COVID-19, stock market and sectoral contagion in US: a time-frequency analysis

Paulo Matos, Antonio Costa and Cristiano da Silva

Research in International Business and Finance, 2021, vol. 57, issue C

Abstract: We assess the conditional relationship in the time-frequency domain between the return on S&P 500 and confirmed cases and deaths by COVID-19 in Hubei, China, countries with record deaths and the world, for the period from January 29 to June 30, 2020. Methodologically, we follow Aguiar-Conraria et al. (2018), by using partial coherencies, phase-difference diagrams, and gains. We also perform a parametric test for Granger-causality in quantiles developed by Troster (2018). We find that short-term cycles of deaths in Italy in the first days of March, and soon afterwards, cycles of deaths in the world are able to lead out-of-phase US stock market. We find that low frequency cycles of the US market index in the first half of April are useful to anticipate in an anti-phasic way the cycles of deaths in the US. We also explore sectoral contagion, based on dissimilarities, Granger causality and partial coherencies between S&P sector indices. Our findings, such as the strategic role of the energy sector, which first reacted to the pandemic, or the evidence about predictability of the Telecom cycles, are useful to tell the history of the pass-through of this recent health crises across the sectors of the US economy.

Keywords: Coronavirus; Lead-lag conditional relationships; Time-frequency domains; Quantile Granger causality; Sectoral pass-through in US (search for similar items in EconPapers)
JEL-codes: C63 G12 H12 O16 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:57:y:2021:i:c:s0275531921000210

DOI: 10.1016/j.ribaf.2021.101400

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