We propose a method for optimal portfolio selection using a Bayesian decision theoretic framework that addresses two major shortcomings of the Markowitz approach: the ability to handle higher moments and estimation error. We employ the skew normal distribution which has many attractive features for modeling multivariate returns. Our results suggest that it is important to incorporate higher ord...

Higher central moments are very useful in statistical analysis: the third moment M3 characterizes asymmetry of the corresponding probability distribution, the fourth moment M4 describes the size of the distribution’s tails, etc. When we know the exact values x1, . . . , xn, we can use the known formulas for computing the corresponding sample central moments. In many practical situations, howeve...

We present analytical calculation of the rst seven moments of the heavy quark vacuum polarization function in the three-loop order. The obtained results are compared against the asymptotic formulas following from the threshold singulari-ties. We also discuss the dependence of the moments within the BLM procedure.

This communication presents a simple algebraic method for the extraction of independent components in multidimensional data. Since statistical independence is a much stronger property than uncorrelation, it is possible, using higher-order moments, to identify source signatures in array data without any a-priori model for propagation or reception, that is, without directional vector parametrizat...