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Do infectious diseases explain Bitcoin price Fluctuations?

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  • Aliu, Florin

Abstract

This study examines Bitcoin price movements from an infectious disease perspective. The author compares the outbreak of the COVID-19 pandemic with the Bitcoin price explosion and adopts the SIR epidemiological model. The SIR model operates by categorizing the population of individuals into susceptible (S), infected (I), and removed (R). In the case of Bitcoin, open wallets represent the susceptible population, and the infection starts with a single individual. After conducting four estimation trials, the model that uses the recovery rate derived from the Bitcoin price downtrend and the infection rate from the upward trend has the highest accuracy. The estimation deviates from the Bitcoin price explosions by only three days. Previous studies commonly use faster-than-exponential growth or stationarity tests to identify bubble formations. This paper introduces a novel approach that employs epidemiological models to analyze Bitcoin’s explosive price behavior.

Suggested Citation

  • Aliu, Florin, 2024. "Do infectious diseases explain Bitcoin price Fluctuations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 93(C).
    • Handle: RePEc:eee:intfin:v:93:y:2024:i:c:s1042443124000775
    DOI: 10.1016/j.intfin.2024.102011
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    as
    1. Podhorsky, Andrea, 2024. "Bursting the bitcoin bubble: Do market prices reflect fundamental bitcoin value?," International Review of Financial Analysis, Elsevier, vol. 93(C).
    2. Suardi, Sandy & Rasel, Atiqur Rahman & Liu, Bin, 2022. "On the predictive power of tweet sentiments and attention on bitcoin," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 289-301.
    3. Phillips, Peter C.B. & Shi, Shu-Ping, 2018. "Financial Bubble Implosion And Reverse Regression," Econometric Theory, Cambridge University Press, vol. 34(4), pages 705-753, August.
    4. Lee, Seungho & Meslmani, Nabil El & Switzer, Lorne N., 2020. "Pricing Efficiency and Arbitrage in the Bitcoin Spot and Futures Markets," Research in International Business and Finance, Elsevier, vol. 53(C).
    5. Coskun, Esra Alp & Lau, Chi Keung Marco & Kahyaoglu, Hakan, 2020. "Uncertainty and herding behavior: evidence from cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 54(C).
    6. Shahzad, Syed Jawad Hussain & Anas, Muhammad & Bouri, Elie, 2022. "Price explosiveness in cryptocurrencies and Elon Musk's tweets," Finance Research Letters, Elsevier, vol. 47(PB).
    7. Xiong, Jinwu & Liu, Qing & Zhao, Lei, 2020. "A new method to verify Bitcoin bubbles: Based on the production cost," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    8. Shu, Min & Zhu, Wei, 2020. "Real-time prediction of Bitcoin bubble crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    9. Florin Aliu & Alban Asllani & Simona Hašková, 2023. "The impact of bitcoin on gold, the volatility index (VIX), and dollar index (USDX): analysis based on VAR, SVAR, and wavelet coherence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 41(1), pages 64-87, June.
    10. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    11. Easley, David & O'Hara, Maureen & Basu, Soumya, 2019. "From mining to markets: The evolution of bitcoin transaction fees," Journal of Financial Economics, Elsevier, vol. 134(1), pages 91-109.
    12. Kaiser, Lars & Stöckl, Sebastian, 2020. "Cryptocurrencies: Herding and the transfer currency," Finance Research Letters, Elsevier, vol. 33(C).
    13. Noemi Schmitt & Frank Westerhoff, 2017. "Herding behaviour and volatility clustering in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1187-1203, August.
    14. Lee, Adrian D. & Li, Mengling & Zheng, Huanhuan, 2020. "Bitcoin: Speculative asset or innovative technology?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    15. Xu, Lei & Kinkyo, Takuji, 2023. "Hedging effectiveness of bitcoin and gold: Evidence from G7 stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    16. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    17. Choi, Hyungeun, 2021. "Investor attention and bitcoin liquidity: Evidence from bitcoin tweets," Finance Research Letters, Elsevier, vol. 39(C).
    18. Duan, Kun & Gao, Yang & Mishra, Tapas & Satchell, Stephen, 2023. "Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    19. Cui, Tianxiang & Ding, Shusheng & Jin, Huan & Zhang, Yongmin, 2023. "Portfolio constructions in cryptocurrency market: A CVaR-based deep reinforcement learning approach," Economic Modelling, Elsevier, vol. 119(C).
    20. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    21. Sean Foley & Jonathan R Karlsen & Tālis J Putniņš, 2019. "Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed through Cryptocurrencies?," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1798-1853.
    22. Jocelyn Grira & Sana Guizani & Ines Kahloul, 2022. "Bitcoin's hedging attributes against equity market volatility: empirical evidence during the COVID-19 pandemic," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 23(5), pages 605-618, August.
    23. 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.
    24. Li, Yi & Zhang, Wei & Urquhart, Andrew & Wang, Pengfei, 2022. "The role of media coverage in the bubble formation: Evidence from the Bitcoin market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    25. Bajra, Ujkan Q. & Aliu, Florin, 2023. "Deciphering the cryptocurrency conundrum: Investigating speculative characteristics and volatility," Finance Research Letters, Elsevier, vol. 58(PC).
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    More about this item

    Keywords

    Bitcoin; COVID-19; Infectious diseases; SIR model; Pandemic;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G4 - Financial Economics - - Behavioral Finance

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