Iranian Journal of Finance

Abstract Iran’s capital market has witnessed substantial transformation over recent decades. However, the sharp downturn of the stock market in 2020 represented a critical juncture, extending beyond retail investors’ financial losses and culminating in a widespread public trust crisis. Addressing this issue, the present study proposes a neurofinance-based model aimed at strengthening public investor trust in Iran’s capital market. The model was developed through a mixed-methods design, integrating qualitative grounded theory exploration with quantitative validation via structural equation modeling (SEM). In the qualitative phase, data were collected in 2025 through semi-structured interviews with 17 capital market experts and analyzed using a three-stage coding procedure comprising: open, axial, and selective coding. In the quantitative phase, the proposed theoretical model was empirically tested using SEM on data obtained from 87 investors in the capital market. The qualitative findings reveal that the development of trust is shaped by causal conditions (e.g., information transparency and emotional responses), contextual conditions (e.g., economic stability and social capital), and intervening conditions (e.g., media, education, and supportive institutions). The quantitative results confirm that all model paths are statistically significant and that the model demonstrates an acceptable level of fit. Accordingly, strategies such as enhancing transparency, empowering retail investors, and promoting financial literacy were proposed, generating outcomes at the individual, market, and macro levels. The novelty of this research lies in integrating a neurofinance perspective with a mixed-methods approach to develop a context-specific model aligned with Iran’s institutional and cultural environment.