IDEAS home Printed from https://ideas.repec.org/a/scn/financ/y2018i4p104-113.html
   My bibliography  Save this article

Влияние Тональности Новостей На Курс Биткоина // The Influence Of The Tonality Of News On The Exchange Rate Of Bitcoin

Author

Listed:
  • E. Fedorova A.

    (Financial University)

  • K. Bechvaya Z.

    (Financial University)

  • O. Rogov Yu.

    (State Research Institute of Aviation Systems)

  • Е. Федорова А.

    (Финансовый университет)

  • К. Бечвая З.

    (Финансовый университет)

  • О. Рогов Ю.

    (Государственный научно-исследовательский институт авиационных систем)

Abstract

The authors assess the impact of the emotional tonality of bitcoin news on its exchange rate. In particular, we studied the hypothesis of the impact of the readability index of the news text on the volatility of bitcoin. Despite the fact that excessive volatility threatens bitcoin not to become a successful currency, many scientists are interested in the determinants of such volatility. Factors such as speculative investments or the attention of the society are the drivers of the volatility of the exchange rate of bitcoin. In this regard, the question of studying the impact of news on the bitcoin exchange rate is relevant. The purpose of this paper is to assess the impact of the emotional tonality of bitcoin news on its exchange rate. The empirical base of the study was quite extensive since it includes more than 1330 news from the Thomson Reuters information base for the period from 19.08.2011 to 16.08.2016 on the bitcoin market. The research methodology includes the sentiment analysis conducted by using the dictionary MacDonald and Loughran and also the analysis of the interdependence of time series-based causal analysis using the test of Granger causation. We present three hypotheses about the impact of news on the bitcoin exchange rate. During the study, two of them were confirmed. We proved the first hypothesis that the negative news had a more significant impact than positive ones, taking into account the five time-lags. The second hypothesis about the impact of positive tonality in the news on the bitcoin exchange rate, using the Granger test for causation, was not confirmed, since the positive values of this test were obtained in two time-lags out of five. We can confirm that the third hypothesis was proved — the high readability index has an impact on the bitcoin volatility for the entire studied period, taking into account all five time-lags. Thus, the assumption about the impact of the emotional tonality of news on the bitcoin exchange rate can be confirmed. Оценивается влияние эмоциональной тональности новостей о биткоине на его курс. В частности, исследуется, влияет ли индекс читабельности текста новостей на волатильность биткоина. Несмотря на то что чрезмерная волатильность угрожает биткоину не стать успешной валютой, многие ученые заинтересованы в детерминантах такой волатильности. Такие факторы, как спекулятивные инвестиции или внимание общества, являются драйверами изменчивости курса биткоина. В связи с этим вопрос исследования влияния новостей на курс биткоина является актуальным. Цель данной работы состоит в том, чтобы оценить влияние эмоциональной тональности новостей о биткойне на его курс. Эмпирическая база исследования довольно объемная, поскольку включает в себя более 1330 новостей из информационной базы Thomson Reuters за период с 19.08.2011 по 16.08.2016 г. по рынку биткоина. Методология исследования включает анализ тональности, проведенный с использованием словаря МакДональда и Лоугрэна, также проведен анализ взаимозависимости временных рядов на основе каузального анализа с применением теста Грэнджера на причинность.В статье поставлены три гипотезы о влиянии новостей на курс биткоина. В ходе исследования получили подтверждение две из них. Доказана первая гипотеза о более значительном влиянии негативных новостей, чем позитивных с учетом пяти лагов. Вторая гипотеза о влиянии положительной тональности в новостях на курс в результате применения теста Грэнджера на причинность не подтвердилась, поскольку положительные значения данного теста были получены в двух лагах из пяти. Также была доказана третья гипотеза о том, что высокий индекс читабельности оказывает влияние на волатильность биткоина за весь изученный период с учетом всех пяти лагов. Таким образом, предположение о влиянии эмоционального освещения новостей на курс биткоина подтвердилось.

Suggested Citation

  • E. Fedorova A. & K. Bechvaya Z. & O. Rogov Yu. & Е. Федорова А. & К. Бечвая З. & О. Рогов Ю., 2018. "Влияние Тональности Новостей На Курс Биткоина // The Influence Of The Tonality Of News On The Exchange Rate Of Bitcoin," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(4), pages 104-113.
    • Handle: RePEc:scn:financ:y:2018:i:4:p:104-113
    as

    Download full text from publisher

    File URL: https://financetp.fa.ru/jour/article/viewFile/737/506.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Anton Badev & Matthew Chen, 2014. "Bitcoin: Technical Background and Data Analysis," Finance and Economics Discussion Series 2014-104, Board of Governors of the Federal Reserve System (U.S.).
    2. Luther, William J. & Salter, Alexander W., 2017. "Bitcoin and the bailout," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 50-56.
    3. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The digital agenda of virtual currencies: Can BitCoin become a global currency?," Information Systems and e-Business Management, Springer, vol. 14(4), pages 883-919, November.
    4. Pieters, Gina & Vivanco, Sofia, 2017. "Financial regulations and price inconsistencies across Bitcoin markets," Information Economics and Policy, Elsevier, vol. 39(C), pages 1-14.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bouri, Elie & Gupta, Rangan & Lau, Chi Keung Marco & Roubaud, David & Wang, Shixuan, 2018. "Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 297-307.
    2. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    3. Saggese, Pietro & Belmonte, Alessandro & Dimitri, Nicola & Facchini, Angelo & Böhme, Rainer, 2023. "Arbitrageurs in the Bitcoin ecosystem: Evidence from user-level trading patterns in the Mt. Gox exchange platform," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 251-270.
    4. Obryan Poyser, 2017. "Exploring the determinants of Bitcoin's price: an application of Bayesian Structural Time Series," Papers 1706.01437, arXiv.org.
    5. Oh, Jeong Hun, 2018. "The Foreign Exchange Market With the Cryptocurrency and "Kimchi Premium"," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society 190386, International Telecommunications Society (ITS).
    6. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2016. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. I," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 44, pages 5-24.
    7. Ji, Qiang & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2018. "Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 203-213.
    8. Matkovskyy, Roman, 2019. "Centralized and decentralized bitcoin markets: Euro vs USD vs GBP," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 270-279.
    9. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    10. Jaroslav Bukovina & Matus Marticek, 2016. "Sentiment and Bitcoin Volatility," MENDELU Working Papers in Business and Economics 2016-58, Mendel University in Brno, Faculty of Business and Economics.
    11. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    12. García-Monleón, Fernando & Danvila-del-Valle, Ignacio & Lara, Francisco J., 2021. "Intrinsic value in crypto currencies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    13. Cheng, Jiameng & Dai, Yanke, 2020. "Is bitcoin a channel of capital inflow? Evidence from carry trade activity," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 261-278.
    14. Julia Reynolds & Leopold Sögner & Martin Wagner, 2021. "Deviations from Triangular Arbitrage Parity in Foreign Exchange and Bitcoin Markets," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(2), pages 105-146, June.
    15. Christie Smith & Aaron Kumar, 2018. "Crypto‐Currencies – An Introduction To Not‐So‐Funny Moneys," Journal of Economic Surveys, Wiley Blackwell, vol. 32(5), pages 1531-1559, December.
    16. Anna Iwona Piotrowska & Dariusz Piotrowski, 2017. "Barriers to the functioning of the bitcoin system ? user assessment," Proceedings of Economics and Finance Conferences 4807736, International Institute of Social and Economic Sciences.
    17. Hau, Liya & Zhu, Huiming & Shahbaz, Muhammad & Sun, Wuqin, 2021. "Does transaction activity predict Bitcoin returns? Evidence from quantile-on-quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    18. Pieters, Gina & Vivanco, Sofia, 2017. "Financial regulations and price inconsistencies across Bitcoin markets," Information Economics and Policy, Elsevier, vol. 39(C), pages 1-14.
    19. Bouri, Elie & Gupta, Rangan & Lahiani, Amine & Shahbaz, Muhammad, 2018. "Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate commodity and gold prices," Resources Policy, Elsevier, vol. 57(C), pages 224-235.
    20. George Milunovich, 2018. "Cryptocurrencies, Mainstream Asset Classes and Risk Factors: A Study of Connectedness," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 51(4), pages 551-563, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:scn:financ:y:2018:i:4:p:104-113. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Алексей Скалабан (email available below). General contact details of provider: http://financetp.fa.ru .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.