COVID-19 Intensity, Resilience, and Expected Returns

Elham Daadmehr

Risks, 2025, vol. 13, issue 3, 1-19

Abstract: This paper provides a model to interpret the relative behavior of expected returns of high- and low-resilience assets from the time of the COVID-19 pandemic, including a novel definition of disaster based on COVID-19 intensity. The setup allows us to disentangle the probability of disaster and investors’ updating probability at each point in time which sheds light on how long-memory investors react to disaster risk and play a role in future prices. The theoretical results show higher revisions in expected return differentials in the case of any perception of a higher possibility of disaster or, equivalently, higher COVID-19 intensity. The intensity of COVID-19 can directly exacerbate the heterogeneity in expected returns for high- and low-resilience assets and their corresponding differentials. More importantly, an increase in COVID-19 intensity increases the expected returns of low-resilience assets more than those of high-resilience ones.

Keywords: intensity of disaster; Poisson distribution; investors’ learning; workplace resilience; expected returns; COVID-19 crisis (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-9091/13/3/60/pdf (application/pdf)
https://www.mdpi.com/2227-9091/13/3/60/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:13:y:2025:i:3:p:60-:d:1616519

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().