This study attempts to analyze the time-varying pattern between the exchange rates, stock market return, temperature, and number of confirmed COVID-19 cases in G7 countries caused by the COVID-19 pandemic. We have implemented our analysis using wavelet coherence and partial wavelet coherence (PWC) on independent variables from January 4, 2021 to July 31, 2021. This paper contributes to the earlier work on the same subject by employing wavelet coherence to analyze the effect of the sudden upsurge of the COVID-19 pandemic on exchange rates, stock market returns, and temperature to sustain and improve previous results regarding correlation analysis between the above-mentioned variables. We arrived at the following results: 1) temperature levels and confirmed COVID-19 cases are cyclical indicating daily temperatures have a material bearing on propagating the novel coronavirus in G7 nations;2) noteworthy correlations at truncated frequencies show that a material long-term impact has been observed on exchange rates and stock market returns of G7 and confirmed COVID-19 cases;3) accounting for impact of temperature and equity market returns, a more robust co-movement is observed between the exchange rate returns of the respective nations and the surge in COVID-19 cases;and 4) accounting for the influence of temperature and exchange rate returns and the increase in the confirmed number of coronavirus-infected cases and equity returns, co-movements are more pronounced. Besides academic contributions, this paper offers insight for policymakers and investment managers alike in their attempt to navigate the impediments created by the coronavirus in their already arduous task of shaping the economy and predicting stock market patterns. Copyright © 2021 Singh, Bansal, Bhardwaj and Agrawal.
Nexus Between COVID-19 Infections, Exchange Rates, Stock Market Return, and Temperature in G7 Countries: Novel Insights From Partial and Multiple Wavelet Coherence