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

2018; Multidisciplinary Digital Publishing Institute; Volume: 11; Issue: 2 Linguagem: Inglês

10.3390/jrfm11020023

1911-8074

Christian Conrad, Anessa Custovic, Éric Ghysels,

Complex Systems and Time Series 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 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.