Mean–Absolute Deviation Portfolio Models with Discrete Choice Constraints

Authors

  • Roy H. Kwon University of Toronto
  • Stephen J. Stoyan University of Southern California

Keywords:

portfolio optimization, mixed-integer programming, heuristics

Abstract

In this paper, we consider the problem of incorporating a wide set of real-world trading constraints to the mean-variance portfolio framework. Instead of using the mean-variance model directly, we use the equivalent Mean-Absolute Deviation (MAD) linear programming formulation. The addition of the trading constraints transforms the MAD model to a mixed-integer linear programming problem. We solve both the mean-variance and MAD models with the various trading constraints using a commercial solver and find that MAD model is substantially more tractable. In addition, a heuristic is developed for the extended MAD model to provide solutions for larger problem instances.

Author Biographies

Roy H. Kwon, University of Toronto

Associate Professor Mechanical and Industrial Engineering

Stephen J. Stoyan, University of Southern California

Assistant Professor Department of Systems and Industrial Engineering

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Published

2012-01-03

How to Cite

Kwon, R. H., & Stoyan, S. J. (2012). Mean–Absolute Deviation Portfolio Models with Discrete Choice Constraints. Algorithmic Operations Research, 6(2), Pages 118 – 134. Retrieved from https://journals.lib.unb.ca/index.php/AOR/article/view/15997

Issue

Vol. 6 No. 2 (2011)

Section

Articles

License

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