The allocation of resources to alternative investment opportunities is one of the most
important decisions organizations and individuals face. These decisions can be guided by …

Portfolio optimization can lead to misspecified stock returns that follow a known distribution.
To investigate tractable formulations of the portfolio selection problem, we study these …

The portfolio optimization (PO) model with semi-mean absolute deviation (SMAD) risk
measure has been commonly applied to construct optimal portfolios due to the ease of …

The mean-variance model formulated by Markowitz for a single period serves as a
fundamental method of modern portfolio selection. In this study, we consider a multi-period …

Sparse portfolio optimization, which significantly boosts the out-of-sample performance of
traditional mean–variance methods, is widely studied in the fields of optimization and …

We use a numerical methods algorithm based on gradient descent to optimise investment
portfolios of global indices using raw and forecasted risk measures at differing frequencies …

Solving the distributional worst-case in the distributionally robust optimization problem is
equivalent to finding the projection onto the intersection of simplex and singly linear …

This paper focuses on the Wasserstein distributionally robust mean-lower semi-absolute
deviation (DR-MLSAD) model, where the ambiguity set is a Wasserstein ball centered on the …

Addressing the uncertainties of renewable energy and load within isolated microgrids, a
robust economic optimization approach for microgrids is proposed based on scenario …

In this paper, we construct a distributionally robust sparse portfolio selection model by
combining semi-absolute deviation (SAD) risk function with Wasserstein distance. First, we …