@misc{Zeinali_Tohid_Stock_2025,
 author={Zeinali, Tohid and Fryczak, Jan Makary},
 identifier={DOI: 10.15611/fins.2025.1.03},
 year={2025},
 rights={Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy},
 description={Financial Sciences. Nauki o Finansach, 2025, vol. 30, no. 2, s. 1-13},
 publisher={Publishing House of Wroclaw University of Economics and Business},
 language={eng},
 abstract={Aim: This study examines how management reports affect stock liquidity and compares the responses of stocks with low, medium, and high liquidity. Methodology: Stocks were classified into three liquidity groups based on the median Amihud (ILLIQ) ratio. The Wilcoxon test and the Mann-Whitney U test were used to verify the result. Lastly, quantile regression was used to show the role of initial liquidity levels, especially in higher quantiles. Findings: The main findings show that management reports generally affect stock liquidity, but stocks with lower liquidity display a stronger reaction. This means that new disclosures, especially for companies that already have weaker liquidity, can create larger market fluctuations. Implications: These results are significant for investors and market regulators because they can use the insights to better manage risk and make more informed decisions. From a managerial perspective, understanding how liquidity responds to disclosures can help companies refine their communication strategies. Researchers can also apply this event-based approach to study how other types of reports or market conditions influence liquidity. Originality/value: Focusing on management reports and their impact on liquidity in a less-studied market and using both nonparametric tests and quantile regression make this research unique, helping to understand how stocks with low liquidity may show more changes after management disclosures.},
 type={artykuł},
 title={Stock Liquidity and Company Annual Reports. How Does Publishing the Annual Report Affect Stock Liquidity?},
 keywords={management reports, stock liquidity, event-based method, Wilcoxon tests, quantile regression},
}