Add to ORKGAbstract: This paper introduces two techniques for computing bounds for several quantile-based risk measures based on distortion functions. Knowledge about the marginal distribution of the involved random variables is assumed with the optional assumption of some partial information about the structure of dependence. The aim is to derive bounds for risk measures of functions of dependent random variables. Several examples taken from an insurance context are given. We use Embrechts et al. (2003) methodology and the stochastic ordering approach to derive bounds for various risk measures in the bi-dimensional and the multidimensional cases
We consider the computation of quantiles and spectral risk measures for discrete distributions. This...
The theory of copulae is known to provide a useful tool for modelling dependence in integrated risk ...
In this paper we consider the problem of determining approximations for distortion risk measures of ...
We describe several analytical and numerical procedures to obtain bounds on the distribution functio...
In the present paper, we study quantile risk measures and their domain. Our starting point is that, ...
Li et al. [Distributions with Fixed Marginals and Related Topics, vol. 28, Institute of Mathematics ...
We propose a new algorithm to compute numerically sharp lower and upper bounds on the distribution o...
The problem of finding the best-possible lower bound on the distribution of a non-decreasing functio...
AbstractWe propose a new algorithm to compute numerically sharp lower and upper bounds on the distri...
In this paper we consider the problem of studying the gap between bounds of risk measures of sums of...
In this paper we consider the problem of studying the gap between bounds of risk measures for sums o...
In this paper we consider the problem of determining approximations for distortion risk measures of ...
There is a recent interest in finding bounds for risk measures of portfolios when the marginal distri...
In this paper, explicit lower and upper bounds on the value-at-risk (VaR) for the sum of possibly de...
A new family of distortion risk measures GlueVaR is proposed in Belles-Sampera et al. (2014) to proc...
We consider the computation of quantiles and spectral risk measures for discrete distributions. This...
The theory of copulae is known to provide a useful tool for modelling dependence in integrated risk ...
In this paper we consider the problem of determining approximations for distortion risk measures of ...
We describe several analytical and numerical procedures to obtain bounds on the distribution functio...
In the present paper, we study quantile risk measures and their domain. Our starting point is that, ...
Li et al. [Distributions with Fixed Marginals and Related Topics, vol. 28, Institute of Mathematics ...
We propose a new algorithm to compute numerically sharp lower and upper bounds on the distribution o...
The problem of finding the best-possible lower bound on the distribution of a non-decreasing functio...
AbstractWe propose a new algorithm to compute numerically sharp lower and upper bounds on the distri...
In this paper we consider the problem of studying the gap between bounds of risk measures of sums of...
In this paper we consider the problem of studying the gap between bounds of risk measures for sums o...
In this paper we consider the problem of determining approximations for distortion risk measures of ...
There is a recent interest in finding bounds for risk measures of portfolios when the marginal distri...
In this paper, explicit lower and upper bounds on the value-at-risk (VaR) for the sum of possibly de...
A new family of distortion risk measures GlueVaR is proposed in Belles-Sampera et al. (2014) to proc...
We consider the computation of quantiles and spectral risk measures for discrete distributions. This...
The theory of copulae is known to provide a useful tool for modelling dependence in integrated risk ...
In this paper we consider the problem of determining approximations for distortion risk measures of ...