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Tail Copula Estimation for Heteroscedastic Extremes
John Einmahl
, C. Zhou
Econometrics and OR
Research Group: Econometrics
Research output
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Working paper
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Discussion paper
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Other research output
149
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Dive into the research topics of 'Tail Copula Estimation for Heteroscedastic Extremes'. Together they form a unique fingerprint.
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Keyphrases
Bivariate
100%
Random Vector
100%
Heteroscedastic Extremes
100%
Tail Copula Estimation
100%
Tail Dependence Coefficient
100%
Marginal Distribution
50%
Tail Dependence
50%
S&P 500
50%
Heteroscedastic
50%
Nonparametric Test
50%
Asymptotic Normality
50%
Copula
50%
Tail Copula
50%
Finite Sample
50%
Non-stationarity
50%
Rank-based Estimator
50%
Stable Tail Dependence Function
50%
Detailed Simulation
50%
Dow Jones Index
50%
Asymptotic Confidence Interval
50%
Mathematics
Marginals
100%
Copula
100%
Bivariate
66%
Random Vector
66%
Marginal Distribution
33%
Nonparametric Test
33%
Asymptotic Normality
33%
Stationarity
33%
Tail Dependence Function
33%
Dow Jones Index
33%
Asymptotic Confidence Interval
33%