The main objective of this study is to investigate tail risk connectedness among six major cryptocurrency markets and determine the extent to which investor sentiment, economic conditions, and economic uncertainty can predict tail risk interconnectedness. Combining the Conditional Autoregressive Value-at-Risk (CAViaR) model with the time-varying parameter vector autoregressive (TVP-VAR) approach shows that the transmission of tail risks among cryptocurrencies changes dynamically over time. During crises and significant events, transmission bursts and tail risks change. Based on both in- and out-of-sample forecasts, we find that the information contained in investor sentiment, economic conditions, and uncertainty includes significant predictive content about the tail risk connectedness of cryptocurrencies.

中文翻译：

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加密货币市场之间尾部风险传播的模式和决定因素：最近危机事件的新证据

本研究的主要目的是调查六大加密货币市场之间的尾部风险关联性，并确定投资者情绪、经济状况和经济不确定性可以在多大程度上预测尾部风险关联性。将条件自回归风险值（CAViaR）模型与时变参数向量自回归（TVP-VAR）方法相结合表明，加密货币之间尾部风险的传递随时间动态变化。在危机和重大事件期间，传播爆发，尾部风险发生变化。基于样本内和样本外的预测，我们发现投资者情绪、经济状况和不确定性中包含的信息包含有关加密货币尾部风险关联性的重要预测内容。