叙述对标准普尔500指数预测的好处

Pascal Blanqué, M. Slimane, Amina Cherief, Théo Le Guenedal, Takaya Sekine, Lauren Stagnol
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引用次数: 1

摘要

在本文中,作者表明,来自全球事件、语言和语气数据库的变量传达了重要信息,可以在对美国股市建模时改进纯宏观经济方法。基于这些指标,作者构建了时间序列,以表示和衡量在当前市场环境中一些看似相互竞争的叙事是如何变化的。具体来说,作者评估了繁荣的20年代、回到70年代、长期停滞和货币经济叙事的力量,但他们也增加了与环境或社会方面相关的社会话题叙事,以及地缘政治风险叙事。作者形式化了一个信息内容框架,并表明,在确定股市走势时,包括转化为定性故事的定量信号带来了附加价值。事实上,除了对其潜在变量具有更高的解释力之外,叙事还可以改善标准宏观经济模型的多样化。因此,作者的研究结果提倡对金融市场的叙事进行密切监控。
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The Benefit of Narratives for Prediction of the S&P 500 Index
In this article, the authors show that variables from the Global Database of Events, Language, and Tone convey significant information that can improve on a purely macroeconomic approach when modeling the US equity market. Based on these metrics, the authors construct time series that represent and measure how some narratives that appear to be battling each other are changing in the current market environment. Specifically, the authors appraise the strength of the roaring 20s, back to the 70s, secular stagnation, and monetary economic narratives, but they also add topical societal narratives related to environmental or social aspects and a geopolitical risk narrative. The authors formalize an information content framework and show that including quantitative signals that translate into qualitative stories brings added value when determining the stock market’s movement. Indeed, in addition to having higher explanatory power from their underlying variables, narratives can improve the diversification of standard macroeconomic models. As such, the authors’ results advocate a close monitoring of narratives in financial markets.
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