2020
DOI: 10.1080/1331677x.2020.1860796
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Dynamic spillovers and connectedness between COVID-19 pandemic and global foreign exchange markets

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Cited by 48 publications
(49 citation statements)
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“…Therefore, COVID-19 has become a grave concern for the world population and economies. The adverse impacts of pandemics, epidemics, economic crisis, a natural disaster on different macroeconomic variables is not a new phenomenon, and numerous literature supports it, for example, Fasanya et al (2020); McKibbin and Fernando (2020); and Shaikh (2020).…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, COVID-19 has become a grave concern for the world population and economies. The adverse impacts of pandemics, epidemics, economic crisis, a natural disaster on different macroeconomic variables is not a new phenomenon, and numerous literature supports it, for example, Fasanya et al (2020); McKibbin and Fernando (2020); and Shaikh (2020).…”
Section: Introductionmentioning
confidence: 99%
“…The results show the importance of essential categories for rethinking the workplace after COVID-19 and for the whole process of change in the workplace (de Lucas Ancillo et al 2020 ). The service industry also suffers impacts from global foreign exchange markets volatility and uncertainty (Fasanya et al 2020 ). This study searches to determine the connectedness and spillover effects of COVID-19 currency pairs around the world.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Katusiime (2019) evaluated the spillover effects between foreign exchanges and found conditional volatility among currency rates and commodity price in Uganda. Most recently, Fasanya et al (2020) investigated the dynamic spillovers and connectedness between the COVID-19 pandemic and global foreign exchange markets. They found a high degree of interdependence between the global COVID-19 occurrences and the returns' volatility of the majorly traded currency pairs.…”
Section: Related Literaturementioning
confidence: 99%
“…In this paper, we have based our measurements of return and volatility spillovers on vector autoregressive (VAR) models, which have been laid out in recent studies Palanska (2018), Mensi et al (2018), andFasanya et al (2020). As compared with other methodologies such as MGARCH and the realised volatility (RV) estimator, the VAR provides strikingly accurate results using high-frequency data.…”
Section: Related Literaturementioning
confidence: 99%