Exogenous Drivers of Bitcoin and Cryptocurrency Volatility – A Mixed Data Sampling Approach to Forecasting
19 Pages Posted: 27 Jun 2018 Last revised: 5 Aug 2019
Date Written: June 19, 2019
We apply the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility of five highly capitalized Cryptocurrencies (Bitcoin, Etherium, Litecoin, Ripple, and Stellar) 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 and the Global Financial Stress Index outperform 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. In addition, we show that the Global Real Economic Activity provides superior volatility predictions for both, bull and bear markets.
Keywords: Bitcoin, Cryptocurrencies, GARCH, Mixed Data Sampling, Volatility
JEL Classification: C10, C58, G11
Suggested Citation: Suggested Citation