Hybrid support vector machine rule extraction method for discovering the preferences of stock market investors: Evidence from Montenegro

Ljiljana KašćelanFaculty of Economics, University of Montenegro, Jovana Tomaševica 37, 81000Podgorica, MontenegroCorrespondence[email protected]
View further author information

Vladimir KašćelanFaculty of Economics, University of Montenegro, Jovana Tomaševica 37, 81000Podgorica, MontenegroView further author information

Miomir JovanovićBiotechnical Faculty, University of Montenegro, Mihaila Lalića bb 37, 81000Podgorica, MontenegroView further author information

Citations (5)

Keep up to date with the latest research on this topic with citation updates for this article.

Read on this site (2)

Biljana Rondović, Ljiljana Kašćelan, Vujica Lazović & Tamara Đuričković. (2019) Discovering the determinants and predicting the degree of e-business diffusion using the decision tree method: evidence from Montenegro. Information Technology for Development 25:2, pages 304-333.
Read now

Vladimir Kašćelan, Ljiljana Kašćelan & Milijana Novović Burić. (2016) A nonparametric data mining approach for risk prediction in car insurance: a case study from the Montenegrin market. Economic Research-Ekonomska Istraživanja 29:1, pages 545-558.
Read now

Articles from other publishers (3)

Tamara Backović, Vesna Karadžić, Sergej Gričar & Štefan Bojnec. (2023) Montenegrin Stock Exchange Market on a Short-Term Perspective. Journal of Risk and Financial Management 16:7, pages 315.
Crossref

Suncica Rogic & Ljiljana Kascelan. 2019. New Trends in Databases and Information Systems. New Trends in Databases and Information Systems 283 294 .

Shuihua Wang, Yudong Zhang, Xiaojun Yang, Ping Sun, Zhengchao Dong, Aijun Liu & Ti-Fei Yuan. (2015) Pathological Brain Detection by a Novel Image Feature—Fractional Fourier Entropy. Entropy 17:12, pages 8278-8296.
Crossref

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Hybrid support vector machine rule extraction method for discovering the preferences of stock market investors: Evidence from Montenegro

Articles from other publishers (3)

Information for

Open access

Opportunities

Help and information

Your download is now in progress and you may close this window

Login or register to access this feature

Hybrid support vector machine rule extraction method for discovering the preferences of stock market investors: Evidence from Montenegro

Citations (5)

Read on this site (2)

Articles from other publishers (3)

Reprints and Corporate Permissions

Academic Permissions

Related research

To cite this article:

Download citation

Information for

Open access

Opportunities

Help and information

Keep up to date