The Application of Rough Set Theory in Stock Price Forecasting (Case Study: Iran Saderat Bank)

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.

SARANJ ALIREZA; KARIMI TOORAJ; Shahrami Babakan Majid

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

Journal Paper

Paper Information

Journal: JOURNAL OF FINANCIAL MANAGEMENT STRATEGY Year:2017 | Volume:5 | Issue:3 (18) Page(s): 119-144

Download Full-Text

Persian Verion

View:

765

Download:

Cites:

Information Journal Paper

Title

The Application of Rough Set Theory in Stock Price Forecasting (Case Study: Iran Saderat Bank)

Author(s)

SARANJ ALIREZA | KARIMI TOORAJ | Shahrami Babakan Majid | Issue Writer Certificate

Keywords

Stock price forecastingQ1

Rough set theoryQ2

Conditional and Decision AttributesQ2

Data DiscretizationQ2

Rules ExtractionQ2

Abstract

This paper proposes a method based on Rough set theory and by using technical indicators to predict the stock price. Rough set theory has several advantages; the most important advantage is that no additional information is needed about the initial data. In the proposed model, a number of technical indicators from the data of Bank Saderat Iran during a year were calculated and used as condition attributes in the decision table and the stock price fluctuation on the next day was selected as decision attribute. It should be noted that by using the correlation matrix analysis, the variables with the highest correlation with decision attribute were selected as conditional attributes. Using Rough set theory and different discretization and reduction methods, some rules are extracted based on learning data and methods validity were computed based on control data. Comparing the return of this method and buy and hold method reveals the superiority of proposed model. Also, using data from different years with different price trends as inputs to the model and achieving satisfactory results is a promising reason for using and developing this method in Stock price forecasting.

Cites

No record.

References

No record.

Cite

APA: Copy

SARANJ, ALIREZA, KARIMI, TOORAJ, & Shahrami Babakan, Majid. (2017). The Application of Rough Set Theory in Stock Price Forecasting (Case Study: Iran Saderat Bank). JOURNAL OF FINANCIAL MANAGEMENT STRATEGY, 5(3 (18) ), 119-144. SID. https://sid.ir/paper/261662/en

Vancouver: Copy

SARANJ ALIREZA, KARIMI TOORAJ, Shahrami Babakan Majid. The Application of Rough Set Theory in Stock Price Forecasting (Case Study: Iran Saderat Bank). JOURNAL OF FINANCIAL MANAGEMENT STRATEGY[Internet]. 2017;5(3 (18) ):119-144. Available from: https://sid.ir/paper/261662/en

IEEE: Copy

ALIREZA SARANJ, TOORAJ KARIMI, and Majid Shahrami Babakan, “The Application of Rough Set Theory in Stock Price Forecasting (Case Study: Iran Saderat Bank),” JOURNAL OF FINANCIAL MANAGEMENT STRATEGY, vol. 5, no. 3 (18) , pp. 119–144, 2017, [Online]. Available: https://sid.ir/paper/261662/en

Related Journal Papers