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Forecasting Bitcoin risk measures: A robust approach
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DOI：10.1016/j.ijforecast.2019.01.003.png)
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摘要
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Over the last few years, Bitcoin and other cryptocurrencies have attracted the interest of many investors, practitioners and researchers. However, little attention has been paid to the predictability of their risk measures. This paper compares the predictability of the one-step-ahead volatility and Value-at-Risk of Bitcoin using several volatility models. We also include procedures that take into account the presence of outliers and estimate the volatility and Value-at-Risk in a robust fashion. Our results show that robust procedures outperform non-robust ones when forecasting the volatility and estimating the Value at-Risk. These results suggest that the presence of outliers plays an important role in the modelling and forecasting of Bitcoin risk measures. (C) 2019 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Keyword:
Cryptocurrency
GARCH
Model confidence set
Outliers
Realised volatility
Value-at-Risk
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