Information asymmetry is a common phenomenon in many transactions. It occurs when one party to a transaction possesses more information than the other, leading to inefficient decision-making, unfair outcomes, and potential exploitation by opportunistic individuals. Reducing information asymmetry can enhance market efficiency, result in fairer outcomes, and influence the informational performance of companies. In today’s complex business environment, traditional models of information asymmetry appear inadequate, and models tailored to market conditions and each country’s characteristics should be developed. Therefore, the present study aims to propose a new model for measuring information asymmetry and to examine its informational consequences in the Tehran Stock Exchange. This study is applied in nature and descriptive-correlational in method. To test the research hypotheses, the regression analysis method was used. The statistical population includes all companies listed on the Tehran Stock Exchange, and through systematic elimination sampling, 166 companies were selected as the sample and examined over an eight-year period from 2017 to 2024. The model proposed in this study was developed through a detailed review of the official disclosure dates of significant information by Tehran Stock Exchange companies. To explore and analyze the informational consequences of the new model, three hypotheses were formulated. The results revealed that the Valipour information leakage model (VILM) has a direct and significant effect on the complexity of financial reporting; however, it has an inverse and significant effect on the quality of financial reporting and the informational content of companies’ accounting earnings. Further analysis indicated that the Valipour information leakage model demonstrates adequate validity and impact on various corporate factors. To confirm this, it was compared with existing models for measuring information asymmetry, and the findings showed that the new model exhibits superior effectiveness relative to the current methods.
Zaree et al. (2025) studied this question.