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The Impact of News on the MICEX Oil & Gas Index: Textual Analysis

https://doi.org/10.38050/01300105201845

Abstract

In this study, a relationship between the mood of news and the response of the oil and gas industry index of the Russian Federation was revealed. The empirical base of the study included 8.5 million news from foreign sources. Research methodology: fuzzy sets, naive Bayesian classifier, Pearson correlation coefficient. As a result of the research, it was discovered that: 1) negative news affects the stronger than the positive on the stock index; 2) news on companies affect the value of the index, and news on the industry affect the volume of trading; 3) the sanctions did not significantly affect the coverage of Russian oil and gas companies.

About the Authors

E. A. Fedorova
Financial University under the government of the Russian Federation; National Research University "Higher school of Economics"
Russian Federation


O. Yu. Rogov
Financial University under the Government of the Russian Federation
Russian Federation


V. A. Klyuchnikov
National Research University "Higher school of Economics"
Russian Federation


References

1. Федорова Е. А., Федоров Ф. Ю., Толкачев А. В. Взаимосвязь новостного фона и притока прямых иностранных инвестиций в регионы России // Пространственная экономика. - 2016. - № 4-5 (48). - С. 75-92.

2. Ankudinov A., Ibragimov R., Lebedev O. Sanctions and the Russian stock market // Research in International Business and Finance. - 2017. - Vol. 40. - P. 150-162.

3. Bodnaruk A., Loughran T., McDonald B. Using 10-K Text to Gauge Financial Constraints // Journal of Financial and Quantitative Analysis. - 2015. - 50:4.

4. Chau F. еt al. Political uncertainty and stock market volatility in the Middle East and North African (MENA)countries // Int. Fin. Markets, Inst. and Money. - 2014. - Vol. 28. - P. 1- 19.

5. Checkley M. S., Añón Higón D., Alles H. The Hasty Wisdom of the Mob: How Market Sentiment Predicts Stock Market Behavior // Expert Systems with Applications. - 2017. - Vol. 77.

6. Coulter A. Slander: Liberal lies about the American right. - N.Y.: Crown Publishers, 2002.

7. Gilbert E., Karahalios K. Widespread worry and the stock market // Proceedings of the 4th International AAAI Conference on Weblogs and Social Media, 2010. - P. 1-8.

8. Goldberg B. Bias: A CBS insider exposes how the media distort the news. - Washington, DC: Regnery Publishing, 2001.

9. Heston Steven L. and Nitish R. Sinha. News versus Sentiment: Predicting Stock Returns from News Stories // Finance and Economics Discussion Series. - 2016. - P. 1-35.

10. Jones K. S. A statistical interpretation of term specificity and its application in retrieval // Journal of Documentation. - Vol. 60. - No. 5. - P. 493-502.

11. Kearney C., Liu S. Textual sentiment in finance: A survey of methods and models // International Review of Financial Analysis. - 2014. - Vol. 33.

12. Lehkonen H., Heimonen K. Democracy, political risks and stock market performance // Journal of International Money and Finance. - 2015. - No. 59. - P. 77-99.

13. Lott J. R., Hassett K. A. Is Newspaper Coverage of Economic Events Politically Biased? // SSRN Electronic Journal. - 2012.

14. Loughran T., McDonald B. When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks // Journal of Finance. - 2011. - No. 66:1. - P. 35-65.

15. Loutia A., Mellios C., Andriosopoulos K. Do OPEC Announcements Influence Oil Prices? // Energy Policy. - 2016. - No. 90. - P. 262-272.

16. Moat H. S., Curme C., Avakian A., Kenett D. Y., Stanley H. E., Preis T. Quantifying Wikipedia Usage Patterns Before Stock Market Moves // Scientific Reports. - 2013. - 3.1.

17. Oliveira N., Cortez P., Areal N. On the predictability of stock market behavior using stock with sentiment and posting volume // Progress in Artificial Intelligence: Lecture Notes in Computer Science. - 2013. - 8154. - P. 355-365.

18. Porshnev A., Lakshina V., Redkin I. Could Emotional Markers in Twitter Posts Add Information to the Stock Market ARMAX-GARCH Model // Higher School of Economics Research Paper No. WP BRP 54/FE/2016.

19. Qing L., Wang T., Li P., Liu L., Gong Q., Chen Y. The Effect of News and Public Mood on Stock Movements // Information Sciences. -2014. - No. 278. - P. 826-840.

20. Tetlock P. C. Giving content to investor sentiment: the role of media in the stock market // J. Finance. - 2007. - No. 62. - P. 1139-1168.

21. Trabelsi Mnif A. Political uncertainty and behavior of Tunisian stock marketcycles: Structural unobserved components time series models // Research in International Business and Finance. - 2017. - No. 39. - P. 206-214.

22. Veronesi P. Stock market overreactions to bad news in good times: a rational expectations equilibrium model // Rev. Finance. Stud. -1999. - 12 975.


Review

For citations:


Fedorova E.A., Rogov O.Yu., Klyuchnikov V.A. The Impact of News on the MICEX Oil & Gas Index: Textual Analysis. Moscow University Economics Bulletin. 2018;(4):79-99. (In Russ.) https://doi.org/10.38050/01300105201845

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ISSN 0130-0105 (Print)