The Impact of Disclosure Sentiment on the Share Prices of Russian Companies

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Abstract

Information about companies published in a news feed is invariably tinted by emotional tonality. As such, resulting perceptions may influence the opinion of market players, and consequently affect the dynamics of a company’s share price. This study aims to evaluate various hypotheses about the impact of the tone of news items regarding dividends, capital expenditures, and development on the stock prices of Russian companies. Information disclosure is extensively studied, and there have been limited studies on the effect of disclosures on Russian companies. However, until now, there have been no research studies which verify hypotheses on the influence of news sentiment on corporate share prices in the Russian market. This analysis was conducted using data from 49 Russian public companies included in the Moscow exchange index over the period from the end of 2017 to the beginning of 2019. To account for the proximate impact of news items on consequential market phenomena, an event study methodology was applied in order to estimate and construct the models of dependency of cumulative abnormal return (CAR) on news tone level, and control for financial and nonfinancial factors. Our results provide evidence for the positive impact of the tone of news texts on the share prices of Russian companies. The increase in news tone by one standard deviation leads to a cumulative abnormal stock return increase of 0.26 percentage points. This result is consistent with previous research conducted on data from developed stock markets. Moreover, the relationship between the tone or sentiment level of a news item and the stock price reaction is linear, without the diminishing marginal effect. Our conclusions should prompt companies to invest effort in delivering information in a tonally positive way, highlighting the most positive news. Investors, in turn, should rationally approach the interpretation of published information.

About the authors

M. Kopyrin

Author for correspondence.
Email: kopyrin.mak@yandex.ru

I. Naidenova

Email: yunaydenova@hse.ru

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