This study examines the reaction of the Russian stock market to the publication of news about companies in the metals and mining segment of the Moscow stock exchange. The article describes the methodology used to collect and analyze a database of news reports, including a modified cumulative abnormal return (CAR) method to register abnormal returns related to news publications. The study also explores the search for parameters such as the beginning, end, duration, and profitability of news using algorithms based on the CAR and normalized abnormal volume (NAV) methods. The results of this analysis are presented in the form of calculated parameters for the beginning, end, duration of the reaction, and CAR, categorized by stock prices and trading volumes.Next, the results obtained from each method are compared. The rationale for the differences in parameter estimates is discussed, as well as the application of these results to improve IR management in companies.