Results 51 to 60 of about 2,569,963 (324)
Tail-event driven NETwork dependence in emerging markets
Emerging Markets Review, 2022 This paper employs the Tail Event NETwork (TENET) to identify financial markets with greater potential risk, and simultaneously investigate the interdependence between them.
M. Naeem +4 more
semanticscholar +1 more source
A Euclidean likelihood estimator for bivariate tail dependence [PDF]
, 2012 The spectral measure plays a key role in the statistical modeling of multivariate extremes. Estimation of the spectral measure is a complex issue, given the need to obey a certain moment condition.
de Carvalho, Miguel +3 more
core +2 more sources
Tail Dependence for Heavy-Tailed Scale Mixtures of Multivariate Distributions [PDF]
Journal of Applied Probability, 2009 The tail dependence of multivariate distributions is frequently studied via the tool of copulas. In this paper we develop a general method, which is based on multivariate regular variation, to evaluate the tail dependence of heavy-tailed scale mixtures of multivariate distributions, whose copulas are not explicitly accessible.
Li, Haijun, Sun, Yannan
openaire +2 more sources
A Note on Upper Tail Behavior of Liouville Copulas
Risks, 2016 The family of Liouville copulas is defined as the survival copulas of multivariate Liouville distributions, and it covers the Archimedean copulas constructed by Williamson’s d-transform.
Lei Hua
doaj +1 more source
PATHS AND INDICES OF MAXIMAL TAIL DEPENDENCE [PDF]
ASTIN Bulletin, 2014 AbstractWe demonstrate both analytically and numerically that the existing methods for measuring tail dependence in copulas may sometimes underestimate the extent of extreme co-movements of dependent risks and, therefore, may not always comply with the new paradigm of prudent risk management.
Edward Furman +2 more
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On the tail dependence in bivariate hydrological frequency analysis
Dependence Modeling, 2015 In Bivariate Frequency Analysis (BFA) of hydrological events, the study and quantification of the dependence between several variables of interest is commonly carried out through Pearson’s correlation (r), Kendall’s tau (τ) or Spearman’s rho (ρ).
Lekina Alexandre +2 more
doaj +1 more source
Robust Learning of Tail Dependence
EconometricsAccurate estimation of tail dependence is difficult due to model misspecification and data contamination. This paper introduces a class of minimum f-divergence estimators for the tail dependence coefficient that unifies robust estimation with extreme ...
Omid M. Ardakani
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An Analysis of a Heuristic Procedure to Evaluate Tail (in)dependence
Journal of Probability and Statistics, 2014 Measuring tail dependence is an important issue in many applied sciences in order to quantify the risk of simultaneous extreme events. A usual measure is given by the tail dependence coefficient.
Marta Ferreira, Sérgio Silva
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A Note on Tail Dependence Regression
SSRN Electronic Journal, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Qingzhao +2 more
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Power-Law Distributions from Sigma-Pi Structure of Sums of Random Multiplicative Processes
Entropy, 2017 We introduce a simple growth model in which the sizes of entities evolve as multiplicative random processes that start at different times. A novel aspect we examine is the dependence among entities.
Arthur Matsuo Yamashita Rios de Sousa +3 more
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