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.
View Full-Text
Keywords:
Baltic dry index; Bitcoin volatility; digital currency; GARCH-MIDAS; pro-cyclical volatility; volume
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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. https://doi.org/10.3390/jrfm11020023
AMA Style
Conrad C, Custovic A, Ghysels E. Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis. Journal of Risk and Financial Management. 2018; 11(2):23. https://doi.org/10.3390/jrfm11020023
Chicago/Turabian StyleConrad, Christian, Anessa Custovic, and Eric Ghysels. 2018. "Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis" Journal of Risk and Financial Management 11, no. 2: 23. https://doi.org/10.3390/jrfm11020023
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
