Time-stamped resampling for robust evolutionary portfolio optimization

Authors:
Sandra García;David Quintana;Inés M. Galván;Pedro Isasi
Affiliations:
Computer Science Department, Carlos III University of Madrid, Avda. Universidad 30, 28911 Leganes, Spain;Computer Science Department, Carlos III University of Madrid, Avda. Universidad 30, 28911 Leganes, Spain;Computer Science Department, Carlos III University of Madrid, Avda. Universidad 30, 28911 Leganes, Spain;Computer Science Department, Carlos III University of Madrid, Avda. Universidad 30, 28911 Leganes, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

Traditional mean-variance financial portfolio optimization is based on two sets of parameters, estimates for the asset returns and the variance-covariance matrix. The allocations resulting from both traditional methods and heuristics are very dependent on these values. Given the unreliability of these forecasts, the expected risk and return for the portfolios in the efficient frontier often differ from the expected ones. In this work we present a resampling method based on time-stamping to control the problem. The approach, which is compatible with different evolutionary multiobjective algorithms, is tested with four different alternatives. We also introduce new metrics to assess the reliability of forecast efficient frontiers.