Volume 19, Issue 3 (9-2024)
J. Mon. Ec. 2024, 19(3): 361-393 |
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Ahadzadeh M, Vakilifard H R, Talebnia G. A Five-Minute Interval Analysis of High-Frequency Volatility under Information Asymmetry: Empirical Evidence from Tehran Stock Exchange. J. Mon. Ec. 2024; 19 (3) : 4
URL: http://jme.mbri.ac.ir/article-1-687-en.html
URL: http://jme.mbri.ac.ir/article-1-687-en.html
1- MSc of Financial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
2- Associate Professor, Department of Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran
2- Associate Professor, Department of Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran
Abstract: (1802 Views)
The modeling and forecasting of yield volatility in the Stock Market have become increasingly critical due to their pivotal role in key applications such as Value at Risk (VaR) assessment, optimal resource allocation in investment portfolios, effective investment management, and accurate pricing of derivatives. Among the key drivers of yield volatility, information asymmetry between market participants has emerged as a significant factor influencing market dynamics. Despite its importance, the empirical exploration of this phenomenon in emerging markets, particularly the Tehran Stock Exchange (TSE), remains scarce. This study examines the impact of information asymmetry on the volatility of the TSE's total index, employing the advanced Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity (FIGARCH) framework. Intraday trading data from 2023 to 2024, collected at five-minute intervals, form the basis of this analysis. Information asymmetry was quantified via the transaction volume-weighted price impact metric. The Akaike Information Criterion (AIC) and Schwarz Bayesian Criterion (SBC) determined the optimal model specification, leading to the application of FIGARCH, with exogenous information asymmetry incorporated into the GARCH (1,1) baseline model. Empirical results underscore a positive and statistically significant relationship between information asymmetry and return volatility in the TSE. These findings have profound implications for enhancing market efficiency, risk management, and derivative pricing strategies in emerging stock markets.
Article number: 4
Keywords: Information Asymmetry, Return Volatility, Total index, Conditional Heterogeneity, GARCH, FIGARCH
Type of Study: Original Research - Empirical |
Subject:
Economics
Received: 29 Mar 2025 | Accepted: 1 Jun 2025 | Published: 1 Jul 2025
Received: 29 Mar 2025 | Accepted: 1 Jun 2025 | Published: 1 Jul 2025
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