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

Jui-Cheng Hung, Hung-Chun Liu and J. Jimmy Yang

The North American Journal of Economics and Finance, 2020, vol. 52, issue C

Abstract: 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

Keywords: Bitcoin; Realized GARCH model; Jump-robust realized measure; Realized bi-power variation; Realized tri-power variation (search for similar items in EconPapers)
JEL-codes: C52 C53 G17 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:52:y:2020:i:c:s1062940820300620

DOI: 10.1016/j.najef.2020.101165

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