Improving the realized GARCH's volatility forecast for Bitcoin with jump-robust estimators

被引:22
作者
Hung, Jui-Cheng [1 ]
Liu, Hung-Chun [2 ]
Yang, J. Jimmy [3 ]
机构
[1] Chinese Culture Univ, Dept Banking & Finance, Taipei, Taiwan
[2] Minghsin Univ Sci & Technol, Dept Finance, Hsinchu, Taiwan
[3] Oregon State Univ, Coll Business, Corvallis, OR 97331 USA
关键词
Bitcoin; Realized GARCH model; Jump-robust realized measure; Realized bi-power variation; Realized tri-power variation; LONG MEMORY VOLATILITY; MARKETS; MODEL; EXCHANGE; RISK;
D O I
10.1016/j.najef.2020.101165
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This study employs the realized GARCH (RGARCH) model to estimate the volatility of Bitcoin returns and measure the benefits of various scaled realized measures in forecasting volatility. Empirical results show that considerable price jumps occurred in the Bitcoin market, suggesting that a jump-robust realized measure is crucial to estimate Bitcoin volatility. The RGARCH model, especially the one with tri-power variation, outperforms the standard GARCH model. Additionally, the RGARCH model with jump-robust realized measures can provide steady forecasting performance. This study is timely given that the CME may release a Bitcoin option product and our results are relevant to option pricing.
引用
收藏
页数:11
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