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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.

Related Keywords

,Beta ,Frisk Measures ,Gaussian Model ,Risk ,Value At Risk Var ,Conditional Value At Risk Cvar ,Original Research ,பீட்டா ,இஸ்க் ,

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