Unconditional and conditional analysis between covid-19 cases, temperature, exchange rate and stock markets using wavelet coherence and wavelet partial coherence approaches.

ABSTRACT: This paper examines the time-frequency relationship between the number of confirmed COVID-19 cases, temperature, exchange rates and stock market return in the top-15 most affected countries by the COVID-19 pandemic. We employ Wavelet Coherence and Partial Wavelet Coherence on the daily data from 1st February, 2020 to 13th May, 2020. This study adds to the literature by implementing the Wavelet Coherence technique to explore the unexpected outbreak effects of the global pandemic on temperature, exchange rates and stock market returns. Our results reveal (i) there is evidence of cyclicality between temperature and COVID-19 cases, implying that average daily temperature has a significant impact on the spread of the COVID-19 disease in most of the countries; (ii) strong connectedness at low fr

SUBMITTER: Sharma GD 

PROVIDER: S-EPMC7868636 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature