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Impact of non-financial information on key financial indicators of Russian companies

Author

Listed:
  • Fedorova, E.

    (Financial University under the Government of the Russian Federation, Moscow, Russia)

  • Afanasev, D.

    (JSC "Greenatom", Moscow, Russia)

  • Nersesyan, R.

    (National Research University Higher School of Economics, Moscow, Russia)

  • Ledyaeva, S.

    (Department of Economics, Aalto University School of Business, Helsinki, Finland)

Abstract

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.

Suggested Citation

  • Fedorova, E. & Afanasev, D. & Nersesyan, R. & Ledyaeva, S., 2020. "Impact of non-financial information on key financial indicators of Russian companies," Journal of the New Economic Association, New Economic Association, vol. 46(2), pages 73-96.
    • Handle: RePEc:nea:journl:y:2020:i:46:p:73-96
    DOI: 10.31737/2221-2264-2020-46-2-4
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    References listed on IDEAS

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    1. Pavel A. Mikhnenko, 2023. "Multimodal business analytics: The concept and its application prospects in economic science and practice," Upravlenets, Ural State University of Economics, vol. 14(6), pages 2-18, December.

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    More about this item

    Keywords

    latent semantic analysis; nonfinancial information; ESG; Global Reporting Initiative; corporate social responsibility; text mining;
    All these keywords.

    JEL classification:

    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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