Analyzing the Time-Varying Characteristics of Information Flow Networks among Main Industries Indices in the Tehran Stock Exchange

The information diffusion and interactions within financial markets have a significant impact on the price discovery process and the sentiment and risk dispersion. Despite its importance, limited research has been conducted on information flow dynamics within the Tehran Stock Exchange, which is a vital component of Iran's capital market. This study aims to fill this gap by examining the information flow dynamics among 39 major industries from March 27, 2010, to June 21, 2023. Effective transfer entropy is employed to quantify the intensity of information flow between industry indices. Sequence of information matrices are constructed using rolling one-week windows over one-year periods. Given the occurrence of critical events during the research period, their influence on information flow dynamics is analyzed using Frobenius distance-based k-nearest neighbor networks, Influence Strength analysis, and threshold networks. The findings reveal that the effective transfer entropy matrix exhibits time-varying characteristics and remains stable throughout most periods. Furthermore, critical events significantly impact information flow dynamics, with abnormal values of Influence Strength associated with market volatility and major events. Additionally, the dominant source of information in the information flow network changes over time, highlighting the transient nature of industry dominance within the network.