In this paper, we derive upper and lower bounds on the Range Value-at-Risk of the portfolio loss when we only know its mean and variance, and its feature of unimodality. In a first step, we use some classic results on stochastic ordering to reduce this optimization problem to a parametric one,...

We derive upper and lower bounds for the Range Value-at-Risk of a unimodal random variable under knowledge of the mean, variance, symmetry, and a possibly bounded support. Moreover, we provide a generalization of the Gauss inequality for symmetric distributions with known support

Brown et al. (2006) derive a Stein-type inequality for the multivariate Student-t distribution. We generalize their result to the family of (multivariate) generalized hyperbolic distributions and derive a lower bound for the variance of a function of a random variable

When two variables are bivariate normally distributed, Stein's (1973, 1981) seminal lemma provides a convenient expression for the covariance of the first variable with a function of the second. The lemma has proven to be useful in various disciplines, including statistics, probability, decision...

When two random variables are bivariate normally distributed Stein's original lemma allows to conveniently express the covariance of the first variable with a function of the second. Landsman & Neslehova (2007) extend this seminal result to the family of multivariate elliptical distributions. In...