Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach To Forecasting
Thomas Walther () and
No 1815, Working Papers on Finance from University of St. Gallen, School of Finance
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 ?nd that the Global Real Economic Activity outperforms all other economic and ?nancial 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 diversi?es the impact of single drivers.
Keywords: Bitcoin; Cryptocurrencies; GARCH; Mixed Data Sampling; Volatility (search for similar items in EconPapers)
JEL-codes: C10 C58 G11 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:usg:sfwpfi:2018:15
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