Granger Causality in Risk and Detection of Extreme Risk Spillover Between Financial Markets

By Yongmiao Hong, Yanhui Liu, Shouyang Wang. 2009

355 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/91fe4d2986c36743740168927ca4a022d76eb964

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Citations in the corpus

Testing for Granger-causality in quantiles (2018, methodology): “Regarding nonparametric approaches, Hong et al. (2009) proposed a nonparametric test of causality in Value-at-Risk (VaR), but their method provides only a necessary condition for Granger-causality.”
Risk spillovers between FinTech and traditional financial institutions: Evidence from the U.S. (2020, neutral): “As a multivariate extension of the Granger causality in risk (Hong et al., 2009), which is commonly utilized to estimate extreme risk spillover (see e.”
A CONSISTENT NONPARAMETRIC TEST FOR CAUSALITY IN QUANTILE (2012, background): “These are important for risk management and portfolio/investment diversification (Hong, Liu, and Wang, 2009).”
A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion (2014, background): “More recent contributions have focused on the concept of Granger causality in quantiles, a particularly important issue for non-Gaussian distributions that exhibit asymmetry, fat-tail characteristics, and nonlinearity (Lee and Yang 2012; Jeong, Härdle, and Song 2012).”
Granger Causality: A Review and Recent Advances (2021, methodology): “In spite of their limitations, bivariate tests of Granger causality have been widely used in many application areas, from economics (Chiou-Wei et al., 2008) and ﬁnance (Hong et al., 2009) to neuroscience (Seth et al., 2015) and meteorology (Mosedale et al., 2006).”
The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series (2014, neutral): “In the absence of dynamic misspecification, which is assumed in Hong et al. (2009) under their null hypothesis, the analysis becomes substantially simple because each hit-process {ψτi(y − qi,t(τi))} is a sequence of iid Bernoulli random variables.”
Causality in quantiles and dynamic stock return–volume relations (2009, methodology): “conventional tests of non-causality in a moment and the tests of Lee and Yang (2006) and Hong, Liu, and Wang (2006) .”
Extreme risk spillovers between crude oil and stock markets (2015, methodology): “The nature of causality relations at the risk level is examined by the econometric method developed by Hong et al. (2009).”
Extreme risk spillover network: application to financial institutions (2017, methodology): “Following Hong et al. (2009), we use the asymmetric slope model to estimate the VaR of each financial institution when its DQ statistic is significant at the 1% level.”