Information Disclosure and Company Performance: Analysis of Non-Financial Reports of Russian Companies

This study explores the relationship between non-financial information disclosure and financial performance of Russian companies against the backdrop of growing demands for transparency and sustainability. Text analysis based on the ruBERT machine learning model is applied to the non-financial reports of 266 Russian companies, comprising a total of 1506 reports. The main objective is to identify correlations between disclosure practices and financial fundamentals, in particular return on assets (ROA) and return on equity (ROE). The analysis revealed a negative relationship between the proportion of sentences associated with each ESG factor in a non-financial report and the financial performance of Russian companies as measured by ROA and ROE. In addition, the construction of models with industry and year fixed effects proved to be unjustified as it led to a decrease in the significance of the coefficients. Thus, the choice of simpler models without these fixed effects may be more appropriate to capture the relationship between non-financial disclosure and financial performance of Russian companies. By elucidating these relationships, our study contributes to a better understanding of how disclosure practices affect corporate performance in the Russian context, thereby informing strategic decision making and investment practices.