Bitcoin volatility predictability-The role of jumps and regimes

【Author】 Qian, Lihua; Wang, Jiqian; Ma, Feng; Li, Ziyang

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【Abstract】This study mainly focuses on the role of jumps in forecasting Bitcoin volatility using linear and nonlinear mixed data sampling models. The results provide strong evidence that using a forecasting model that incorporates continuous-time jump and two-stage regimes can significantly improve predictive accuracy and achieve high economic gains. Interestingly, the superior forecasting ability of the model with a continuous-time jump is reflected in highly volatile periods, especially in the period of a Black Swan event.

【Keywords】Bitcoin volatility; Markov-regime switching; Jump; Mixed data sampling model

【发表时间】2022 JUN

【收录时间】2022-07-17

【文献类型】实证性文章

【主题类别】

区块链治理-市场治理-市场分析