Results 11 to 20 of about 447 (86)
Dependent defaults and losses with factor copula models
Dependence Modeling, 2017 We present a class of flexible and tractable static factor models for the term structure of joint default probabilities, the factor copula models. These high-dimensional models remain parsimonious with paircopula constructions, and nest many standard ...
Ackerer Damien, Vatter Thibault
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Measures of concordance determined by D4‐invariant copulas
International Journal of Mathematics and Mathematical Sciences, Volume 2004, Issue 70, Page 3867-3875, 2004., 2004 A continuous random vector (X, Y) uniquely determines a copula C : [0, 1] 2 → [0, 1] such that when the distribution functions of X and Y are properly composed into C, the joint distribution function of (X, Y) results. A copula is said to be D4‐invariant if its mass distribution is invariant with respect to the symmetries of the unit square.
H. H. Edwards +2 more
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Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas
Dependence Modeling, 2018 Previous research has focused on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, existing dynamic models are not easily applied to high-dimensional problems due to the curse ...
Jin Xisong, Lehnert Thorsten
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Moments tensors, Hilbert's identity, and k-wise uncorrelated random variables [PDF]
, 2014 In this paper, we introduce a notion to be called k-wise uncorrelated random variables, which is similar but not identical to the so-called k-wise independent random variables in the literature.
He, Simai +3 more
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Probabilistic derivation of a bilinear summation formula for the Meixner‐Pollaczek polynominals
International Journal of Mathematics and Mathematical Sciences, Volume 3, Issue 4, Page 761-771, 1980., 1980 Using the technique of canonical expansion in probability theory, a bilinear summation formula is derived for the special case of the Meixner‐Pollaczek polynomials which are defined by the generating function These polynomials satisfy the orthogonality condition with respect to the weight function
P. A. Lee
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Inference for copula modeling of discrete data: a cautionary tale and some facts
Dependence Modeling, 2017 In this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula ...
Faugeras Olivier P.
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Multivariate medial correlation with applications
Dependence Modeling, 2020 We define a multivariate medial correlation coefficient that extends the probabilistic interpretation and properties of Blomqvist’s β coefficient, incorporates multivariate marginal dependencies and it preserves a partial ordering stronger than ...
Ferreira Helena, Ferreira Marta
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Copula modeling for discrete random vectors
Dependence Modeling, 2020 Copulas have now become ubiquitous statistical tools for describing, analysing and modelling dependence between random variables. Sklar’s theorem, “the fundamental theorem of copulas”, makes a clear distinction between the continuous case and the ...
Geenens Gery
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Portfolio selection based on graphs: Does it align with Markowitz-optimal portfolios?
Dependence Modeling, 2018 Some empirical studies suggest that the computation of certain graph structures from a (large) historical correlation matrix can be helpful in portfolio selection.
Hüttner Amelie +2 more
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Optimizing effective numbers of tests by vine copula modeling
Dependence Modeling, 2020 In the multiple testing context, we utilize vine copulae for optimizing the effective number of tests. It is well known that for the calibration of multiple tests for control of the family-wise error rate the dependencies between the marginal tests are ...
Steffen Nico, Dickhaus Thorsten
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