The t Copula and Related Copulas

By S. Demarta, Alexander J. McNeil. 2005

1,057 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d100be4b508bd3f3498ec28d9ef16c1f68e8f73b

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Citations in the corpus

RANK-BASED INFERENCE FOR BIVARIATE EXTREME-VALUE COPULAS (2007, neutral): “(g) The t-EV model [Demarta and McNeil (2005)], in which A(w) = wtχ+1(zw) + (1−w)tχ+1(z1−w), zw = (1 + χ) 1/2[{w/(1−w)}1/χ − ρ](1− ρ2)−1/2 with parameters χ > 0 and ρ ∈ (−1,1), where tχ+1 is the distribution function of a Student-t random variable with χ+ 1 degrees of freedom.”
A review of copula models for economic time series (2012, methodology): “McNeil et al. [110] contains an overview of copula methods in the context of risk management, as does Denuit et al. [43].”
Asymptotic Results for the Sum of Dependent Non-identically Distributed Random Variables (2009, methodology): “First, we calculate the t-extremevalue copula (for the bivariate case a different representation can be found in [11]).”
Generation and evaluation of space–time trajectories of photovoltaic power (2016, background): “, F̂ −1 D (UD)) (8) The formulation for Gaussian, T and Gumbel copulas can be found in [28, 29].”
Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures (2016, methodology): “One possibility is to choose the distribution of R(2) as the inverse-gamma distribution with rate and shape parameters equal to Df/2, yielding Student-t random fields with Df > 0 degrees of freedom (Røislien and Omre, 2006; Demarta and McNeil, 2005) and converging to the Gaussian limit as Df → ∞.”
Goodness-of-fit tests for parametric families of Archimedean copulas (2008, background): “These are Air yFor the Gaussian and t-copulas the correlation coefficient (in standard notation) is ¼ sin( /2)¼ 0.4540 (Demarta and McNeil 2005).”
Multivariate autoregressive modeling of time series count data using copulas (2007, methodology): “We use the continued extension argument proposed by Denuit and Lambert (2005) to overcome these difficulties and apply copulas with discrete marginals.”
Extreme value copulas and max-stable processes (2013, background): “Two other parametric extreme value copulas that do not suffer from this drawback are the extremal-t and Hüsler–Reiss copulas [18, 9].”
Portfolio optimization for student t and skewed t returns (2010, methodology): “Skewed t distribution If 1⁄4 /2, 1⁄4 and 1⁄4 0, we obtain a limiting case which is called the skewed t distribution by Demarta and McNeil (2005), because it generalizes the Student t distribution, obtained from the skewed t by setting the skewness parameter c1⁄4 0.”
A new copula approach for high-dimensional real world portfolios (2012, methodology): “(5)Dividing by (T + 1) rather than by T is an approach that has been proposed by Demarta and McNeil [12].”