Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach to Forecasting
13 Pages Posted: 27 Jun 2018 Last revised: 11 Dec 2018
Date Written: June 7, 2018
We apply the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility of four highly capitalized Cryptocurrencies (Bitcoin, Etherium, Litecoin, and Ripple) as well as the Cryptocurrency index CRIX. Based on the prediction quality, we determine the most important exogenous drivers of volatility in Cryptocurrency markets. We find that the Global Real Economic Activity outperforms all other economic and financial drivers under investigation. Only the average forecast combination results in lower loss functions. This indicates that the information content of exogenous factors is time-varying and the model averaging approach diversifies the impact of single drivers.
Keywords: Bitcoin, Cryptocurrencies, GARCH, Mixed Data Sampling, Volatility
JEL Classification: C10, C58, G11
Suggested Citation: Suggested Citation