Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty

doi:10.1016/j.jempfin.2021.03.003

CSpace

	Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty
	Qiu, Yue 1; Wang, Zongrun 2; Xie, Tian 3; Zhang, Xinyu 4,5,6
	2021-06-01
发表期刊	JOURNAL OF EMPIRICAL FINANCE
ISSN	0927-5398
卷号	62 页码:179-201
摘要	Modeling Bitcoin realized volatility by the heterogeneous autoregressive model is subject to substantial model specification uncertainty in practice. To circumvent the lag specification uncertainty, we introduce a new model averaging coefficient estimator with the mean squared error of the coefficient to be minimized. We show that the averaged coefficient vector has a root -n consistency with n being the sample size and propose using a double bootstrap to provide inference. Monte Carlo simulation results demonstrate reliability of the proposed method. The in-sample application shows that adjustment for measurement errors by HARQ-type models is necessary. The model averaging estimator has higher in-sample explanatory power with more significant predictors. The out-of-sample outcomes reveal that the forecast horizon plays a key role at determining the effectiveness of signed realized variance for predicting the Bitcoin volatility. Finally, the model averaging HARQ-type models demonstrate superior out-of-sample performance for both short and long forecast horizons.
关键词	HARQ Model averaging & nbsp Bitcoin Realized volatility
DOI	10.1016/j.jempfin.2021.03.003
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[71925007] ; National Natural Science Foundation of China[72091212] ; National Natural Science Foundation of China[72003122] ; National Natural Science Foundation of China[71631008] ; National Natural Science Foundation of China[71701175] ; Chinese Ministry of Education Project of Humanities and Social Sciences, China[17YJC790174] ; Fundamental Research Funds for the Central Universities, China
WOS研究方向	Business & Economics
WOS类目	Business, Finance ; Economics
WOS记录号	WOS:000656796300011
出版者	ELSEVIER
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/58789
专题	中国科学院数学与系统科学研究院
通讯作者	Zhang, Xinyu
作者单位	1.Shanghai Univ Int Business & Econ, Sch Finance, Shanghai, Peoples R China 2.Cent South Univ, Sch Business, Changsha, Peoples R China 3.Shanghai Univ Finance & Econ, Coll Business, Shanghai, Peoples R China 4.Univ Sci & Technol China, Sch Management, Hefei, Peoples R China 5.Univ Sci & Technol China, Int Inst Finance, Hefei, Peoples R China 6.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Qiu, Yue,Wang, Zongrun,Xie, Tian,et al. Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty[J]. JOURNAL OF EMPIRICAL FINANCE,2021,62:179-201.
APA	Qiu, Yue,Wang, Zongrun,Xie, Tian,&Zhang, Xinyu.(2021).Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty.JOURNAL OF EMPIRICAL FINANCE,62,179-201.
MLA	Qiu, Yue,et al."Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty".JOURNAL OF EMPIRICAL FINANCE 62(2021):179-201.