This article presents a new approach for building robust portfolios based on stochastic efficiency analysis and periods … varying the level of probability in fulfilling the constraints (1-αi) of the CCDEA model. We show that the optimal portfolios …, allows us to build robust portfolios, with higher cumulative returns in the validation period, and portfolios with lower beta …

We develop the idea of using Monte Carlo sampling of random portfolios to solve portfolio investment problems. We … explore the need for more general optimization tools, and consider the means by which constrained random portfolios may be …

problems: the lack of robustness and diversification of portfolios obtained through these models. To solve these problems, I …

reformulation and algorithmic framework, and to evaluate the performance of theDRSTARR-constructed portfolios. The cross …-validation results obtained using a rolling-horizon procedure show the superior out-of-sample performance of the DRSTARR portfolios under …

Many investors use optimization to determine their optimal investment portfolio. Unfortunately, optimal portfolios are … near-optimal portfolios which, especially in light of the robustness problem, are all good allocation decisions. Then, as …-optimal portfolio. We will show that the region of near-optimal portfolios is significantly more robust than the optimal portfolio …

optimization. We identify the portfolios that cause problems in standard MVO and present a simple enhanced portfolio optimization …