Herding and loss aversion in stock markets: mediating role of fear of missing out (FOMO) in retail investors

Purpose The study aims to understand the impact of loss aversion and herding on investment decision of retail investors. The study further evaluates the mediating role of fear of missing out (FOMO) in retail investors on these relationships. Design/methodology/approach The study employed questionnaire survey to collect data from retail investors of Indian stock market. Total 323 data were collected. The collected data were examined using SmartPLS. Factor analysis and partial least square structural equation modeling were employed for fulfilling the objectives of the study. Findings The results of the study revealed that investment decisions of retail investors are significantly influenced by loss aversion, herd behavior as well as FOMO. Assessing the impact of herd behavior and loss aversion on investment decision in presence and absence of FOMO exposed that FOMO partially mediates these relations. The mediation was complementary in nature as the presence of FOMO increased the influence of loss aversion and herd behavior on retail investor's investment decisions. Practical implications Behavioral predispositions are accountable for numerous irregularities in stock markets. Thus, it is quite substantial to realize the stimulus of these partialities on investment decisions. The outcomes of this study would help financial planners and investors to keep in mind the different ways their decision outcomes could be biased and try to ignore them. Originality/value Though there have been many studies conducted on behavioral biases and their impact on investment decisions, there are very few studies that have taken into account the FOMO factor in investment, in context of the behavioral biases. Theoretically, FOMO has been linked with herd behavior and greed of earning more, but there are very few empirical supports to this fact. Thus, this study is an attempt to fill this gap by examining the role of FOMO on investment decisions and the different biases associated with it.