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Semi-Parametric Models for the Multivariate Tail Dependence Function - the Asymptotically Dependent Case
by
PENG, LIANG
, KUHN, GABRIEL
, KLÜPPELBERG, CLAUDIA
in
Applications
/ asymptotic normality
/ Credit risk
/ dependence modelling
/ elliptical copula
/ elliptical distribution
/ Estimators
/ Exact sciences and technology
/ General topics
/ Insurance, economics, finance
/ Mathematical functions
/ Mathematics
/ Matrices
/ Probability and statistics
/ regular variation
/ Risk management
/ Sciences and techniques of general use
/ semi-parametric model
/ Semiparametric modeling
/ Sine function
/ Statistical discrepancies
/ Statistical theories
/ Statistics
/ tail dependence function
/ Weighting functions
2008
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Semi-Parametric Models for the Multivariate Tail Dependence Function - the Asymptotically Dependent Case
by
PENG, LIANG
, KUHN, GABRIEL
, KLÜPPELBERG, CLAUDIA
in
Applications
/ asymptotic normality
/ Credit risk
/ dependence modelling
/ elliptical copula
/ elliptical distribution
/ Estimators
/ Exact sciences and technology
/ General topics
/ Insurance, economics, finance
/ Mathematical functions
/ Mathematics
/ Matrices
/ Probability and statistics
/ regular variation
/ Risk management
/ Sciences and techniques of general use
/ semi-parametric model
/ Semiparametric modeling
/ Sine function
/ Statistical discrepancies
/ Statistical theories
/ Statistics
/ tail dependence function
/ Weighting functions
2008
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Do you wish to request the book?
Semi-Parametric Models for the Multivariate Tail Dependence Function - the Asymptotically Dependent Case
by
PENG, LIANG
, KUHN, GABRIEL
, KLÜPPELBERG, CLAUDIA
in
Applications
/ asymptotic normality
/ Credit risk
/ dependence modelling
/ elliptical copula
/ elliptical distribution
/ Estimators
/ Exact sciences and technology
/ General topics
/ Insurance, economics, finance
/ Mathematical functions
/ Mathematics
/ Matrices
/ Probability and statistics
/ regular variation
/ Risk management
/ Sciences and techniques of general use
/ semi-parametric model
/ Semiparametric modeling
/ Sine function
/ Statistical discrepancies
/ Statistical theories
/ Statistics
/ tail dependence function
/ Weighting functions
2008
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Semi-Parametric Models for the Multivariate Tail Dependence Function - the Asymptotically Dependent Case
Journal Article
Semi-Parametric Models for the Multivariate Tail Dependence Function - the Asymptotically Dependent Case
2008
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Overview
In general, the risk of joint extreme outcomes in financial markets can be expressed as a function of the tail dependence function of a high-dimensional vector after standardizing marginals. Hence, it is of importance to model and estimate tail dependence functions. Even for moderate dimension, non-parametrically estimating a tail dependence function is very inefficient and fitting a parametric model to tail dependence functions is not robust. In this paper, we propose a semi-parametric model for (asymptotically dependent) tail dependence functions via an elliptical copula. Under this model assumption, we propose a novel estimator for the tail dependence function, which proves favourable compared to the empirical tail dependence function estimator, both theoretically and empirically.
Publisher
Blackwell Publishing Ltd,Blackwell Publishing,Blackwell,Danish Society for Theoretical Statistics
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