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Warm-Start Heuristic for Stochastic Portfolio Optimization with Fixed and Proportional Transaction Costs

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Abstract

We consider a probabilistic portfolio optimization model including fixed and proportional transaction costs. We derive a deterministic equivalent of the probabilistic model for fat-tailed portfolio returns. We develop a method which finds provably near-optimal solutions in minimal amount of time for industry-sized (up to 2000 assets) problems. To solve the mixed-integer nonlinear programming (MINLP) deterministic formulation equivalent to the stochastic problem, we design a mathematical programming-based warm-start heuristic. The tests show the computational efficiency of the heuristic which is more than an order of magnitude faster than Cplex in finding high-quality solutions.

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Acknowledgements

The authors are grateful to the valuable comments and suggestions from two anonymous reviewers and the editor who helped improve the paper significantly.

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Authors and Affiliations

  1. Management School, Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Tiago P. Filomena

  2. Department of Decision Sciences, The George Washington University, Washington, DC, USA

    Miguel A. Lejeune

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  1. Tiago P. Filomena
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  2. Miguel A. Lejeune
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Correspondence to Miguel A. Lejeune.

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Filomena, T.P., Lejeune, M.A. Warm-Start Heuristic for Stochastic Portfolio Optimization with Fixed and Proportional Transaction Costs. J Optim Theory Appl 161, 308–329 (2014). https://doi.org/10.1007/s10957-013-0348-y

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