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

Abstract

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

Suggested Citation

Hattori, Takahiro, A Forecast Comparison of Volatility Models Using Realized Volatility: Evidence from the Bitcoin Market (November 1, 2018). Available at SSRN: https://ssrn.com/abstract=3267379 or http://dx.doi.org/10.2139/ssrn.3267379

Takahiro Hattori (Contact Author)

Ministry of Finance - Japan ( email )

3-1-1 Kasumigaseki
Chiyoda-ku
Tokyo, 100-8940
Japan

Register to save articles to
your library

Register

Paper statistics

Downloads
148
rank
193,326
Abstract Views
510
PlumX Metrics