IRAN STOCK MARKET PREDICTION BASED ON BAYESIAN NETWORKS AND HIDDEN MARKOV MODELS

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.

ALAMATIAN ZOHREH; VAFAEI JAHAN MAJID

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

Journal Paper

Paper Information

Journal: FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT) Year:2018 | Volume:8 | Issue:33 Page(s): 283-298

Download Full-Text

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

Persian Verion

View:

887

Download:

Cites:

Information Journal Paper

Title

IRAN STOCK MARKET PREDICTION BASED ON BAYESIAN NETWORKS AND HIDDEN MARKOV MODELS

Author(s)

ALAMATIAN ZOHREH | VAFAEI JAHAN MAJID | Issue Writer Certificate

Keywords

TECHNICAL INDICATORQ1

STOCK MARKETQ2

INDEXQ2

BAYESIAN NETWORKQ1

HIDDEN MARKOV MODELQ1

Abstract

Stock market behavior is one of the most complex mechanisms, considered by researchers. Financial markets are influenced by the external and internal factors. External factors such as political and social factors are not measurable, so prediction the trend of STOCK MARKETs is focused on internal factors.This study suggests a hybrid approach based on BAYESIAN NETWORKs and HIDDEN MARKOV MODELs to predict trend of STOCK MARKET. The used variables are 6 INDEX of Tehran Stock Exchange, which have the most correlation coefficient with target stock, and 22 TECHNICAL INDICATORs. BAYESIAN NETWORKs are utilized to find the relationships between variables, and the effect of each variable in prediction considered from conditional probability tables. HIDDEN MARKOV MODEL is designed for sets of extract from BAYESIAN NETWORKs.The proposed model tested on four company’s stock names Mobarakeh Steel, Iran Khodro, Mellat Bank and Iran drug.The average accuracy of the proposed system is 83.26 %. The experimental results show that the suggested procedure has higher performance for prediction of STOCK MARKETs in comparison with other previous methods.

Cites

No record.

References

No record.

Cite

APA: Copy

ALAMATIAN, ZOHREH, & VAFAEI JAHAN, MAJID. (2018). IRAN STOCK MARKET PREDICTION BASED ON BAYESIAN NETWORKS AND HIDDEN MARKOV MODELS. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), 8(33 ), 283-298. SID. https://sid.ir/paper/197791/en

Vancouver: Copy

ALAMATIAN ZOHREH, VAFAEI JAHAN MAJID. IRAN STOCK MARKET PREDICTION BASED ON BAYESIAN NETWORKS AND HIDDEN MARKOV MODELS. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)[Internet]. 2018;8(33 ):283-298. Available from: https://sid.ir/paper/197791/en

IEEE: Copy

ZOHREH ALAMATIAN, and MAJID VAFAEI JAHAN, “IRAN STOCK MARKET PREDICTION BASED ON BAYESIAN NETWORKS AND HIDDEN MARKOV MODELS,” FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), vol. 8, no. 33 , pp. 283–298, 2018, [Online]. Available: https://sid.ir/paper/197791/en

Related Journal Papers