Robust Portfolio Optimisation Under Sparse Contamination

Carlo E. Autiero () and Alessio Farcomeni ()
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Carlo E. Autiero: University of Rome “Tor Vergata”
Alessio Farcomeni: University of Rome “Tor Vergata”

Computational Economics, 2025, vol. 66, issue 2, No 6, 1137-1155

Abstract: Abstract We introduce novel methods for mean-variance portfolio optimisation in the presence of component-wise contamination. Methods are obtained by combining component-wise robust location-scatter estimation and optimisation based on genetic algorithms. The newly proposed approaches are compared with classical and row-wise robust methods in a simulation study and a real-data application on data from the Italian stock exchange. Results show a strong advantage of cell-wise resistant methodologies over competitors, both in terms of absolute risk and Sharpe ratio.

Keywords: Cell-wise contamination; Component-wise contamination; Portfolio allocation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10614-024-10733-y

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