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.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
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