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News and social networks of Russian companies: Degree of influence on the securities market

Author

Listed:
  • Fedorova, E.

    (Department of Corporate Finance and Corporate Governance, Financial University under the Government of the Russian Federation, Moscow, Russia)

  • Pyltsin, I.

    (NRU-HSE, Department of Economic Sciences, Moscow, Russia)

  • Kovalchuk, Yu.

    (MGIMO MFA of Russia, Moscow, Russia)

  • Drogovoz, P.

    (Bauman Moscow State Technical University, Moscow, Russia)

Abstract

The main purpose of this work is to determine the periods in which the profitability of the Russian stock market is partially explained by official information (RBC news) and unofficial (tweets of companies). The methodology of the study included a VAR model with a sliding window of 50 days. The empirical base of the study included 32 thousand news articles and 111 thousand tweets for 2011-2020. The assessment of the tonality of the text was carried out on the basis of the EcSentiThemeLex dictionary, this dictionary is one of the first dictionaries that allow assessing the tonality of economic and financial texts in Russian by five tonalities. The results of the study show that the profitability of the market is explained both by economic indicators (the price of oil and the exchange rate) and by the tone of textual information. Moreover, from 2011 to 2015, the tone of the news background was the dominant information factor in the profitability of the securities market, and in 2017-2020 - dominance has shifted to the mood of social media texts. A short-term period of influence of textual information was also revealed, sudden bursts of investor sentiment lead to a temporary jump in stock prices, which quickly return to close the initial level.

Suggested Citation

  • Fedorova, E. & Pyltsin, I. & Kovalchuk, Yu. & Drogovoz, P., 2022. "News and social networks of Russian companies: Degree of influence on the securities market," Journal of the New Economic Association, New Economic Association, vol. 53(1), pages 32-52.
    • Handle: RePEc:nea:journl:y:2022:i:53:p:32-52
    DOI: 10.31737/2221-2264-2022-53-1-2
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    text analysis; tweets; RBC news; stock market;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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