Robust multi-period and multi-objective portfolio selection

Abstract

In this paper, a multi-period multi-objective portfolio selection problem with uncertainty is studied. Under the assumption that the uncertainty set is ellipsoidal, the robust counterpart of the proposed problem can be transformed into a standard multi-objective optimization problem. A weighted-sum approach is then introduced to obtain Pareto front of the problem. Numerical examples will be presented to illustrate the proposed method and validate the effectiveness and efficiency of the model developed.

An Approach for a Multi-Period Portfolio Selection Problem by considering Transaction Costs and Prediction on the Stock Market

“…Additional to the mean-variance objective, the authors constructed a portfolio whose allocation is given by model predictive control with a risk-parity objective. Finally, Jiang and Wang [27] considered a multi-period multiobjective portfolio selection problem with uncertainty. A weightedsum approach was introduced to obtain the Pareto front of the problem.…”

Mean-variance portfolio selection with random investment horizon

“…A prominent approach for quantitative asset allocation is the mean-variance portfolio optimization which was pioneered by the seminal work of the Nobel Laureate in Economics, Harry Markowitz, (see [13]). The Markowitz mean-variance portfolio selection model is a static single-period model, where an economic agent seeks to minimize the risk of his investment, measured by the variance of a portfolio's return, subject to a given level of the mean return 1 Extension to multi-period for different applications are still actively developed [10,5]. A dynamic extension of the Markowitz model, especially in continuous time, has been widely studied in the literature (see, for example, [6,8,9,16,18]).…”