COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic - Rennes School of Business Access content directly
Journal Articles Digital Finance Year : 2022

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

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.

Dates and versions

hal-04021587 , version 1 (09-03-2023)

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Yuting Chen, Don Bredin, Valerio Potì, Roman Matkovskyy. COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic. Digital Finance, 2022, 4 (1), pp.17-61. ⟨10.1007/s42521-021-00045-3⟩. ⟨hal-04021587⟩
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