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What Drives Bitcoin Volatility?




We look at the link between the volatility in the Bitcoin market and the volatility in other related traditional markets, i.e. the gold, currency and stock market. We also try to answer if the volatility in the Bitcoin market can be explained by retail investor-driven internet search volumes or, perhaps, by the general level of risk in the financial system, as measured by two market-wide risk indicators. We use daily, weekly as well as monthly data covering the period 2011 to 2017. Correlations and regressions reveal a weak but positive contemporaneous link between changes in the Bitcoin volatility and changes in the volatility of the trade weighted USD currency index. A stronger positive link is found between Bitcoin volatility and search pressures on Bitcoin-related words on Google, particularly for the word “bitcoin”. To further assess what drives Bitcoin volatility we turn to a VAR-analysis and impulse response functions which point at Google searches for the word “bitcoin”, and to some extent the USD currency index volatility, being the only determinants of future Bitcoin volatility. We then use our findings to make improved predictions of Bitcoin volatility based on Google search activity. Interestingly, the significant link that we find between Google search volumes and market volatility points at retail investors, rather than large institutions, being the most important drivers of Bitcoin volatility. We believe that we contribute to the literature in several ways and that our results could be of significant practical importance if the Bitcoin market continues to grow at the current speed.

Suggested Citation

  • Byström, Hans & Krygier, Dominika, 2018. "What Drives Bitcoin Volatility?," Working Papers 2018:24, Lund University, Department of Economics.
  • Handle: RePEc:hhs:lunewp:2018_024

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    References listed on IDEAS

    1. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    2. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    3. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1593-1636.
    4. 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.
    5. Ladislav Kristoufek, 2015. "What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.
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    More about this item


    Bitcoin; volatility; internet searches; Google Trends; gold; VIX;

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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