IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v267y2018i1d10.1007_s10479-016-2377-z.html
   My bibliography  Save this article

A new efficiently encoded multiobjective algorithm for the solution of the cardinality constrained portfolio optimization problem

Author

Listed:
  • K. Liagkouras

    (University of Piraeus)

  • K. Metaxiotis

    (University of Piraeus)

Abstract

This paper proposes a novel multiobjective evolutionary Algorithm (MOEA) for the solution of the cardinality constrained portfolio optimization problem (CCPOP). The proposed algorithm introduces an efficient encoding scheme specially designed for dealing with the difficulties of the CCPOP. Also, the proposed algorithm incorporates a new mutation and recombination operator tailor-made to work well with the new encoding scheme. Datasets from seven different stock markets are utilized for testing the efficiency of the proposed approach. In particular, the performance of the proposed efficiently encoded multiobjective portfolio optimization solver (EEMPOS) is assessed in comparison with two well-known MOEAs, namely NSGAII and MOEA/D. The experimental results indicate that the proposed EEMPOS outperforms the two other MOEAs for all examined performance metrics when is applied to the solution of the CCPOP for a fraction of time required by the other techniques.

Suggested Citation

  • K. Liagkouras & K. Metaxiotis, 2018. "A new efficiently encoded multiobjective algorithm for the solution of the cardinality constrained portfolio optimization problem," Annals of Operations Research, Springer, vol. 267(1), pages 281-319, August.
    • Handle: RePEc:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-016-2377-z
    DOI: 10.1007/s10479-016-2377-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-016-2377-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-016-2377-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ron Bird & Mark Tippett, 1986. "Note---Naive Diversification and Portfolio Risk---A Note," Management Science, INFORMS, vol. 32(2), pages 244-251, February.
    2. Andriosopoulos, Kostas & Doumpos, Michael & Papapostolou, Nikos C. & Pouliasis, Panos K., 2013. "Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 16-34.
    3. K. Liagkouras & K. Metaxiotis, 2015. "Efficient Portfolio Construction with the Use of Multiobjective Evolutionary Algorithms: Best Practices and Performance Metrics," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 535-564.
    4. John L. Evans & Stephen H. Archer, 1968. "Diversification And The Reduction Of Dispersion: An Empirical Analysis," Journal of Finance, American Finance Association, vol. 23(5), pages 761-767, December.
    5. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2013. "Portfolio rebalancing with an investment horizon and transaction costs," Omega, Elsevier, vol. 41(2), pages 406-420.
    6. Johnson, K. H. & Shannon, D. S., 1974. "A note on diversification and the reduction of dispersion," Journal of Financial Economics, Elsevier, vol. 1(4), pages 365-372, December.
    7. Simone Brands & David R. Gallagher, 2005. "Portfolio selection, diversification and fund‐of‐funds: a note," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 45(2), pages 185-197, July.
    8. Frank Fabozzi & Dashan Huang & Guofu Zhou, 2010. "Robust portfolios: contributions from operations research and finance," Annals of Operations Research, Springer, vol. 176(1), pages 191-220, April.
    9. Smimou, K., 2014. "International portfolio choice and political instability risk: A multi-objective approach," European Journal of Operational Research, Elsevier, vol. 234(2), pages 546-560.
    10. Tang, Gordon Y. N., 2004. "How efficient is naive portfolio diversification? an educational note," Omega, Elsevier, vol. 32(2), pages 155-160, April.
    11. Duan Li & Xiaoling Sun & Jun Wang, 2006. "Optimal Lot Solution To Cardinality Constrained Mean–Variance Formulation For Portfolio Selection," Mathematical Finance, Wiley Blackwell, vol. 16(1), pages 83-101, January.
    12. Bloomfield, Ted & Leftwich, Richard & Long, John Jr., 1977. "Portfolio strategies and performance," Journal of Financial Economics, Elsevier, vol. 5(2), pages 201-218, November.
    13. Adam Krzemienowski & Sylwia Szymczyk, 2016. "Portfolio optimization with a copula-based extension of conditional value-at-risk," Annals of Operations Research, Springer, vol. 237(1), pages 219-236, February.
    14. Adam Krzemienowski & Sylwia Szymczyk, 2016. "Portfolio optimization with a copula-based extension of conditional value-at-risk," Annals of Operations Research, Springer, vol. 237(1), pages 219-236, February.
    15. Konstantinos Anagnostopoulos & Georgios Mamanis, 2011. "Multiobjective evolutionary algorithms for complex portfolio optimization problems," Computational Management Science, Springer, vol. 8(3), pages 259-279, August.
    16. Deb, Kalyanmoy & Tiwari, Santosh, 2008. "Omni-optimizer: A generic evolutionary algorithm for single and multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1062-1087, March.
    17. Dimitris Bertsimas & Romy Shioda, 2009. "Algorithm for cardinality-constrained quadratic optimization," Computational Optimization and Applications, Springer, vol. 43(1), pages 1-22, May.
    18. Beasley, J. E. & Meade, N. & Chang, T. -J., 2003. "An evolutionary heuristic for the index tracking problem," European Journal of Operational Research, Elsevier, vol. 148(3), pages 621-643, August.
    19. Marco Corazza & Giovanni Fasano & Riccardo Gusso, 2011. "Particle Swarm Optimization with non-smooth penalty reformulation for a complex portfolio selection problem," Working Papers 2011_10, Department of Economics, University of Venice "Ca' Foscari".
    20. Markus Hirschberger & Ralph E. Steuer & Sebastian Utz & Maximilian Wimmer & Yue Qi, 2013. "Computing the Nondominated Surface in Tri-Criterion Portfolio Selection," Operations Research, INFORMS, vol. 61(1), pages 169-183, February.
    21. Crama, Y. & Schyns, M., 2003. "Simulated annealing for complex portfolio selection problems," European Journal of Operational Research, Elsevier, vol. 150(3), pages 546-571, November.
    22. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2011. "Heuristic algorithms for the cardinality constrained efficient frontier," European Journal of Operational Research, Elsevier, vol. 213(3), pages 538-550, September.
    23. Jennings, Edward H., 1971. "An Empirical Analysis of Some Aspects of Common Stock Diversification," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 6(2), pages 797-813, March.
    24. N. J. Jobst & M. D. Horniman & C. A. Lucas & G. Mitra, 2001. "Computational aspects of alternative portfolio selection models in the presence of discrete asset choice constraints," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 489-501.
    25. Fisher, Lawrence & Lorie, James H, 1970. "Some Studies of Variability of Returns on Investments in Common Stocks," The Journal of Business, University of Chicago Press, vol. 43(2), pages 99-134, April.
    26. Clara Calvo & Carlos Ivorra & Vicente Liern, 2016. "Fuzzy portfolio selection with non-financial goals: exploring the efficient frontier," Annals of Operations Research, Springer, vol. 245(1), pages 31-46, October.
    27. Ralph Steuer & Yue Qi & Markus Hirschberger, 2007. "Suitable-portfolio investors, nondominated frontier sensitivity, and the effect of multiple objectives on standard portfolio selection," Annals of Operations Research, Springer, vol. 152(1), pages 297-317, July.
    28. Adam Krzemienowski, 2009. "Risk preference modeling with conditional average: an application to portfolio optimization," Annals of Operations Research, Springer, vol. 165(1), pages 67-95, January.
    29. Branke, J. & Scheckenbach, B. & Stein, M. & Deb, K. & Schmeck, H., 2009. "Portfolio optimization with an envelope-based multi-objective evolutionary algorithm," European Journal of Operational Research, Elsevier, vol. 199(3), pages 684-693, December.
    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. Carla Oliveira Henriques & Maria Elisabete Neves & Licínio Castelão & Duc Khuong Nguyen, 2022. "Assessing the performance of exchange traded funds in the energy sector: a hybrid DEA multiobjective linear programming approach," Annals of Operations Research, Springer, vol. 313(1), pages 341-366, June.
    2. K. Liagkouras & K. Metaxiotis & G. Tsihrintzis, 2022. "Incorporating environmental and social considerations into the portfolio optimization process," Annals of Operations Research, Springer, vol. 316(2), pages 1493-1518, September.
    3. Adolfo Hilario-Caballero & Ana Garcia-Bernabeu & Jose Vicente Salcedo & Marisa Vercher, 2020. "Tri-Criterion Model for Constructing Low-Carbon Mutual Fund Portfolios: A Preference-Based Multi-Objective Genetic Algorithm Approach," IJERPH, MDPI, vol. 17(17), pages 1-15, August.

    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. K. Liagkouras & K. Metaxiotis, 2019. "Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem," Annals of Operations Research, Springer, vol. 272(1), pages 119-137, January.
    2. K. Liagkouras & K. Metaxiotis & G. Tsihrintzis, 2022. "Incorporating environmental and social considerations into the portfolio optimization process," Annals of Operations Research, Springer, vol. 316(2), pages 1493-1518, September.
    3. Vitali Alexeev & Mardi Dungey, 2015. "Equity portfolio diversification with high frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1205-1215, July.
    4. Alexeev, Vitali & Tapon, Francis, 2013. "Equity Portfolio Diversification: How Many Stocks are Enough? Evidence from Five Developed Markets," Working Papers 2013-16, University of Tasmania, Tasmanian School of Business and Economics, revised 20 Nov 2013.
    5. Vitali Alexeev & Francis Tapon, 2014. "The number of stocks in your portfolio should be larger than you think: diversification evidence from five developed markets," Published Paper Series 2014-4, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    6. David Bradfield & Brian Munro, 2017. "The number of stocks required for effective portfolio diversification: the South African case," South African Journal of Accounting Research, Taylor & Francis Journals, vol. 31(1), pages 44-59, January.
    7. A. Garcia-Bernabeu & J. V. Salcedo & A. Hilario & D. Pla-Santamaria & Juan M. Herrero, 2019. "Computing the Mean-Variance-Sustainability Nondominated Surface by ev-MOGA," Complexity, Hindawi, vol. 2019, pages 1-12, December.
    8. Florin Aliu & Besnik Krasniqi & Adriana Knapkova & Fisnik Aliu, 2019. "Interdependence and Risk Comparison of Slovak, Hungarian and Polish Stock Markets: Policy and Managerial Implications," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 69(2), pages 273-287, June.
    9. Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2013. "A new method for mean-variance portfolio optimization with cardinality constraints," Annals of Operations Research, Springer, vol. 205(1), pages 213-234, May.
    10. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    11. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    12. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2011. "Heuristic algorithms for the cardinality constrained efficient frontier," European Journal of Operational Research, Elsevier, vol. 213(3), pages 538-550, September.
    13. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    14. Azra Zaimovic & Adna Omanovic & Almira Arnaut-Berilo, 2021. "How Many Stocks Are Sufficient for Equity Portfolio Diversification? A Review of the Literature," JRFM, MDPI, vol. 14(11), pages 1-30, November.
    15. Gilles Boevi Koumou, 2016. "Risk reduction and Diversification within Markowitz's Mean-Variance Model: Theoretical Revisit," Papers 1608.05024, arXiv.org, revised Aug 2016.
    16. Frahm, Gabriel & Wiechers, Christof, 2011. "On the diversification of portfolios of risky assets," Discussion Papers in Econometrics and Statistics 2/11, University of Cologne, Institute of Econometrics and Statistics.
    17. Florian Methling & Rüdiger Nitzsch, 2020. "Tailor-made thematic portfolios: a core satellite optimization," Journal of Global Optimization, Springer, vol. 76(2), pages 317-331, February.
    18. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
    19. Nasim Dehghan Hardoroudi & Abolfazl Keshvari & Markku Kallio & Pekka Korhonen, 2017. "Solving cardinality constrained mean-variance portfolio problems via MILP," Annals of Operations Research, Springer, vol. 254(1), pages 47-59, July.
    20. E. Grizickas Sapkute & M. A. Sánchez-Granero & M. N. López García & J. E. Trinidad Segovia, 2022. "The impact of regulation-based constraints on portfolio selection: The Spanish case," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.

    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:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-016-2377-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.