學年
|
108 |
學期
|
2 |
出版(發表)日期
|
2020-04-01 |
作品名稱
|
Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators |
作品名稱(其他語言)
|
|
著者
|
Jui-Cheng Hung; Hung-Chun Liu; J. Jimmy Yang |
單位
|
|
出版者
|
|
著錄名稱、卷期、頁數
|
North American Journal of Economics and Finance、52、101165 |
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 |
關鍵字
|
Bitcoin; Realized GARCH model; Jump-robust realized measure; Realized bi-power variation; Realized tri-power variation |
語言
|
en |
ISSN
|
1062-9408 |
期刊性質
|
國外 |
收錄於
|
SSCI
NotTSSCI
|
產學合作
|
|
通訊作者
|
|
審稿制度
|
是 |
國別
|
USA |
公開徵稿
|
|
出版型式
|
,電子版 |