The primary purpose of this paper is to investigate whether a novel Markov regime‐switching mixed‐data sampling (MRS‐MIADS) model we design can improve the prediction accuracy of the realized variance (RV) of Bitcoin. Moreover, to verify whether the importance of jumps for RV forecasting changes over time, we extend the standard MIDAS model to characterize two volatility regimes and introduce a jump‐driven time‐varying transition probability between the two regimes. Our results suggest that the proposed novel MRS‐MIDAS model exhibits statistically significant improvement for forecasting the RV of Bitcoin. In addition, we find that jump occurrences significantly increase the persistence of the high‐volatility regime and switch between high‐ and low‐volatility regimes. A wide range of checks confirm the robustness of our results. Finally, the proposed model shows significant improvement for 2‐week and 1‐month horizon forecasts.

中文翻译：

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加密货币波动性预测：马尔可夫政权转换的MIDAS方法

本文的主要目的是研究我们设计的新型马尔可夫政权切换混合数据采样（MRS-MIADS）模型是否可以提高比特币实现变异（RV）的预测准确性。此外，为了验证跳跃对RV预测的重要性是否随时间变化，我们扩展了标准MIDAS模型以表征两个波动率体制，并引入了两个体制之间的跳跃驱动时变过渡概率。我们的结果表明，提出的新型MRS-MIDAS模型在预测比特币RV方面具有统计学上的显着改进。此外，我们发现跳跃事件显着增加了高波动率制度的持久性，并在高波动率制度和低波动率制度之间切换。广泛的检查证实了我们结果的可靠性。最后，