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Differential Evolution (DEoptim) for Non-Convex Portfolio Optimization

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  • Ardia, David
  • Boudt, Kris
  • Carl, Peter
  • Mullen, Katharine M.
  • Peterson, Brian

Abstract

The R package DEoptim implements the differential evolution algorithm. This algorithm is an evolutionary technique similar to genetic algorithms that is useful for the solution of global optimization problems. In this note we provide an introduction to the package and demonstrate its utility for financial applications by solving a non-convex portfolio optimization problem.

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File URL: http://mpra.ub.uni-muenchen.de/22135/
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File URL: http://mpra.ub.uni-muenchen.de/28187/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 22135.

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Date of creation: 15 Apr 2010
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Handle: RePEc:pra:mprapa:22135

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Keywords: Differential optimization; non-convex portfolio optimization; DEoptim; R software;

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References

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  1. O. Scaillet, 2004. "Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall," Mathematical Finance, Wiley Blackwell, vol. 14(1), pages 115-129.
  2. Thiemo Krink & Stefan Mittnik & Sandra Paterlini, 2009. "Differential Evolution and Combinatorial Search for Constrained Index Tracking," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 09032, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".
  3. Mullen, Katharine M. & Ardia, David & Gil, David L. & Windover, Donald & Cline, James, 2009. "DEoptim: An R Package for Global Optimization by Differential Evolution," MPRA Paper 21743, University Library of Munich, Germany, revised 26 Dec 2010.
  4. Maringer Dietmar G. & Meyer Mark, 2008. "Smooth Transition Autoregressive Models -- New Approaches to the Model Selection Problem," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-21, March.
  5. Manfred GILLI & Peter WINKER, . "A review of heuristic optimization methods in econometrics," Swiss Finance Institute Research Paper Series 08-12, Swiss Finance Institute.
  6. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
  7. Thiemo Krink & Sandra Paterlini, 2008. "Differential Evolution for Multiobjective Portfolio Optimization," Center for Economic Research (RECent) 021, University of Modena and Reggio E., Dept. of Economics.
  8. Higgins, Steven I. & Kantelhardt, Jochen & Scheiter, Simon & Boerner, Jan, 2007. "Sustainable management of extensively managed savanna rangelands," Ecological Economics, Elsevier, vol. 62(1), pages 102-114, April.
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Citations

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Cited by:
  1. Ankit Dangi, 2013. "Financial Portfolio Optimization: Computationally guided agents to investigate, analyse and invest!?," Papers 1301.4194, arXiv.org.
  2. Katharine M. Mullen & David Ardia & David L. Gil & Donald Windover & James Cline, . "DEoptim: An R Package for Global Optimization by Differential Evolution," Journal of Statistical Software, American Statistical Association, vol. 40(i06).
  3. Ardia, David & Ospina, Juan & Giraldo, Giraldo, 2010. "Jump-Diffusion Calibration using Differential Evolution," MPRA Paper 26184, University Library of Munich, Germany, revised 25 Oct 2010.
  4. Jarraya, Bilel, 2013. "Asset allocation and portfolio optimization problems with metaheuristics: a literature survey," MPRA Paper 53698, University Library of Munich, Germany, revised 2013.

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