Artificial Counselor System for Stock Investment

Hadi NekoeiQachkanloo, Benyamin Ghojogh, Ali Saheb Pasand and Mark Crowley

Papers from arXiv.org

Abstract: This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment. In this paper, the stock future prices (technical features) are predicted using Support Vector Regression. Thereafter, the predicted prices are used to recommend which portions of the budget an investor should invest in different existing stocks to have an optimum expected profit considering their level of risk tolerance. Two different methods are used for suggesting best portions, which are Markowitz portfolio theory and fuzzy investment counselor. The first approach is an optimization-based method which considers merely technical features, while the second approach is based on Fuzzy Logic taking into account both technical and fundamental features of the stock market. The experimental results on New York Stock Exchange (NYSE) show the effectiveness of the proposed system.

Date: 2019-03
New Economics Papers: this item is included in nep-cmp and nep-fmk
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, no. 01, pp. 9558-9564, 2019

Downloads: (external link)
http://arxiv.org/pdf/1903.00955 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1903.00955

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().