Big data, news diversity and financial market crash

Sabri Boubaker, Zhenya Liu and Ling Zhai
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Zhenya Liu: CERGAM - Centre d'Études et de Recherche en Gestion d'Aix-Marseille - AMU - Aix Marseille Université - UTLN - Université de Toulon, Renmin University of China = Université Renmin de Chine
Ling Zhai: Renmin University of China = Université Renmin de Chine

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Abstract: A vast quantity of high-dimensional, unstructured textual news data is produced every day, more than two decades after the launch of the global Internet. These big data have a significant influence on the way that decisions are made in business and finance, due to the cost, scalability, and transparency benefits that they bring. However, limited studies have fully exploited big data to analyze changes in news diversity or to predict financial market movements, specifically stock market crashes. Based on modern methods of textual analysis, this paper investigates the relationship between news diversity and financial market crashes by applying the change-point detection approach. The empirical analysis shows that (1) big data is a relatively new and useful tool for assessing financial market movements, (2) there is a relationship between news diversity and financial market movements. News diversity tends to decline when the market falls and volatility soars, and increases when the market is on an upward trend and in recovery, and (3) the multiple structural breaks detected improve the ability to forecast stock price movements. Therefore, changes to news diversity, embedded in big data, can be a useful indicator of financial market crashes and recoveries.

Keywords: Big data; News diversity; Textual analysis; Change-point; Financial crisis (search for similar items in EconPapers)
Date: 2021-07
New Economics Papers: this item is included in nep-big, nep-des, nep-pay and nep-sea
Note: View the original document on HAL open archive server: https://hal.science/hal-03511405v1
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Citations: View citations in EconPapers (7)

Published in Technological Forecasting and Social Change, 2021, 168, pp.120755. ⟨10.1016/j.techfore.2021.120755⟩

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Journal Article: Big data, news diversity and financial market crash (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03511405

DOI: 10.1016/j.techfore.2021.120755

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