A CONSISTENT NONPARAMETRIC TEST FOR CAUSALITY IN QUANTILE

By Kiho Jeong, Wolfgang Karl Härdle. Econometric Theory, 2012

447 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/00f4985f86eb78d173b1ad6855c169574896c854

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Citations in the corpus

Geopolitical Risks and Movements in Islamic Bond and Equity Markets: A Note (2019, background): “In an extension of Jeong, Härdle, and Song (2012)’s framework, Balcilar, Bekiros, and Gupta (2016) also develop a test for the second moment.”
Extreme risk spillovers between crude oil and stock markets (2015, background): “If the distributions involved are fat tailed as is to be expected with financial returns, a tail area relation may be quite different (Jeong et al., 2012).”
Geopolitical risks and stock market dynamics of the BRICS (2018, methodology): “Jeong et al., (2012) show that the feasible kernel-based sample analog of J has the following form:”
The marginal impacts of energy prices on carbon price variations: Evidence from a quantile-on-quantile approach (2021, unknown): “Then our strategy will be to draw upon these results to lend a detailed comparison with ours, be it with regard to the market period under consideration, the estimation method and the theoretical explanation, in a threefold manner.”
The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method (2017, methodology): “Jeong et al. (2012) specify the distance function as follows:”
Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test (2015, methodology): “The causality-in-quantiles test that we employ in this paper, combines the frameworks of k-th order causality of Nishiyama et al. (2011) and quantile causality of Jeong et al. (2012), and hence, can be considered to be a more general version of the former.”
Does Uncertainty Move the Gold Price? New Evidence from a Nonparametric Causality-in-Quantiles Test (2016, methodology): “Jeong et al. (2012) specify the distance function as follows:”
Testing for Granger-causality in quantiles (2018, methodology): “Jeong et al. (2012) extended the idea of Zheng (1998) to transform conditional quantile restrictions into conditional mean restrictions to testing causality in quantiles; more recently, Taamouti et al. (2014) proposed a nonparametric test for conditional density based Granger-causality.”
A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion (2014, background): “The VaR of an instrument or a portfolio of instruments is the maximum dollar loss within the α%-confidence interval (Jorion 2007).”