Title: Multi-intervals robust mean-conditional value-at-risk portfolio optimisation with conditional scenario reduction technique

Authors: Tahereh Khodamoradi; Maziar Salahi; Ali Reza Najafi

Addresses: Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran ' Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran; Center of Excellence for Mathematical Modeling, Optimization and Combinatorial Computing (MMOCC), University of Guilan, Rasht, Iran ' Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran

Abstract: In this paper, we study mean-conditional value at risk (mean-CVaR) portfolio optimisation with cardinality constraints and short selling under uncertainty. To reduce the level of conservatism, instead of single uncertainty interval, multi-intervals uncertainty sets are considered that are obtained by an efficient scenario reduction technique. It is proven that the proposed robust mean-CVaR model with cardinality constraints and short selling is equivalent to a mixed integer linear programming problem. Finally, using historical data on the S&P index for 2018, we evaluate the efficiency of the proposed models using CVX software in MATLAB. The results show that robust model has relatively low conservatism under multi-intervals uncertainties.

Keywords: conditional value-at-risk; scenario reduction; robust optimisation.

DOI: 10.1504/IJADS.2023.129475

International Journal of Applied Decision Sciences, 2023 Vol.16 No.2, pp.237 - 254

Received: 15 Aug 2021
Accepted: 02 Dec 2021
Published online: 10 Mar 2023 *

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