Evaluation of Systematic Risk of Assets Using a News Analysis Approach in the Tehran Stock Exchange
Keywords:
Systematic risk, news analysis, news sense, artificial intelligence, Tehran Stock ExchangeAbstract
Systematic risk plays a critical role in the assessment and management of financial assets and is increasingly influenced by information flow and investor behavior, both of which must be properly identified. Accordingly, this study, with a focus on the Tehran Stock Exchange, sought—for the first time in Iran—to examine the effect of sentiment conveyed through news on the variations in realized beta coefficients of companies. The approach of this research is applied and mixed-method (quantitative and qualitative), and the data were collected from a purposive sample of 74 companies across 10 stock market industries during the years 2020 to 2023. Key variables were extracted from daily news using artificial intelligence technologies and natural language processing methods, and the analysis was performed using a dynamic panel econometric model with fixed effects. The results revealed that positive sentiment derived from news significantly reduces the systematic risk of companies on the day the news is released; whereas news silence and high tonal similarity between company-specific news and general market news increase systematic risk. Additionally, daily trading volume—as an indicator of liquidity—was found to have a decreasing effect on beta. Therefore, systematic risk is not only influenced by economic factors but is also strongly dependent on the quality and tone of disseminated information. These findings offer novel insights into the dynamics of systematic risk in Iran’s capital market based on informational and behavioral factors.
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Copyright (c) 2025 Zohreh Memarpour, Gholamreza Askarzadeh Dareh, Hamid Khajeh Mahmoudabadi, Seyyed Yahya Abtahi (Author)
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