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JACIII Vol.22 No.2 pp. 224-235
doi: 10.20965/jaciii.2018.p0224
(2018)

Paper:

Discovering Expert Traders on Social Trading Services

Woonyeol Lee and Qiang Ma

Graduate School of Informatics, Kyoto University
Yoshidahonmachi, Sakyo-ku, Kyoto 606-8501, Japan

Received:
July 10, 2017
Accepted:
January 5, 2018
Published:
March 20, 2018
Keywords:
social trading services, discovering experts, data mining, financial information systems
Abstract

Social trading services, which are financial services connected with social networking services, are currently in the spotlight. Users can follow and automatically imitate expert traders’ trades using social trading services. Finding expert traders who exhibit an exceptional and consistent performance for users to follow is a key challenge in this field. We propose a ranking mechanism with three measures to address this issue: performance, risk, and consistency. We estimated traders’ performance, risk, and consistency levels by comparatively analyzing their trading histories and news data. In addition, we propose a system called Whom to Follow (W2F) to help users discover expert traders by utilizing this ranking mechanism. W2F visualizes the ranking results, and provides feedback functions to help users reach decisions regarding who to follow. We conducted experiments to test and then validate the proposed ranking mechanism in terms of the ranking accuracy, profit, and ranking stability. We also conducted a user experiment to demonstrate the feasibility of W2F.*

* This paper is an extended version of “Whom to Follow on Social Trading Services? A System to Support Discovering Expert Traders,” 10th Int. Conf. on Digital Information Management (ICDIM) 2015, pp. 188-193.

Cite this article as:
W. Lee and Q. Ma, “Discovering Expert Traders on Social Trading Services,” J. Adv. Comput. Intell. Intell. Inform., Vol.22, No.2, pp. 224-235, 2018.
Data files:
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Last updated on Dec. 07, 2018