Decoding market instability: The interplay of attention deficits, internal information risks, and investor sentiment in shaping sustainable investments in Iran’s energy and technology sectors

This study investigates the interplay between investor attention deficits, internal information risks, and sentiment in driving market volatility and hindering sustainable investments in Iran’s energy and technology sectors. Drawing on behavioral finance and sustainable finance theories, we address a critical gap in emerging market literature by examining how cognitive biases and informational asymmetries amplify instability in the Tehran Stock Exchange (TSE). Employing a mixed-methods design, we analyze historical TSE data (2015–2023), conduct semi-structured interviews with 30 investors and project managers, and apply advanced models including dynamic panel regression, GARCH, structural equation modeling, and deep neural networks (DNNs). Findings reveal that attention deficits significantly heighten volatility, with an Attention Deficit Index exhibiting strong positive correlations to short- and long-term fluctuations. Internal risks, such as incomplete disclosures and managerial turnover, double the odds of market inefficiency. Investor sentiment mediates 48% of attention deficits’ effects on volatility, while DNNs (89% accuracy) uncover nonlinear interactions between biases and risks. Results demonstrate that behavioral inefficiencies outweigh macroeconomic drivers (e.g., exchange rates, oil prices) in fostering instability, underscoring the need for enhanced transparency and education. This research offers novel insights for policymakers to bolster sustainable transitions aligned with SDGs, extending behavioral models to sanctioned economies.