Modeling the Predictors of Fake Financial News Sharing on Social Media Using Behavioral Reasoning Theory: Evidence from Retail Investors of <scp>USA</scp>

ABSTRACT The dissemination of fake news in the financial domain has surged in recent years. However, factors leading to this dissemination are less well studied. Drawing on Behavioral Reasoning Theory, this study investigates the factors influencing fake financial news sharing (FFNS) on social media, focusing on finance‐specific variables such as herd behavior, financial literacy, and investment experience. Based on survey data from a sample of U.S. retail investors ( n = 112), we employed Partial Least Squares (PLS) analysis to examine five key predictors of FFNS. The results indicate that perceived herd behavior and a sense of belonging are significant positive predictors. Although financial literacy and the act of authenticating news before sharing were hypothesized to reduce FFNS, their effects were statistically insignificant. These findings contribute to a deeper understanding of the psychological and contextual drivers of FFNS and offer practical insights for developing interventions to curb its spread.