Влияние нефинансовой информации на основные показатели российских компаний

Translated title of the contribution: Impact of non-financial information on key financial indicators of russian companies

E. A. Fedorova, D. O. Afanasev, R. Nersesyan, Svetlana Ledyaeva

Research output: Contribution to journalArticleScientificpeer-review


This study examines the relation between non-financial information and companies’ financial results, especially stock returns and weighted average cost of capital (WACC) in the Russian Federation. It selected a sample as a source of nonfinancial information containing Annual reports, Sustainable development reports, ESG reports (environmental, social, governance) and Global Reporting Initiative (GRI) reports of public firms listed in the Russian stock market (MOEX) from 2010 to 2018. To evaluate the role of information disclosure there were applied Bloomberg ESG disclosure indexes. The methodology of text analysis was based on latent semantic analysis (LSA) technique. Latent semantic analysis is a method of textual associative patterns recognition and themes of text formalization with rich mathematical background. Besides, we applied classical text mining procedure — bag of words with corporate social performance dictionary. The results demonstrate both significant influence of some themes or information disclosure importance for stakeholders and independent market agents. Firstly, this study serves top-management purposes and expands understanding of non-financial information influence. Second, the results may be used by external agents to detect the core idea vanishing in text massive.

Translated title of the contributionImpact of non-financial information on key financial indicators of russian companies
Original languageRussian
Pages (from-to)73-96
Number of pages24
JournalZhournal Novoi Ekonomicheskoi Associacii
Issue number2
Publication statusPublished - 2020
MoE publication typeA1 Journal article-refereed


  • Corporate social responsibility
  • ESG
  • Global reporting initiative
  • Latent semantic analysis
  • Nonfinancial information
  • Text mining


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