Long- and short-term cryptocurrency volatility components: a GARCH-MIDAS analysis

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 realiz...

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Main Authors: Conrad, Christian (Author) , Custovic, Anessa (Author) , Ghysels, Eric (Author)
Format: Article (Journal)
Language:English
Published: 10 May 2018
In: Journal of risk and financial management
Year: 2018, Volume: 11, Issue: 2
ISSN:1911-8074
DOI:10.3390/jrfm11020023
Subjects:
Online Access:Resolving-System, kostenfrei, Volltext: https://doi.org/10.3390/jrfm11020023
Verlag, kostenfrei, Volltext: http://www.mdpi.com/1911-8074/11/2/23/pdf
Resolving-System, kostenfrei: http://hdl.handle.net/10419/238870
Verlag, Terms of use, 46: http://creativecommons.org/licenses/by/4.0/
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Author Notes:Christian Conrad, Anessa Custovic and Eric Ghysels
Description
Summary: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.
Item Description:Published: 10 May 2018
This article belongs to the Special Issue Alternative Assets and Cryptocurrencies
Gesehen am 17.04.2019
Physical Description:Online Resource
ISSN:1911-8074
DOI:10.3390/jrfm11020023