2015
DOI: 10.1016/j.physa.2015.02.017
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Abstract: The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2 nd January 2006 to 31 st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-samples revealed three significant findings.First, after the recent financial crisis the impact of the US stock market has declined. Second, spatial probit models confirmed the role of the temp… Show more

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Cited by 100 publications
(59 citation statements)
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“…Especially with respect to performing the Granger causality test, caution must be exercised because information sets must be precisely aligned with respect to time. Our return alignment procedure follows Výrost et al [19], which we briefly summarize below: 3 (1) Closing prices for two stock markets are pairwise synchronized; i.e., when there is a missing observation (non-trading day) on one market, observations corresponding to this day on the other market are deleted. (2) Consecutive returns are computed, which means that returns over non-trading days during the week are excluded.…”
Section: Data Description and Return Alignment Proceduresmentioning
confidence: 99%
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“…Especially with respect to performing the Granger causality test, caution must be exercised because information sets must be precisely aligned with respect to time. Our return alignment procedure follows Výrost et al [19], which we briefly summarize below: 3 (1) Closing prices for two stock markets are pairwise synchronized; i.e., when there is a missing observation (non-trading day) on one market, observations corresponding to this day on the other market are deleted. (2) Consecutive returns are computed, which means that returns over non-trading days during the week are excluded.…”
Section: Data Description and Return Alignment Proceduresmentioning
confidence: 99%
“…Attention has been paid by the researchers to the equity and stock markets (Güloğlu et al [17]; Boubaker and Ali Raza [18]; Výrost et al [19]; Al Rahahleh and Bhatti [20]; Liu et al [21]) as well as to commodity markets (Ji and Guo [22]; Lahmiri [23]). Additional evidence has been put forward for spillovers between spot and futures markets (Liu and Wang [24]; Kang et al [25]) or spot and derivative markets (Kim and Ryu [26]).…”
Section: Introduction: Motivation Related Literature and Contributionmentioning
confidence: 99%
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“…(2010) considered networks wherein only correlations above a threshold value were used, as topological constraints in MST and PMFG have unclear statistical and economic meaning (Výrost et al, 2015). We therefore also considered threshold networks where only edges that were statistically significant remained in the network.…”
Section: Threshold Significance Graphmentioning
confidence: 99%
“…Rec [2009] scrutinizes the financial integration of stock markets in the former Yugoslav countries. Finally Vyrost, Lyocsa, and Baumohl [2014] analyze Granger causality networks constructed amongst 20 developed stock markets.…”
Section: Literature Reviewmentioning
confidence: 99%