IDEAS home Printed from https://ideas.repec.org/a/cys/ecocyb/v50y2016i1p311-326.html
   My bibliography  Save this article

A Modified Harmony Search Algorithm For Portfolio Optimization Problems

Author

Listed:
  • ShouHeng Tuo

    (School of Mathematics and Computer Science Shaanxi University of Technology Hanzhong 723000, P.R.China)

Abstract

For a diversified portfolio problem, building an optimization model is very necessary to make investment return be as large as possible and to make the investment risk be as small as possible. In this work, firstly, the basic mathematic model of Portfolio Optimization (PO) and Cardinality Constrained Mean–Variance (CCMV) model are introduced. Then a modified Harmony search algorithm called HSDS based on Dimensional-Selection (DS) strategy and dynamic fret width (FW) strategy is proposed to solve PO problems, in which the DS strategy is for avoiding generating invalid solutions and the FW strategy is to balance global exploration and local exploitation. Finally, Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing and Tabu Search are compared with the HSDS algorithm employing five portfolio problems (HangSeng, DAX 100, FTSE 100, S&P 100 and Nikkei). Experimental results indicate that the proposed algorithm is very effective for solving large scale portfolio optimization problems.

Suggested Citation

  • ShouHeng Tuo, 2016. "A Modified Harmony Search Algorithm For Portfolio Optimization Problems," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 311-326.
    • Handle: RePEc:cys:ecocyb:v:50:y:2016:i:1:p:311-326
    as

    Download full text from publisher

    File URL: ftp://www.eadr.ro/RePEc/cys/ecocyb_pdf/ecocyb1_2016p311-326.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chamberlain, Gary, 1983. "A characterization of the distributions that imply mean--Variance utility functions," Journal of Economic Theory, Elsevier, vol. 29(1), pages 185-201, February.
    2. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    3. Merton, Robert C., 1972. "An Analytic Derivation of the Efficient Portfolio Frontier," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(4), pages 1851-1872, September.
    4. Owen, Joel & Rabinovitch, Ramon, 1983. "On the Class of Elliptical Distributions and Their Applications to the Theory of Portfolio Choice," Journal of Finance, American Finance Association, vol. 38(3), pages 745-752, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yindi Ma & Yanhai Li & Longquan Yong, 2024. "Teaching–Learning-Based Optimization Algorithm with Stochastic Crossover Self-Learning and Blended Learning Model and Its Application," Mathematics, MDPI, vol. 12(10), pages 1-19, May.
    2. Jin Hee Yoon & Zong Woo Geem, 2021. "Empirical Convergence Theory of Harmony Search Algorithm for Box-Constrained Discrete Optimization of Convex Function," Mathematics, MDPI, vol. 9(5), pages 1-13, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Taras Bodnar & Yarema Okhrin & Valdemar Vitlinskyy & Taras Zabolotskyy, 2018. "Determination and estimation of risk aversion coefficients," Computational Management Science, Springer, vol. 15(2), pages 297-317, June.
    2. Gaydon, D.S. & Meinke, H. & Rodriguez, D. & McGrath, D.J., 2012. "Comparing water options for irrigation farmers using Modern Portfolio Theory," Agricultural Water Management, Elsevier, vol. 115(C), pages 1-9.
    3. Zhang, Duo, 2008. "Non-convex optimal portfolio sets and constant relative risk aversion," Journal of Economics and Business, Elsevier, vol. 60(6), pages 551-555.
    4. Penaranda, Francisco, 2007. "Portfolio choice beyond the traditional approach," LSE Research Online Documents on Economics 24481, London School of Economics and Political Science, LSE Library.
    5. Schuhmacher, Frank & Auer, Benjamin R., 2014. "Sufficient conditions under which SSD- and MR-efficient sets are identical," European Journal of Operational Research, Elsevier, vol. 239(3), pages 756-763.
    6. Sergio Ortobelli Lozza, 2001. "The classification of parametric choices under uncertainty: analysis of the portfolio choice problem," Theory and Decision, Springer, vol. 51(2), pages 297-328, December.
    7. Taras Bodnar & Taras Zabolotskyy, 2017. "How risky is the optimal portfolio which maximizes the Sharpe ratio?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(1), pages 1-28, January.
    8. Thomas Eichner, 2010. "Slutzky equations and substitution effects of risks in terms of mean-variance preferences," Theory and Decision, Springer, vol. 69(1), pages 17-26, July.
    9. David A. Hennessy, 2004. "Orthogonal Subgroups for Portfolio Choice," Economics Bulletin, AccessEcon, vol. 7(1), pages 1-7.
    10. Ioannis D Vrontos & Loukia Meligkotsidou & Spyridon D Vrontos, 2011. "Performance evaluation of mutual fund investments: The impact of non-normality and time-varying volatility," Journal of Asset Management, Palgrave Macmillan, vol. 12(4), pages 292-307, September.
    11. Peñaranda, Francisco & Sentana, Enrique, 2012. "Spanning tests in return and stochastic discount factor mean–variance frontiers: A unifying approach," Journal of Econometrics, Elsevier, vol. 170(2), pages 303-324.
    12. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2002. "Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 617-639, December.
    13. Masayuki Hirukawa & Mari Sakudo, 2016. "Testing Symmetry of Unknown Densities via Smoothing with the Generalized Gamma Kernels," Econometrics, MDPI, vol. 4(2), pages 1-27, June.
    14. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2013. "Sequential estimation of shape parameters in multivariate dynamic models," Journal of Econometrics, Elsevier, vol. 177(2), pages 233-249.
    15. Amengual, Dante & Sentana, Enrique, 2010. "A comparison of mean-variance efficiency tests," Journal of Econometrics, Elsevier, vol. 154(1), pages 16-34, January.
    16. Fischer, Thomas & Lundtofte, Frederik, 2020. "Unequal returns: Using the Atkinson index to measure financial risk," Journal of Banking & Finance, Elsevier, vol. 116(C).
    17. Mencía, Javier & Sentana, Enrique, 2009. "Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation," Journal of Econometrics, Elsevier, vol. 153(2), pages 105-121, December.
    18. Francisco Peñaranda, 2009. "Understanding portfolio efficiency with conditioning information," Economics Working Papers 1146, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2011.
    19. Kais Dachraoui & Georges Dionne, 2007. "Conditions Ensuring the Decomposition of Asset Demand for All Risk-Averse Investors," The European Journal of Finance, Taylor & Francis Journals, vol. 13(5), pages 397-404.
    20. Istvan Varga-Haszonits & Fabio Caccioli & Imre Kondor, 2016. "Replica approach to mean-variance portfolio optimization," Papers 1606.08679, arXiv.org.

    More about this item

    Keywords

    Portfolio Optimization; Harmony search Algorithm; Dimensional-selection strategy; Cardinality Constrained Mean-Variance Model;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cys:ecocyb:v:50:y:2016:i:1:p:311-326. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Corina Saman (email available below). General contact details of provider: https://edirc.repec.org/data/feasero.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.