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Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis

Author

Listed:
  • Christian Conrad

    (Department of Economics, Heidelberg University, Bergheimer Strasse 58, 69115 Heidelberg, Germany)

  • Anessa Custovic

    (Department of Economics, University of North Carolina, Chapel Hill, NC 27599, USA)

  • Eric Ghysels

    (Department of Economics, University of North Carolina, Chapel Hill, NC 27599, USA
    CEPR, Department of Finance, Kenan-Flagler School of Business, University of North Carolina, Chapel Hill, NC 27599, USA)

Abstract

We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure of global economic activity. We find that S&P 500 realized volatility has a negative and highly significant effect on long-term Bitcoin volatility. The finding is atypical for volatility co-movements across financial markets. Moreover, we find that the S&P 500 volatility risk premium has a significantly positive effect on long-term Bitcoin volatility. Finally, we find a strong positive association between the Baltic dry index and long-term Bitcoin volatility. This result shows that Bitcoin volatility is closely linked to global economic activity. Overall, our findings can be used to construct improved forecasts of long-term Bitcoin volatility.

Suggested Citation

  • Christian Conrad & Anessa Custovic & Eric Ghysels, 2018. "Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis," JRFM, MDPI, vol. 11(2), pages 1-12, May.
    • Handle: RePEc:gam:jjrfmx:v:11:y:2018:i:2:p:23-:d:145629
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    References listed on IDEAS

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