COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic

Yuting Chen, Don Bredin, Valerio Potì and Roman Matkovskyy
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Yuting Chen: ESC [Rennes] - ESC Rennes School of Business, UCD - University College Dublin [Dublin]

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Abstract: In this paper, we study the role of narratives in stock markets with a particular focus on the relationship with the ongoing COVID-19 pandemic. The pandemic represents a natural setting for the development of viral financial market narratives. We thus treat the pandemic as a natural experiment on the relation between prevailing narratives and financial markets. We adopt natural language processing (NLP) on financial news to characterize the evolution of important narratives. Doing so, we reduce the high-dimensional narrative information to few interpretable and important features while avoiding over-fitting.

Date: 2022-03
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Published in Digital Finance, 2022, 4 (1), pp.17-61. ⟨10.1007/s42521-021-00045-3⟩

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Journal Article: COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04021587

DOI: 10.1007/s42521-021-00045-3

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