609 research outputs found
Distorted Copulas: Constructions and Tail Dependence
Given a copula C, we examine under which conditions on an order isomorphism ψ of [0, 1] the distortion C ψ: [0, 1]2 → [0, 1], C ψ(x, y) = ψ{C[ψ−1(x), ψ−1(y)]} is again a copula. In particular, when the copula C is totally positive of order 2, we give a sufficient condition on ψ that ensures that any distortion of C by means of ψ is again a copula. The presented results allow us to introduce in a more flexible way families of copulas exhibiting different behavior in the tails
Biconic semi-copulas with a given section
Inspired by the notion of biconic semi-copulas, we introduce biconic semi-copulas with a given section. Such semi-copulas are constructed by linear interpolation on segments connecting the graph of a continuous and decreasing function to the points (0, 0) and (1, 1). Special classes of biconic semi-copulas with a given section such as biconic (quasi-)copulas with a given section are considered. Some examples are also provided
Baire category results for quasi–copulas
AbstractThe aim of this manuscript is to determine the relative size of several functions (copulas, quasi–
copulas) that are commonly used in stochastic modeling. It is shown that the class of all quasi–copulas that
are (locally) associated to a doubly stochastic signed measure is a set of first category in the class of all quasi–
copulas. Moreover, it is proved that copulas are nowhere dense in the class of quasi-copulas. The results are
obtained via a checkerboard approximation of quasi–copulas
Estimating Discrete Markov Models From Various Incomplete Data Schemes
The parameters of a discrete stationary Markov model are transition
probabilities between states. Traditionally, data consist in sequences of
observed states for a given number of individuals over the whole observation
period. In such a case, the estimation of transition probabilities is
straightforwardly made by counting one-step moves from a given state to
another. In many real-life problems, however, the inference is much more
difficult as state sequences are not fully observed, namely the state of each
individual is known only for some given values of the time variable. A review
of the problem is given, focusing on Monte Carlo Markov Chain (MCMC) algorithms
to perform Bayesian inference and evaluate posterior distributions of the
transition probabilities in this missing-data framework. Leaning on the
dependence between the rows of the transition matrix, an adaptive MCMC
mechanism accelerating the classical Metropolis-Hastings algorithm is then
proposed and empirically studied.Comment: 26 pages - preprint accepted in 20th February 2012 for publication in
Computational Statistics and Data Analysis (please cite the journal's paper
The joint distribution of stock returns is not elliptical
Using a large set of daily US and Japanese stock returns, we test in detail
the relevance of Student models, and of more general elliptical models, for
describing the joint distribution of returns. We find that while Student
copulas provide a good approximation for strongly correlated pairs of stocks,
systematic discrepancies appear as the linear correlation between stocks
decreases, that rule out all elliptical models. Intuitively, the failure of
elliptical models can be traced to the inadequacy of the assumption of a single
volatility mode for all stocks. We suggest several ideas of methodological
interest to efficiently visualise and compare different copulas. We identify
the rescaled difference with the Gaussian copula and the central value of the
copula as strongly discriminating observables. We insist on the need to shun
away from formal choices of copulas with no financial interpretation.Comment: 12 figure
Revisiting Relations between Stochastic Ageing and Dependence for Exchangeable Lifetimes with an Extension for the IFRA/DFRA Property
We first review an approach that had been developed in the past years to
introduce concepts of "bivariate ageing" for exchangeable lifetimes and to
analyze mutual relations among stochastic dependence, univariate ageing, and
bivariate ageing. A specific feature of such an approach dwells on the concept
of semi-copula and in the extension, from copulas to semi-copulas, of
properties of stochastic dependence. In this perspective, we aim to discuss
some intricate aspects of conceptual character and to provide the readers with
pertinent remarks from a Bayesian Statistics standpoint. In particular we will
discuss the role of extensions of dependence properties. "Archimedean" models
have an important role in the present framework. In the second part of the
paper, the definitions of Kendall distribution and of Kendall equivalence
classes will be extended to semi-copulas and related properties will be
analyzed. On such a basis, we will consider the notion of "Pseudo-Archimedean"
models and extend to them the analysis of the relations between the ageing
notions of IFRA/DFRA-type and the dependence concepts of PKD/NKD
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