Robust Optimisation and Portfolio Selection: The Cost of Robustness

32 Pages Posted: 16 Aug 2008

See all articles by Christine Gregory

Christine Gregory

CARISMA, Brunel University

Kenneth Darby-Dowman

Brunel University

Gautam Mitra

Brunel University London - CARISMA: The Centre for the Analysis of Risk and Optimisation Modelling Applications

Date Written: July 17, 2008

Abstract

Robust optimization is a tractable alternative to stochastic programming particularly suited for problems in which parameter values are unknown, variable, and their distributions are uncertain. We evaluate the cost of robustness of the robust counterpart to the maximum return portfolio optimization problem. The uncertainty of asset returns is modelled by polyhedral uncertainty sets as opposed to the earlier proposed ellipsoidal sets. We derive the robust model from a min-regret perspective and examine the properties of robust models with respect to portfolio composition. We investigate the effect of different definitions of the bounds on the uncertainty sets and show that robust models yield well diversified portfolios, in terms of the number of assets and asset weights.

Keywords: robust optimization, portfolio selection

Suggested Citation

Gregory, Christine and Darby-Dowman, Kenneth and Mitra, Gautam, Robust Optimisation and Portfolio Selection: The Cost of Robustness (July 17, 2008). Available at SSRN: https://ssrn.com/abstract=1225678 or http://dx.doi.org/10.2139/ssrn.1225678

Christine Gregory (Contact Author)

CARISMA, Brunel University ( email )

John Crank Building
Brunel University
Uxbridge, UB8 3PH
United Kingdom

Kenneth Darby-Dowman

Brunel University ( email )

Kingston Lane
Uxbridge, Middlesex UB8 3PH
United Kingdom

Gautam Mitra

Brunel University London - CARISMA: The Centre for the Analysis of Risk and Optimisation Modelling Applications ( email )

John Crank Building
Brunel University
Uxbridge, UB8 3PH
United Kingdom

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