Mean-Variance Programming Framework in Markowitz Modeling

Abstract

For mathematical frameworks in place, which are applied to portfolio optimization problems, the majority come in the form of risk minimization – relative to the return parameter. When it comes to the quadratic programming framework, in relation to Markowitz, its associated challenges have been countered when considerations are made to recent trends in algorithmic scholarly investigations. In particular, a linear risk function has been introduced, especially in response to the need to address problems of portfolio selection, given real constraints. In this study, the main aim is to address the problem of portfolio selection in relation to minimum transaction lots. Also, the paper focuses on an improved search model that is applied to active constrained, whereby solutions are developed for the integer programming algorithm. The proposed model is that which focuses on the relaxed problem’s solution initially, before establishing solutions that are deemed closer to the continuous solutions..