This textual analysis with spillover effects examines whether the sentiment expressed in the US President Donald Trump’s tweets correlates to price and volume activity in the Bitcoin market. After examining 13,918 tweets from January 2017 to January 2020, we find that negative sentiment is a predictive factor for Bitcoin returns, trading volumes, realized volatility, and jumps. In addition, only negative sentiment has a Granger-causal relation with volatility. We also find that Trump’s Twitter sentiment can influence the Bitcoin market in the form of time-varying dependence. This paper also extended the COVID-19 period and found that Trump’s sentiment can be a predictive tool to the Bitcoin market during the pandemic. Our results hold robust for alternative cryptocurrencies and offer insights about this market.

这种具有溢出效应的文本分析检验了美国总统唐纳德特朗普的推文中表达的情绪是否与比特币市场的价格和交易量活动相关。在检查了 2017 年 1 月至 2020 年 1 月的 13,918 条推文后，我们发现负面情绪是比特币回报、交易量、已实现波动率和跳涨的预测因素。此外，只有负面情绪与波动性存在格兰杰因果关系。我们还发现，特朗普的 Twitter 情绪可以以时变依赖的形式影响比特币市场。该论文还延长了 COVID-19 时期，发现特朗普的情绪可以成为大流行期间比特币市场的预测工具。我们的结果适用于替代加密货币，并提供有关该市场的见解。