The effect of local search on the constrained portfolio selection problem

2006 IEEE Congress on Evolutionary Computation, CEC 2006

Volumn , Issue , 2006, Pages 2368-2374

  Streichen, Felix ^a   Tanaka Yamawaki, Mieko ^a  

^a TOTTORI UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; EVOLUTIONARY ALGORITHMS; GLOBAL OPTIMIZATION; HEURISTIC METHODS; PROBLEM SOLVING;

FINANCIAL ENGINEERING; MULTI OBJECTIVE OPTIMIZATION; PORTFOLIO SELECTION PROBLEMS; PREMATURE CONVERGENCE;

CONSTRAINT THEORY;

EID: 34547312873     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (34)

1. R. Armañanzas and J. A. Lozano. A multiobjective approach to the portfolio optimization problem. In Congress on Evolutionary Computation (CEC 2005). IEEE Press, 2005.
2. S. Arnone, A. Loraschi, and A. Tettamanzi. A genetic approach to portfolio selection. Neural Network World, International Journal on Neural and Mass-Parallel Computing and Information Systems, 3:597-604, 1993.
3. J. E. Beasley. OR-Library: distributing test problems by electronic mail. Journal of the Operational Research, 8:429-433, 1996.
4. T.-J. Chang, N. Meade, J. E. Beasley, and Y. M. Sharaiha. Heuristics for cardinality constrained portfolio optimization. Computers and Operations Research, 27(13): 1271-1302, 2000.
5. Y. Crama and M. Schyns. Simulated annealing for complex portfolio selection problems. Working paper GEMME 9911, Universit de Lige, 1999.
6. K. Deb. Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons, LTD, 200.1.
7. K. Deb, S. Agrawal, A. Pratab, and T. Meyarivan. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. In M. Schoenauer, K. Deb, and G. Rudolph et al., editors, 6th International Conference on Parallel Problem Solvingfrom Nature (PPSN VI), volume 1917 of LNCS, pages 849-858. SpringerVerlag, 2000.
8. D. Eddelbüttel. A hybrid genetic algorithm for passive management, presented at the Second Conference 'Computing in Economics and Finance' organised by the Society for Computational Economics and hosted by the Department of Econometrics at the University of Geneva, Switzerland, June 1996.
9. J. Fieldsend, J. Matatko, and M. Peng. Cardinality constrained portfolio optimisation. In Z. Yang, R. Everson, and H. Yin, editors, 5th International Conference on Intelligent Data Engineering and Automated Learning, number 3177 in LNCS, pages 788-793. SpringerVerlag, 2004.
10. W. E. Hart, N. Krasnogor, and J. E. Smith, editors. Recent Advances in Memetic Algorithms, volume 166 of Studies in. Fuzziness and Soft Computing. Springer-Verlag, 2005.
11. J. Holland. Adaption in. Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Systems. The University Press of Michigan, Ann Arbor, 1975.
12. N. J. Jobst, M. H. Horniman, C. Lucas, and G. Mitra. Computational aspects of alternative portfolio selection models in the presence of discrete asset choice constraints. Quantitative Finance, 1:1-13, 2001.
13. H. Kellerer and D. Maringer. Optimization of cardinality constrained portfolios with a hybrid local search algorithm.. OR Spectrum, 25(4):481- 495, 2003.
14. A. Loraschi and A. Tettamanzi. An evolutionary algorithm for portfolio selection in a downside risk framework. Working Papers in Financial. Economics, 6:8-12, 1995.
15. A. Loraschi, A. Tettamanzi, M. Tomassini, and P. Verda. Distributed genetic algorithms with an application to portfolio selection problems. In D. W. Pearson, N. C. Steele, and R. F. Albrecht, editors, Artificial Neural Networks and Genetic Algorithms, pages 384-387. Sringer, 1995.
16. H. M. Markowitz. Portfolio selection. Journal of Finance, 1(7):77-91, 1952.
17. H. M. Markowitz. Portfolio Selection: efficient diversification, of investments. John Wiley & Sons, LTD, 1959.
18. Mathworks. Matlab. Mathworks, Inc., Natick, MA, 1999.
19. K. M. Miettinen. Nonlinear Multiobjective Optimization. Kluwer Academic Publishers, 1998.
20. J. Nocedal and S. Wright. Numerical Optimization. Springer-Verlag, 1999.
21. F. Schlottmann, A. Mitschele, and D. Seese. A multi-objetive approach to integrated risk management. In C. A. Coello Coello, A. H. Aguirre, and E. Ziztler, editors, Conference on Evolutionary Multi-Criterion Optimization (EMO 2005), volume 3410 of LNCS, pages 692-706. Springer-Verlag, 2005.
22. F. Schlottmann and D. Seese. A hybrid genetic-quantitative method for risk-return-optimization of credit portfolios. In Quantitative Methods in Finance, page 55, 2001.
23. F. Schlottmann and D. Seese. Hybrid multi-objective evolutionary computation of constrained downside risk-return efficient sets for credit portfolios. In 8th International Conference of the Society for Computational Economics: Computing in Economics and Finance, 2002.
24. H.-P. Schwefel. Evolution and Optimum. Seeking. John Wiley & Sons, LTD, 1995.
25. J. Shapcott. Index tracking: Genetic algorithms for investment portfolio selection. Technical Report EPCC-SS92-24, Edinburgh Parallel Computing Centre, University of Edinburgh, 1992.
26. J. Shoaf and J. A. Foster. The efficient set ga for stock portfolios. In Congress on Evolutionary Computation (CEC 1998), pages 354-359. IEEE Press, 1998.
27. R. E. Steuer, Y. Qi, and M. Hirschberger. Multiple objectives in portfolio selection. Journal of Financial Decision Making, l (l): l 1-26, 2005.
28. F. Streichert and H. Ulmer. JavaEvA - a java framework for evolutionary algorithms. Technical Report WSI-2005-06, Centre for Bioinformatics Tübingen, University of Tübingen, 2005.
29. F. Streichert, H. Ulmer, and A. Zell. Evolutionary algorithms and the cardinality constrained portfolio selection problem. In D. Ahr, R. Fahrion, M. Oswald, and G. Reinelt, editors, Operations Research Proceedings 2003, Selected Papers, pages 253 - 260. Springer-Verlag, 2003.
30. F. Streichert, H. Ulmer, and A. Zell. Evaluating a hybrid encoding and three crossover operators on the constrained portfolio selection problem. In Congress on Evolutionary Computation (CEC 2004), pages 932-939. IEEE Press, 2004.
31. J. Tang, M. H. Lim, and Y. S. Ong. Grid technology in financial planning - a methodology for portfolio structuring. Technical report, Nanyang Technology University, 2003.
32. P. Turney. Myths and legends of the Baldwin effect. In T. Fogarty and G. Venturini, editors, 13th International Conference on Machine Learning, pages 135-142, 1996.
33. G. Vedarajan, L. Chan, and D. Goldberg. Investment portfolio optimization using genetic algorithms. In J. Koza, editor, Genetic Programming, pages 255-263, 1997.
34. T. Yu and P. Bentley. Methods to evolve legal phenotypes. In A. E. Eiben, T. Back, and M. Schoenauer et al., editors, 5th International Conference on Parallel Problem Solving from Nature (PPSN V), pages 280-291. Springer-Verlag, 1998.