Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis
1
Department of Economics, Heidelberg University, Bergheimer Strasse 58, 69115 Heidelberg, Germany
2
Department of Economics, University of North Carolina, Chapel Hill, NC 27599, USA
3
CEPR, Department of Finance, Kenan-Flagler School of Business, University of North Carolina, Chapel Hill, NC 27599, USA
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2018, 11(2), 23; https://doi.org/10.3390/jrfm11020023
Received: 10 April 2018 / Revised: 5 May 2018 / Accepted: 8 May 2018 / Published: 10 May 2018
(This article belongs to the Special Issue Alternative Assets and Cryptocurrencies)
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.
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Keywords:
Baltic dry index; Bitcoin volatility; digital currency; GARCH-MIDAS; pro-cyclical volatility; volume
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MDPI and ACS Style
Conrad, C.; Custovic, A.; Ghysels, E. Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis. J. Risk Financial Manag. 2018, 11, 23.
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