Evaluating the Predictive Power of the Energy-Related Uncertainty Index on Bitcoin Volatility
Keywords:
energy uncertainty, realized volatility, stochastic model, cryptocurrency market, risk managementAbstract
Uncertainty indices at low frequency have garnered increasing attention in financial research due to their significant impact on asset returns. This study delves into the emerging field of low-frequency uncertainty indices in financial research, focusing on the Energy-Related Uncertainty Index (EUI) and its implications for Bitcoin volatility modeling. Utilizing GARCH-MIDAS models, we compare Bitcoin's volatility under the influence of EUI against Bitcoin's realized volatility (RV), examining its predictive power across 28 countries. The results reveal two key findings: Firstly, integrating EUI into the GARCH-MIDAS model significantly enhances its capability to explain Bitcoin volatility, with the effectiveness differing across countries. EUI's impact on Bitcoin volatility is especially pronounced with approximately a one-year lag. Secondly, although there is no apparent leverage effect in Bitcoin returns, EUI exhibits an asymmetric influence on Bitcoin volatility, highlighting its essential role in volatility modeling. These findings hold significance for investors and policymakers, providing valuable insights to enhance risk management strategies in the volatile cryptocurrency markets.
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