In this paper, we consider nonparametric copula inference under bivariate censoring. Based on an estimator of the joint cumulative distribution function, we define a discrete and two smooth estimators of the copula. The construction that we propose is valid for a large number of estimators of the distribution function, and therefore for a large number of bivariate censoring frameworks. Under so...

By a theorem due to Sklar, a multivariate distribution can be represented in terms of its underlying margins by binding them together using a copula function. By exploiting this representation, the “copula approach” to statistical modelling proceeds by specifying distributions for each margin and a copula function. In this paper, a number of families of copula functions are given, with attentio...

This paper investigates the robustness of conventional mean-variance (MV) optimization model by making two adjustments within MV formulation. First, portfolio selection based on a behavioral decision-making theory that encapsulates statistics and investors psychology. The second aspect involves capturing asset dependence structure through copula. Using (BMV) copula (CBMV), results show stocks w...

this study presents a new method for interpolation by use of copula for groundwater quality zoning. in this regard, the data of the concentration of bicarbonate in 87 piezometric wells on the plains of kerman and ravar in september 2013 were examined. for this purpose, four archimedean copula including clayton, frank, gumbel and joe have been used. then, the obtained results were compared to th...

The univariate Piecing-Together approach (PT) fits a univariate generalized Pareto distribution (GPD) to the upper tail of a given distribution function (df) in a continuous manner. A multivariate extension was established by Aulbach et al. (2011a): The upper tail of a given copula C was cut off and substituted by the upper tail of a multivariate GPD-copula in a continuous manner. The result is...

This paper presents three tests of contagion of the US subprime crisis to the European markets of the NYSE-Euronext group. Copula models are used to analyse dependence structures between the US’s and the other markets in the sample, in the pre-crisis and in the subprime crisis periods. The first test assesses the existence of contagion on the relevant markets’ indices, the second checks the hom...

We propose a high dimensional classification method, named the Copula Discriminant Analysis (CODA). The CODA generalizes the normal-based linear discriminant analysis to the larger Gaussian Copula models (or the nonparanormal) as proposed by Liu et al. (2009). To simultaneously achieve estimation efficiency and robustness, the nonparametric rank-based methods including the Spearman’s rho and Ke...

Copula constructions are problematic in the syntax of most languages. The paper describes three different dependency syntactic methods for handling copula constructions: function head, content head and complex label analysis. Furthermore, we also propose a POS-based approach to copula detection. We evaluate the impact of these approaches in computational parsing, in two parsing experiments for ...

We study the possibility for international diversi cation of catastrophe risk by the insurance sector. Adopting the argument that large insurance losses may be a `globalizing factor' for the industry, we study the dependence of geographically distant insurance markets via equity returns. In particular, we employ conditional copula theory to model the bivariate dependence of the insurance indust...