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

文化大學機構典藏 CCUR > 商學院 > 財務金融學系 > 期刊論文 > Item 987654321/48850

Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/48850

Title:	Improving the realized GARCH's volatility forecast for Bitcoin with jump-robust estimators
Authors:	Hung, JC (Hung, Jui-Cheng) Liu, HC (Liu, Hung-Chun) Yang, JJ (Yang, J. Jimmy)
Contributors:	財金系
Keywords:	Bitcoin Realized GARCH model Jump-robust realized measure Realized bi-power variation Realized tri-power variation
Date:	2020-04
Issue Date:	2020-11-27 16:00:25 (UTC+8)
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.
Relation:	NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE 卷冊: 52 文獻號碼: 101165
Appears in Collections:	[財務金融學系 ] 期刊論文

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