Skip to main content
SpringerLink
Log in

A New MOPSO to Solve a Multi-Objective Portfolio Selection Model with Fuzzy Value-at-Risk

  • Conference paper
Knowledge-Based and Intelligent Information and Engineering Systems (KES 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6883))

  • 2128 Accesses

Abstract

This study proposes an novel fuzzy multi-objective model that can evaluate the invest risk properly and increase the probability of obtaining the expected return. In building the model, fuzzy Value-at-Risk is used to evaluate the exact future risk, in term of loss. And, variance is utilized to make the selection more stable. This model can provide investors with more significant information in decision-making. To solve this model, a new Pareto-optimal set based multi-objective particle swarm optimization algorithm is designed to obtain better solutions among the Pareto-front. At the end of this study, the proposed model and algorithm are exemplified by one numerical example. Experiment results show that the model and algorithm are effective in solving the multi-objective portfolio selection problem.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Markowitz, H.: Portfolio selection. Journal of Finance 7(1), 77–91 (1952)

    Google Scholar 

  2. Watada, J.: Fuzzy portfolio selection and its application to decision making. Tatra Mountains Math. Publication 13(4), 219–248 (1997)

    MATH  MathSciNet  Google Scholar 

  3. Huang, X.: Mean-entropy models for fuzzy portfolio selection. IEEE Transactions on Fuzzy Systems 16(4), 1096–1101 (2008)

    Article  Google Scholar 

  4. Li, X., Qin, Z., Kar, S.: Mean-variance-skewness model for portfolio selection with fuzzy returns. European Journal of Operational Research 202(1), 239–247 (2009)

    Article  MATH  Google Scholar 

  5. Huang, X.: Mean-semivariance models for fuzzy portfolio selection. Journal of Computational and Applied Mathematics 217(1), 1–8 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  6. Wang, B., Wang, S., Watada, J.: Fuzzy portfolio selection based on Value-at-Risk. IEEE Transactions on Fuzzy Systems 19(4) (to be published 2011)

    Google Scholar 

  7. Jana, P., Roy, T.K., Mazumder, S.K.: Multi-objective possibilistic model for portfolio selection with transaction cost. Journal of Computational and Applied Mathematics 228(1), 188–196 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  8. Steuer, R.E., Qi, Y., Hirschberger, M.: Multiple Objectives in Portfolio Selection. Journal of Financial Decision Making 1(1) (2005)

    Google Scholar 

  9. Zhang, Y., Li, X., Wong, H., Tan, L.: Fuzzy multi-objective portfolio selection model with transaction cost. In: Proceeding of the 2009 IEEE International Conference on Fuzzy System, pp. 273–278 (2009)

    Google Scholar 

  10. Liu, B., Liu, Y.K.: Expected value of fuzzy variable and fuzzy expected value models. IEEE Transaction on Fuzzy Systems 10(4), 445–450 (2002)

    Article  Google Scholar 

  11. Nahmias, S.: Fuzzy variable. Fuzzy Sets and Systems 1(2), 97–101 (1978)

    Article  MATH  MathSciNet  Google Scholar 

  12. Wang, S., Liu, Y., Dai, X.: On the continuity and absolute continuity of credibility functions. Journal of Uncertain System 1(2), 185–200 (2007)

    Google Scholar 

  13. Wang, S., Watada, J., Pedrycz, W.: Value-at-Risk-Based two-stage fuzzy facility location problems. IEEE Transactions on Industrial Informatics 5(4), 465–482 (2009)

    Article  Google Scholar 

  14. Duffie, D., Pan, J.: An overview of value-at-risk. Journal of Derivatives 4(3), 7–49 (1997)

    Article  Google Scholar 

  15. Jorion, P.: Value at Risk: The New Benchmark for Managing Financial Risk. McGraw-Hill, New York (2006)

    Google Scholar 

  16. Wang, S., Watada, J.: Two-stage fuzzy stochastic programming with Value-at-Risk criteria. Applied Soft Computing 11(1), 1044–1056 (2011)

    Article  Google Scholar 

  17. Zmeskal, Z.: Value at risk methodology of international index portfolio under soft conditions. International Review of Financial Analysis 14(6), 263–275 (2005)

    Article  Google Scholar 

  18. Wang, B., Li, Y., Watada, J.: Fuzzy Power System Reliability Model Based on Value-at-Risk. In: Proceedings of the 14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, pp. 445–453 (2010)

    Google Scholar 

  19. Wang, B., Li, Y., Watada, J.: Re-Scheduling of Unit Commitment Based on Customers’ Fuzzy Requirements for Power Reliability. IEICE Transactions on Information and Systems E94-D(7) (to be published 2011)

    Google Scholar 

  20. Jabr, R.A.: Robust self-scheduling under price uncertainty using conditional value-at-risk. IEEE Transactions on Power Systems 20(4), 1852–1858 (2005)

    Article  Google Scholar 

  21. Kennedy, J., Eberhaart, R.C.: Particle swarm optimization. In: Proceedings of the 1995 IEEE International Conference on Neual Network, IV, pp. 1942–1948 (1995)

    Google Scholar 

  22. Chankong, V., Haimes, Y.: Multi-objective decision making theory and methodology. North-Holland, New York (1983)

    MATH  Google Scholar 

  23. Taboada, H.A., Espiritu, J.F., Coit, D.W.: MOMS-GA: A Multi-Objective Multi-State Genetic Algorithm for System Reliability Optimization Design Problems. IEEE Trans. on Reliability 57(1), 182–191 (2008)

    Article  Google Scholar 

  24. Yalcinoz, T., Koksoy, O.: A multi-objective optimization method to environmental economic dispatch. Int. J. Electr. Power Energy Syst 29(1), 42–50 (2007)

    Article  Google Scholar 

  25. Branke, J., Scheckenbach, B., Stein, M., Deb, K., Schmeck, H.: Portfolio optimization with an envelope-based multi-objective evolutionary algorithm. European Journal of Operational Research 199(3), 684–693 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  26. Tripathi, P., Bandyopadhyay, S., Pal, S.: Multi-Objective Particle Swarm Optimization with time variant inertia and acceleration coefficients. Information Sciences 177(22), 5033–5049 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  27. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions On Evolutionary Computation 6(2), 182–197 (2002)

    Article  Google Scholar 

  28. Coello, C., Pulido, G., Lechuga, M.: Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation 8(3), 256–279 (2004)

    Article  Google Scholar 

  29. Li, X.: A non-dominated sorting particle swarm optimizer for multi-objective optimization. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2723, pp. 37–48. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  30. Coello, C., Veldhuizen, D., Lamount, G.: Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic Publishers, Dordrecht (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, 808-0135, Japan

    Bo Wang, You Li & Junzo Watada

Authors
  1. Bo Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. You Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junzo Watada
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Integrated Sensor Systems, University of Kaiserslautern, Erwin-Schroedinger-str. 12, 67663, Kaiserslautern, Germany

    Andreas König

  2. Knowledge-Based Systems Group, Department of Computer Science, University of Kaiserslautern, P.O. Box 3049, 67653, Kaiserslautern, Germany

    Andreas Dengel

  3. School of Business, University of Applied Sciences Northwestern Switzerland, Riggenbachstr. 16, 4600, Olten, Switzerland

    Knut Hinkelmann

  4. Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, 599-8531, Osaka, Japan

    Koichi Kise

  5. KES International, P.O. Box 2115, BN43 9AF, Shoreham-by-sea, UK

    Robert J. Howlett

  6. University of South Australia, Adelaide, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wang, B., Li, Y., Watada, J. (2011). A New MOPSO to Solve a Multi-Objective Portfolio Selection Model with Fuzzy Value-at-Risk. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23854-3_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23854-3_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23853-6

  • Online ISBN: 978-3-642-23854-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation