Developing an Intelligent Model to Predict Stock Trend Using the Technical Analysis

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.

Afsharirad Elham; Alavi Seyed Enayatallah; SINAEI HASSANALI

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

Journal Paper

Paper Information

Journal: FINANCIAL RESEARCH Year:2018 | Volume:20 | Issue:2 Page(s): 249-264

Download Full-Text

Persian Verion

View:

2,103

Download:

Cites:

Information Journal Paper

Title

Developing an Intelligent Model to Predict Stock Trend Using the Technical Analysis

Author(s)

Afsharirad Elham | Alavi Seyed Enayatallah | SINAEI HASSANALI | Issue Writer Certificate

Keywords

Index Stock Exchange PredictionQ1

Technical AnalysisQ1

Intelligent Machine Learning MethodsQ1

Abstract

Objective: The aim of this study is to predict trend in stock using both analytical methods of stock prediction and Intelligent Machine Learning Methods on the case study of the Tehran Stock Exchange index. Methods: The proposed method consists of the following steps: at first, required data are collected. Afterwards, the data are evaluated using 25 analytical methods certified by Tehran stock exchange, Inc. Then, 10 highest rank methods are selected based on feature selection technique leading to a decrease in dimensions. Results: The output of the final step is given to five Intelligent Machine Learning Methods, i. e., linear support vector machines, Gaussian kernel support vector machines, decision trees, Naï ve Bayes and K nearest neighbors. Conclusion: Eventually, majority voting approach is used to make the final decision. The advantage of the proposed technique is the flexibility to use any Technical Analysis methods which means there is almost no limitation for this approach. Moreover, the feature selection technique is utilized for Technical Analysis and these methods are prioritized.

Cites

No record.

References

No record.

Cite

APA: Copy

Afsharirad, Elham, Alavi, Seyed Enayatallah, & SINAEI, HASSANALI. (2018). Developing an Intelligent Model to Predict Stock Trend Using the Technical Analysis. FINANCIAL RESEARCH, 20(2 ), 249-264. SID. https://sid.ir/paper/91213/en

Vancouver: Copy

Afsharirad Elham, Alavi Seyed Enayatallah, SINAEI HASSANALI. Developing an Intelligent Model to Predict Stock Trend Using the Technical Analysis. FINANCIAL RESEARCH[Internet]. 2018;20(2 ):249-264. Available from: https://sid.ir/paper/91213/en

IEEE: Copy

Elham Afsharirad, Seyed Enayatallah Alavi, and HASSANALI SINAEI, “Developing an Intelligent Model to Predict Stock Trend Using the Technical Analysis,” FINANCIAL RESEARCH, vol. 20, no. 2 , pp. 249–264, 2018, [Online]. Available: https://sid.ir/paper/91213/en

Related Journal Papers