PREDICT THE RISK OF FALLING STOCK PRICES BY USING META-INNOVATIVE METHODS (CUMULATIVE PARTICLE MOTION OPTIMIZATION ALGORITHM) AND COMPARISON WITH LOGISTIC REGRESSION

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.

MALEKIAN ESFANDIAR; FAKHARI HOSSEIN; GHASEMI JAMAL; FARZAD SARVEH

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:9 | Issue:36 Page(s): 225-250

Download Full-Text

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

Persian Verion

View:

808

Download:

Cites:

Information Journal Paper

Title

PREDICT THE RISK OF FALLING STOCK PRICES BY USING META-INNOVATIVE METHODS (CUMULATIVE PARTICLE MOTION OPTIMIZATION ALGORITHM) AND COMPARISON WITH LOGISTIC REGRESSION

Author(s)

MALEKIAN ESFANDIAR | FAKHARI HOSSEIN | GHASEMI JAMAL | FARZAD SARVEH | Issue Writer Certificate

Keywords

CUMULATIVE MOTION ALGORITHM OF PARTICLESQ1

GENETIC ALGORITHMQ2

ARTIFICIAL NEURAL NETWORKQ2

STOCK PRICE RISKQ1

Abstract

The Crash, which indicates how much specific stock prices are at risk of collapse. Accordingly, the purpose of this research is to model the risk of falling stock price of listed companies in Tehran Stock Exchange using a multivariate optimization algorithm for particle cumulative movement and comparing results with logistic regression. For this purpose, a hypothesis was developed for the study of this issue and the data for 106 members of the Tehran Stock Exchange for the period of 2010-2010 were analyzed. First, 14 independent variables were introduced as inputs of the combined GENETIC ALGORITHM and ARTIFICIAL NEURAL NETWORK, which was considered as a feature selection method, and 7 optimal variables were selected. Then, using particle cumulative algorithm and logistic regression, predicted The risk of falling stock prices. The stock price collapse criterion has been used to calculate the risk of falling stock prices. The research findings show that the particle agglomeration algorithm is more likely than traditional logistic regression to predict the risk of falling stock prices. These findings underscore the need for managers to use meta-metric methods for forecasting.

Cites

No record.

References

No record.

Cite

APA: Copy

MALEKIAN, ESFANDIAR, FAKHARI, HOSSEIN, GHASEMI, JAMAL, & FARZAD, SARVEH. (2018). PREDICT THE RISK OF FALLING STOCK PRICES BY USING META-INNOVATIVE METHODS (CUMULATIVE PARTICLE MOTION OPTIMIZATION ALGORITHM) AND COMPARISON WITH LOGISTIC REGRESSION. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), 9(36 ), 225-250. SID. https://sid.ir/paper/197536/en

Vancouver: Copy

MALEKIAN ESFANDIAR, FAKHARI HOSSEIN, GHASEMI JAMAL, FARZAD SARVEH. PREDICT THE RISK OF FALLING STOCK PRICES BY USING META-INNOVATIVE METHODS (CUMULATIVE PARTICLE MOTION OPTIMIZATION ALGORITHM) AND COMPARISON WITH LOGISTIC REGRESSION. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)[Internet]. 2018;9(36 ):225-250. Available from: https://sid.ir/paper/197536/en

IEEE: Copy

ESFANDIAR MALEKIAN, HOSSEIN FAKHARI, JAMAL GHASEMI, and SARVEH FARZAD, “PREDICT THE RISK OF FALLING STOCK PRICES BY USING META-INNOVATIVE METHODS (CUMULATIVE PARTICLE MOTION OPTIMIZATION ALGORITHM) AND COMPARISON WITH LOGISTIC REGRESSION,” FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), vol. 9, no. 36 , pp. 225–250, 2018, [Online]. Available: https://sid.ir/paper/197536/en

Related Journal Papers