A social investing approach for portfolio recommendation

Presently, people use social media at a greater rate to share their personal investment experiences. This plentiful user-generated data source has been promisingly used by investors for portfolio creation. A new type of investing platform that allows investors to copy the portfolios of experienced investors has grown dramatically. In this research, we propose a collective intelligence mechanism that can extract and consolidate the opinions expressed over the social investing platform and generate appropriate portfolios by analyzing other investors’ knowledge, authority, and opinions toward the investment target. The experimental results obtained based on the social investing platform eToro.com reveal that the portfolio recommended by the proposed mechanism outperforms the market index and other benchmark approaches in various financial performance aspects.