Even though the global contagion effects of the financial crisis have been well documented, the transmission mechanism as well as the nature of the volatility spillovers among the US, the EU and the BRIC markets has not been systematically investigated. To examine the dynamic linear and nonlinear causal linkages a stepwise filtering methodology is introduced, for which vector autoregressions and various multivariate GARCH representations are adopted. The sample covers the after-Euro period and includes the financial crisis and the Eurozone debt crisis. The empirical results show that the BRICs have become more internationally integrated after the US financial crisis and contagion is further substantiated. Moreover, no consistent evidence in support of the "decoupling" view is found. Some nonlinear causal links persist after filtering during the examined period. This indicates that nonlinear causality can, to a large extent, be explained by simple volatility effects, although tail dependency and higher-moments may be significant factors of the remaining interdependencies.

Contagion, Decoupling and the Spillover Effects of the US Financial Crisis: Evidence from the BRIC Markets

BEKIROS S
2014-01-01

Abstract

Even though the global contagion effects of the financial crisis have been well documented, the transmission mechanism as well as the nature of the volatility spillovers among the US, the EU and the BRIC markets has not been systematically investigated. To examine the dynamic linear and nonlinear causal linkages a stepwise filtering methodology is introduced, for which vector autoregressions and various multivariate GARCH representations are adopted. The sample covers the after-Euro period and includes the financial crisis and the Eurozone debt crisis. The empirical results show that the BRICs have become more internationally integrated after the US financial crisis and contagion is further substantiated. Moreover, no consistent evidence in support of the "decoupling" view is found. Some nonlinear causal links persist after filtering during the examined period. This indicates that nonlinear causality can, to a large extent, be explained by simple volatility effects, although tail dependency and higher-moments may be significant factors of the remaining interdependencies.
2014
33
58
69
Filtering; GJR-GARCH; Multivariate GARCH models; Nonlinear causality; Spillovers; Stock markets
BEKIROS S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1913871
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