FARSHAD, MOUSAVI SEYYED MOSTAFA. STOCK INDEX PREDICTION BY MODELING. ECONOMIC RESEARCH REVIEW[Internet]. 2010;10(7 (SUPPLEMENT)):61-72. Available from: https://sid.ir/paper/67123/en

IEEE: Copy

FARSHAD HEYBATI, and SEYYED MOSTAFA MOUSAVI, “STOCK INDEX PREDICTION BY MODELING,” ECONOMIC RESEARCH REVIEW, vol. 10, no. 7 (SUPPLEMENT), pp. 61–72, 2010, [Online]. Available: https://sid.ir/paper/67123/en

Related Journal Papers