KMS Of Academy of mathematics and systems sciences, CAS
| Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty | |
| Qiu, Yue1; Wang, Zongrun2; Xie, Tian3; Zhang, Xinyu4,5,6 | |
| 2021-06-01 | |
| Source Publication | JOURNAL OF EMPIRICAL FINANCE
 |
| ISSN | 0927-5398 |
| Volume | 62Pages:179-201 |
| Abstract | 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. |
| Keyword | HARQ Model averaging & nbsp Bitcoin Realized volatility |
| DOI | 10.1016/j.jempfin.2021.03.003 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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 Research Area | Business & Economics |
| WOS Subject | Business, Finance ; Economics |
| WOS ID | WOS:000656796300011 |
| Publisher | ELSEVIER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/58789 |
| Collection | 中国科学院数学与系统科学研究院 |
| Corresponding Author | Zhang, Xinyu |
| Affiliation | 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 |
| Recommended Citation 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. |
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