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Cited by 20 publications
(14 citation statements)
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“…Aharon et al ( 2021 ) also study the dynamic connectedness between the US TSIR (considering all three components), bitcoin and safe-haven currencies, highlighting the role of bitcoin as a safe-haven asset, especially in periods of economic turbulence. Another paper that examines time-varying spillovers between the different components of the G7 countries’ yield curves is that of Aharon et al ( 2022 ), using the coronavirus MCI index. Interestingly, the methodology used allows distinguishing between risk-sending and risk-receiving countries in terms of connectedness measures, which also has relevant implications for portfolio managers.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Aharon et al ( 2021 ) also study the dynamic connectedness between the US TSIR (considering all three components), bitcoin and safe-haven currencies, highlighting the role of bitcoin as a safe-haven asset, especially in periods of economic turbulence. Another paper that examines time-varying spillovers between the different components of the G7 countries’ yield curves is that of Aharon et al ( 2022 ), using the coronavirus MCI index. Interestingly, the methodology used allows distinguishing between risk-sending and risk-receiving countries in terms of connectedness measures, which also has relevant implications for portfolio managers.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The previous literature on the relationship between WPU and commodity prices set the WPU impact either on a global scale [e.g., ( 16 )] or at a regional level, such as the United States ( 17 ), Europe ( 18 ), G7 ( 19 ), and the BRICS ( 20 ). In the selection of commodity indices, these researchers tend to use the BCOM index, which is more suitable for studying the fluctuations in the global commodity prices [e.g., ( 21 )].…”
Section: Related Workmentioning
confidence: 99%
“…The first approach used the bivariate GARCH family models to estimate the coefficients of cross-term in the mean equation and variance-covariance equation of these models to examine the return spillover and volatility spillover between two assets by using the significant situation of coefficients [see ( 1 7 , 9 , 12 , 14 , 18 23 ) and so on]. 11 The second approach used the time-varying parameter vector autoregression (TVP-VAR) methodology, which extends the connectedness work of Diebold and Yilmaz ( 38 ), to calculate the net total directional connectedness for each asset within a group of assets to determine whether this asset is a net transmitter or a net receiver on return or risk by using the value of net total directional connectedness being positive or negative [see ( 13 , 25 31 )]. However, this approach can't determine whether the spillover is significant or not and whether the spillover is positive or negative.…”
Section: Literature Reviewmentioning
confidence: 99%
“… 10 Even though, this study uses a model with two time-dummy variables to explore the impact of the COVID-19 pandemic on the interaction issues. As shown in Table 2B , there are still some kinds of literature investigating the impact of the COVID-19 pandemic on the spillover or correlation issues by using RavenPack Coronavirus Media Coverage Index or Ravenpack Coronavirus Panic Index ( 25 , 27 32 , 34 ). In addition, Zaremba et al ( 24 ) evaluated the impact of COVID-19 on the term spreads of bonds by using the change in the number of COVID-19 infections.…”
mentioning
confidence: 99%