Exploring the relationship between bank liquidity risk and the media sentiment index via big data technology: a study during the COVID-19 pandemic and the Russia–Ukraine conflict
Year: 2026
Type: article
Abstract: This study assesses the influence of media sentiment on liquidity risk during financial crises within the context of the Russian financial market. Trade sanctions, especially the suspension of the SWIFT network, have profoundly impacted Russian banking sector liquidity. Given this vulnerable situation, the study utilizes media sentiment data to analyze banking sector performance via monthly data from January 2012 to December 2024. This study applies big data modeling techniques to construct positive, negative, and mixed media sentiment indices to evaluate their relationship with bank liquidity risk. The findings, which are based on GMM estimation, reveal that the media sentiment index is significantly and positively associated with bank liquidity risk. Moreover, negative and mixed media sentiment indices have a detrimental effect on bank performance, leading to an appreciation of liquidity risk. Additionally, the study finds that interbank networks play a vital role in mitigating liquidity risk. Overall, media sentiment significantly impacts banking performance. The findings provide practical implications for banking sector policymakers, financial market regulators, and investors in making informed decisions during both normal and crisis periods.
Source: Financial Innovation
Authors: Mirzat Ullah, Kazi Sohag, M. Kabir Hassan
Institutions: Ural Federal University, St Petersburg University, LSU New Orleans
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: diamond
Funder: Russian Science Foundation
Awards: G1369148522, G4989015463
OpenAlex ID: W7128040702