Risk measures: a generalization from the univariate to the matrix-variate This paper proposes a method to calculate matrix-variate value-at-risk. This paper develops a method for estimating the value-at-risk and the conditional value-at-risk when the underlying risk factors follow a beta distribution in a univariate and matrix-variate setting. Analytical expressions of the risk measures are developed. A numerical solution for the risk measures for any parameterization of beta distributed loss variables is presented. Of fundamental importance is the application of computer-based algorithms for solving classically analytic problems in financial risk management. The data we acquired from Colombian financial institutions are considered using both algorithmic and analytic methods. Our results demonstrate a correspondence between the two. Although our results are motivated by problems in finance, we believe that our methods may well more general applications as well.