用语言变化预测市场波动，发现政治立场影响预测效果
Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups
- 通过语义嵌入变化追踪市场冲击的因果关系
- 政治立场不同群体对市场波动反应差异显著
- 突发事件中语言数据对经济预测价值更高
宏观经济波动与叙事之间存在相互强化的循环：公众话语可引发行为变化导致经济变动，而经济变化又重塑传播中的故事。我们证明语义嵌入空间的变动可被因果关联到金融市场的异常波动（即偏离预期的表现）。此外，我们发现政治立场会影响文本对市场波动的预测能力，并塑造对相同冲击的反应。在新冠疫情等突发事件中，基于文本的信号尤为显著，凸显语言数据作为经济预测外生变量的价值。研究揭示了新闻媒体与市场冲击之间的双向关系，为二者相互作用提供了新的实证方法。
原文摘要 · Abstract (English)
Macroeconomic fluctuations and the narratives that shape them form a mutually reinforcing cycle: public discourse can spur behavioural changes leading to economic shifts, which then result in changes in the stories that propagate. We show that shifts in semantic embedding space can be causally linked to financial market shocks -- deviations from the expected market behaviour. Furthermore, we show how partisanship can influence the predictive power of text for market fluctuations and shape reactions to those same shocks. We also provide some evidence that text-based signals are particularly salient during unexpected events such as COVID-19, highlighting the value of language data as an exogenous variable in economic forecasting. Our findings underscore the bidirectional relationship between news outlets and market shocks, offering a novel empirical approach to studying their effect on each other.
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