Behavioral Biases and Trust in Social Trading: A Mixed-Method Approach

Abstract

This research was conducted to extend the study of social trading using the behavioral finance perspective, the role of trust and a mixed-method approach from followers on social trading platforms. This research uses a mixed-method approach. In the first stage, semi-structured interviews were conducted with 11 follower traders by snowball sampling to find out the factors that influence traders' investment and trading behavior through social trading platforms.  The second stage will quantitatively test the model using SmartPLS with 342 follower traders. Respondents in the second stage are followers of traders with real accounts on social trading platforms. Data was collected by accidental sampling using an online questionnaire distributed through forums and trader communities.  The behavioral finance perspective is the basis of this research because empirical psychology can provide a good explanation when people are faced with uncertainty, which in this case is the uncertainty of trading results. Until now, research on social trading has mostly discussed about behavioral biases from the perspective of top leaders, not followers. Why people trust and mimic the behavior of traders through social trading platforms is an interesting question. Trust plays a vital role in the world of finance and technology, but very little research has addressed the role of trust in social trading. This research closes that gap by discussing the role of trust in social trading from a behavioral finance perspective. The results of this study conclude that Optimism, Herding, Stereotype bias, Confirmation bias, and Hot hand fallacy have a positive effect on trading decisions. Trust in trader leaders also strengthens the influence of optimism and stereotype bias on trading decisions.