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Multiobjective robustness for portfolio optimization in volatile environments

Hassan, G; Clack, C; (2008) Multiobjective robustness for portfolio optimization in volatile environments. In: Proceedings of the 10th annual conference on Genetic and evolutionary computation. (pp. pp. 1507-1514). ACM: Association for Computing Machinery: Atlanta, GA, USA. Green open access

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Abstract

Multiobjective methods are ideal for evolving a set of portfolio optimisation solutions that span a range from high-return/high-risk to low-return/low-risk, and an investor can choose her preferred point on the risk-return frontier. However, there are no guarantees that a low-risk solution will remain low-risk . if the environment changes, the relative positions of previously identified solutions may alter. A low-risk solution may become high-risk and vice versa. The robustness of a Multiobjective Genetic Programming (MOGP) algorithm such as SPEA2 is vitally important in the context of the real-world problem of portfolio optimisation. We explore robustness in this context, providing new definitions and a statistical measure to quantify the robustness of solutions. A new robustness measure is incorporated into a MOGP fitness function to bias evolution towards more robust solutions. This new system ("R-SPEA2") is compared against the original SPEA2 and we present our results.

Type: Proceedings paper
Title: Multiobjective robustness for portfolio optimization in volatile environments
Event: GECCO08: Genetic and Evolutionary Computation Conference
ISBN-13: 9781605581309
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/1389095
Publisher version: https://doi.org/10.1145/1389095.1389387
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: GP, Multiobjective Optimization, Robustness, Portfolio Optimization, Finance, Dynamic Environment
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10087095
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