A Forecast Comparison of Volatility Models Using Realized Volatility: Evidence from the Bitcoin Market
9 Pages Posted: 28 Nov 2018 Last revised: 9 Dec 2018
Date Written: November 1, 2018
This paper first evaluates the volatility modeling in the Bitcoin market in terms of its realized volatility, which is considered to be a reliable proxy of its true volatility. In addition, we also rely on the important work by Patton (2011), which shows good measures for making the forecast accuracy robust to noise in the imperfect volatility proxy. We empirically show that (1) the asymmetric volatility models such as EGARCH and APARCH have a higher predictability, and (2) the volatility model with normal distribution performs better than the fat-tailed distribution such as skewed t distribution.
Keywords: Cryptocurrency, Bitcoin, realized volatility, volatility modeling
JEL Classification: C5, G1
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