Reliability in Portfolio Optimization using Uncertain Estimates

Portfolio optimization problems are rather easy to solve if one assumes normality of the (joint) distribution returns with given parameters and a linear objective function, subject some risk constraints. Higher degrees complexities arise when taking into account (i) non- asset classes, (ii) non-normal distributions, (iii) constraints on lot size, portfolio shares etc., (iv) uncertainty parameter estimates. In this paper Reliability-Based Design Optimization (RBDO) framework is developed tackle last two issues, namely, problems, sizes, shares, estimates (i.e., return risk). Thereby, standard methods heuristics, available in literature for handling reliability-based constraints, adopted. The Block-Bootstrap method used obtain For an application stocks which components DAX, efficient portfolios obtained trade-off between optimal values function reliability results.