Differential Evolution (DEoptim) for Non-Convex Portfolio Optimization
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.
|Date of creation:||15 Apr 2010|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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 "Marco Biagi".
- Thiemo Krink & Sandra Paterlini, 2008. "Differential Evolution for Multiobjective Portfolio Optimization," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 08012, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
- Mullen, Katharine M. & Ardia, David & Gil, David L. & Windover, Donald & Cline, James, 2009.
"DEoptim: An R Package for Global Optimization by Differential Evolution,"
21743, University Library of Munich, Germany, revised 26 Dec 2010.
- Mullen, Katharine M. & Ardia, David & Gil, David L. & Windover, Donald & Cline, James, 2011. "DEoptim: An R Package for Global Optimization by Differential Evolution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i06).
- Manfred Gilli & Enrico Schumann, 2009.
"Heuristic Optimisation in Financial Modelling,"
- O. Scaillet, 2004. "Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall," Mathematical Finance, Wiley Blackwell, vol. 14(1), pages 115-129.
- Manfred GILLI & Peter WINKER, "undated".
"A review of heuristic optimization methods in econometrics,"
Swiss Finance Institute Research Paper Series
08-12, Swiss Finance Institute.
- Manfred Gilli & Peter Winker, 2008. "Review of Heuristic Optimization Methods in Econometrics," Working Papers 001, COMISEF.
- 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.
- 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, Dipartimento di Economia "Marco Biagi".
- Thiemo Krink & Stefan Mittnik & Sandra Paterlini, 2009. "Differential evolution and combinatorial search for constrained index-tracking," Annals of Operations Research, Springer, vol. 172(1), pages 153-176, November.
- Jan Börner & Steven I. Higgins & Jochen Kantelhardt & Simon Scheiter, 2007. "Rainfall or price variability: what determines rangeland management decisions? A simulation-optimization approach to South African savannas," Agricultural Economics, International Association of Agricultural Economists, vol. 37(2-3), pages 189-200, 09.
- 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.
When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:22135. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter)
If references are entirely missing, you can add them using this form.