Tail Dependence for Heavy-Tailed Scale Mixtures of Multivariate Distributions
By Haijun Li, Yannan Sun. Journal of Applied Probability, 2009
48 citations recorded by the source corpus.
Subfields: Finance, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a32f13ed833167b531605a931c5423fe4b8edec3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- L. Zhu
- Haijun Li
- Harry Joe
- Aristidis K. Nikoloulopoulos
- Claudia Czado
- Eike C. Brechmann
- Yannan Sun
- Ingrid Hobæk Haff
In Statistics and Probability
- Harry Joe
- L. Zhu
- Haijun Li
- Aristidis K. Nikoloulopoulos
- Claudia Czado
- Chandra R. Bhat
- Eike C. Brechmann
- Mohsen Pourahmadi
Citations in the corpus
- Asymptotic Analysis of Multivariate Tail Conditional Expectations (2012, methodology): “A multivariate regular variation method based on the tail dependence function (see Joe et al. 2010; Li and Sun 2009) was developed in Joe and Li (2011) to derive tractable asymptotic bounds for multivariate TCEs, but these bounds are expressed in terms of univariate integrals of tail dependence…”
- Tail Risk of Multivariate Regular Variation (2011, background): “Unlike λU , however, the tail dependence function provides all the extremal dependence information [29, 18, 26].”