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What are bitcoin market reactions to its-related events?

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  • Li, Zhenghui
  • Chen, Liming
  • Dong, Hao

Abstract

Motivated by the risen linkage between events and Bitcoin return, this paper first defines Bitcoin-related events (BREs) based on the change points analysis and then divides these events into two categories. Furthermore, we model the impact of BREs on the Bitcoin market activities, using an event study methodology and a GARCH-X model. Empirical results show that the shock directions of Bitcoin-related events on Bitcoin price are heavily correlative with types of events. Additionally, there is a significant positive influence of domestic events on reaction volatility, whereas the foreign events impose their influences on both the expectations of market reactions and volatility.

Suggested Citation

  • Li, Zhenghui & Chen, Liming & Dong, Hao, 2021. "What are bitcoin market reactions to its-related events?," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 1-10.
  • Handle: RePEc:eee:reveco:v:73:y:2021:i:c:p:1-10
    DOI: 10.1016/j.iref.2020.12.020
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    as
    1. Ji, Qiang & Guo, Jian-Feng, 2015. "Oil price volatility and oil-related events: An Internet concern study perspective," Applied Energy, Elsevier, vol. 137(C), pages 256-264.
    2. Tetsuya Takaishi, 2017. "Statistical properties and multifractality of Bitcoin," Papers 1707.07618, arXiv.org, revised May 2018.
    3. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    4. Huina Mao & Scott Counts & Johan Bollen, 2011. "Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data," Papers 1112.1051, arXiv.org.
    5. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.
    6. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    7. Ciaian, Pavel & Rajcaniova, Miroslava & Kancs, d'Artis, 2018. "Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 173-195.
    8. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    9. Alina Sorescu & Nooshin L. Warren & Larisa Ertekin, 2017. "Event study methodology in the marketing literature: an overview," Journal of the Academy of Marketing Science, Springer, vol. 45(2), pages 186-207, March.
    10. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2015. "Modelling systemic price cojumps with Hawkes factor models," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1137-1156, July.
    11. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    12. Ilaria Bordino & Stefano Battiston & Guido Caldarelli & Matthieu Cristelli & Antti Ukkonen & Ingmar Weber, 2012. "Web Search Queries Can Predict Stock Market Volumes," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-17, July.
    13. Hu, Haiqing & Wei, Wei & Chang, Chun-Ping, 2019. "Do shale gas and oil productions move in convergence? An investigation using unit root tests with structural breaks," Economic Modelling, Elsevier, vol. 77(C), pages 21-33.
    14. Bouri, Elie & Gupta, Rangan & Tiwari, Aviral Kumar & Roubaud, David, 2017. "Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions," Finance Research Letters, Elsevier, vol. 23(C), pages 87-95.
    15. Huang, Zhehao & Liao, Gaoke & Li, Zhenghui, 2019. "Loaning scale and government subsidy for promoting green innovation," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 148-156.
    16. Fenghua Wen & Jihong Xiao & Chuangxia Huang & Xiaohua Xia, 2018. "Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 319-334, January.
    17. Tonzer, Lena, 2015. "Cross-border interbank networks, banking risk and contagion," Journal of Financial Stability, Elsevier, vol. 18(C), pages 19-32.
    18. Wang, Juan & Zhang, Dongxiang & Zhang, Jian, 2015. "Mean reversion in stock prices of seven Asian stock markets: Unit root test and stationary test with Fourier functions," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 157-164.
    19. Thies, Sven & Molnár, Peter, 2018. "Bayesian change point analysis of Bitcoin returns," Finance Research Letters, Elsevier, vol. 27(C), pages 223-227.
    20. 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.
    21. Takaishi, Tetsuya, 2018. "Statistical properties and multifractality of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 507-519.
    22. Gandal, Neil & Hamrick, JT & Moore, Tyler & Oberman, Tali, 2018. "Price manipulation in the Bitcoin ecosystem," Journal of Monetary Economics, Elsevier, vol. 95(C), pages 86-96.
    23. Elie Bouri & Luis A. Gil‐Alana & Rangan Gupta & David Roubaud, 2019. "Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 412-426, January.
    24. Yue Liu & Hao Dong & Pierre Failler, 2019. "The Oil Market Reactions to OPEC’s Announcements," Energies, MDPI, vol. 12(17), pages 1-15, August.
    25. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    26. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    27. Stjepan Beguv{s}i'c & Zvonko Kostanjv{c}ar & H. Eugene Stanley & Boris Podobnik, 2018. "Scaling properties of extreme price fluctuations in Bitcoin markets," Papers 1803.08405, arXiv.org.
    28. Ederington, Louis & Guan, Wei & Yang, Lisa (Zongfei), 2015. "Bond market event study methods," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 281-293.
    29. Claus Dierksmeier & Peter Seele, 2018. "Cryptocurrencies and Business Ethics," Journal of Business Ethics, Springer, vol. 152(1), pages 1-14, September.
    30. Liu, Laura Xiaolei & Shu, Haibing & Wei, K.C. John, 2017. "The impacts of political uncertainty on asset prices: Evidence from the Bo scandal in China," Journal of Financial Economics, Elsevier, vol. 125(2), pages 286-310.
    31. Su, Chi-Wei & Li, Zheng-Zheng & Tao, Ran & Si, Deng-Kui, 2018. "Testing for multiple bubbles in bitcoin markets: A generalized sup ADF test," Japan and the World Economy, Elsevier, vol. 46(C), pages 56-63.
    32. Zhenghui Li & Gaoke Liao & Khaldoon Albitar, 2020. "Does corporate environmental responsibility engagement affect firm value? The mediating role of corporate innovation," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1045-1055, March.
    33. Loutia, Amine & Mellios, Constantin & Andriosopoulos, Kostas, 2016. "Do OPEC announcements influence oil prices?," Energy Policy, Elsevier, vol. 90(C), pages 262-272.
    34. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    35. Lin, Sharon Xiaowen & Tamvakis, Michael, 2010. "OPEC announcements and their effects on crude oil prices," Energy Policy, Elsevier, vol. 38(2), pages 1010-1016, February.
    36. Shuanglian Chen & Zhehao Huang & Benjamin M. Drakeford & Pierre Failler, 2019. "Lending Interest Rate, Loaning Scale, and Government Subsidy Scale in Green Innovation," Energies, MDPI, vol. 12(23), pages 1-22, November.
    37. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    38. Feng, Wenjun & Wang, Yiming & Zhang, Zhengjun, 2018. "Informed trading in the Bitcoin market," Finance Research Letters, Elsevier, vol. 26(C), pages 63-70.
    39. Manner, Hans & Stark, Florian & Wied, Dominik, 2019. "Testing for structural breaks in factor copula models," Journal of Econometrics, Elsevier, vol. 208(2), pages 324-345.
    40. Begušić, Stjepan & Kostanjčar, Zvonko & Eugene Stanley, H. & Podobnik, Boris, 2018. "Scaling properties of extreme price fluctuations in Bitcoin markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 400-406.
    41. Sang Byung Seo & Jessica A. Wachter, 2018. "Do Rare Events Explain CDX Tranche Spreads?," Journal of Finance, American Finance Association, vol. 73(5), pages 2343-2383, October.
    42. Dyhrberg, Anne Haubo, 2016. "Hedging capabilities of bitcoin. Is it the virtual gold?," Finance Research Letters, Elsevier, vol. 16(C), pages 139-144.
    43. A. Craig MacKinlay, 1997. "Event Studies in Economics and Finance," Journal of Economic Literature, American Economic Association, vol. 35(1), pages 13-39, March.
    44. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
    45. Phillip, Andrew & Chan, Jennifer S.K. & Peiris, Shelton, 2018. "A new look at Cryptocurrencies," Economics Letters, Elsevier, vol. 163(C), pages 6-9.
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    2. Yanqiong Liu & Zhenghui Li & Yanyan Yao & Hao Dong, 2021. "Asymmetry of Risk Evolution in Crude Oil Market: From the Perspective of Dual Attributes of Oil," Energies, MDPI, vol. 14(13), pages 1-22, July.
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    5. Li, Bin & Liu, Xiaomei, 2023. "Communist party organization and abnormal compensation of enterprise executives," Finance Research Letters, Elsevier, vol. 57(C).
    6. Ao Shu & Feiyang Cheng & Jianlei Han & Zini Liang & Zheyao Pan, 2023. "Arbitrage across different Bitcoin exchange venues: Perspectives from investor base and market related events," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(5), pages 5183-5210, December.
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    8. Haihua Liu & Peng Wang & Zejun Li, 2021. "Is There Any Difference in the Impact of Digital Transformation on the Quantity and Efficiency of Enterprise Technological Innovation? Taking China’s Agricultural Listed Companies as an Example," Sustainability, MDPI, vol. 13(23), pages 1-19, November.
    9. Yue Liu & Pierre Failler & Zhiying Liu, 2022. "Impact of Environmental Regulations on Energy Efficiency: A Case Study of China’s Air Pollution Prevention and Control Action Plan," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    10. Florentina Șoiman & Jean-Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX [Le rendement de (I)DeFiX]," Working Papers hal-03625891, HAL.
    11. Li, Zhenghui & Mo, Bin & Nie, He, 2023. "Time and frequency dynamic connectedness between cryptocurrencies and financial assets in China," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 46-57.
    12. Florentina c{S}oiman & Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX," Papers 2204.00251, arXiv.org.

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    More about this item

    Keywords

    Events; Change points; Event study methodology; Investor attention; Bitcoin;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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