Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/230800 
Year of Publication: 
2019
Series/Report no.: 
IRTG 1792 Discussion Paper No. 2019-024
Publisher: 
Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", Berlin
Abstract: 
Among all the emerging markets, the cryptocurrency market is considered the most controversial and simultaneously the most interesting one. The visibly significant market capitalization of cryptos motivates modern financial instruments such as futures and options. Those will depend on the dynamics, volatility, or even the jumps of cryptos. In this paper, the risk characteristics for Bitcoin are analyzed from a realized volatility dynamics view. The realized variance RV is estimated with (threshold-)jump components (T)J, semivariance RSV+(−) , and signed jumps (T)J+(−) . Our empirical results show that the Bitcoin market is far riskier than any other developed financial market. Up to 68% of the sample days are identified to entangle jumps. However, the discontinuities do not contribute to the variance significantly. By employing a 90-day rolling-window method, the in-sample evidence suggests that the impacts of predictors change over time systematically under HAR-type models. The out-of-sample forecasting results reveal that the forecasting horizon plays an important role in choosing forecasting models. For long-horizon risk forecast, a finer model calibrated with jumps gives extra utility up to 20 basis points annually, while an approach based on the roughest estimators suits the short-horizon risk forecast best. Last but not least, a simple equal-weighted portfolio not only significantly reduces the size and quantity of jumps but also gives investors higher utility in short-horizon risk forecast case.
Subjects: 
Cryptocurrency
Bitcoin
Realized Variance
Thresholded Jump
Signed Jumps
Realized Utility
JEL: 
C53
E47
G11
G17
Document Type: 
Working Paper

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