Robust Portfolio Selection with Near Optimal Centering

43 Pages Posted: 5 May 2020 Last revised: 28 Mar 2021

See all articles by Dany Cajas

Dany Cajas

Universidad Nacional de Ingeniería

Date Written: December 30, 2019

Abstract

Quantitative asset allocation models have not been widely adopted by practitioners because they suffer from two problems: the lack of robustness and diversification of portfolios obtained through these models. To solve these problems, We developed a new portfolio selection method that can be applied to any convex risk measure. The procedure begins selecting an optimal portfolio in the efficient frontier, then we define a near optimal region and finally we define the analytic center as the new optimal portfolio. We compare 30 portfolio optimization models for 4 asset samples, and the results suggest that the new method overcomes traditional methods in robustness and diversification.

Keywords: Mean Variance Portfolio, MAD Portfolio, CVaR Portfolio, Robust Optimization, Portfolio Selection, Near Optimal Portfolios

JEL Classification: C61, G11

Suggested Citation

Cajas, Dany, Robust Portfolio Selection with Near Optimal Centering (December 30, 2019). Available at SSRN: https://ssrn.com/abstract=3572435 or http://dx.doi.org/10.2139/ssrn.3572435

Dany Cajas (Contact Author)

Universidad Nacional de Ingeniería ( email )

Avenida Túpac Amaru 210
Lima, Lima 15081
Peru

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