Skip to main content

Advertisement

SpringerLink
Log in

Multiobjective expected value model for portfolio selection in fuzzy environment

  • Original Paper
  • Published:
Optimization Letters Aims and scope Submit manuscript

Abstract

In this paper, we propose a credibilistic framework for portfolio selection problem using an expected value multiobjective model with fuzzy parameters. We consider short term return, long term return, risk and liquidity as key financial criteria. A solution procedure comprising fuzzy goal programming and fuzzy simulation based real-coded genetic algorithm is developed to solve the model. The proposed solution approach is considered advantageous particularly for the cases where the fuzzy parameters of the problem may assume any general functional form. An empirical study is included to illustrate the usefulness of the proposed model and solution approach in real-world applications of portfolio selection.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Bhattacharyya R., Kar S., Majumder D.D.: Fuzzy mean-variance-skewness portfolio selection models by interval analysis. Comput. Math. Appl. 61, 126–137 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  2. Carlsson C., Fullér R., Majlender P.: A possibilistic approach to selecting portfolios with highest utility score. Fuzzy Set. Syst. 131, 13–21 (2002)

    Article  MATH  Google Scholar 

  3. Charnes A., Cooper W.W.: Management Models and Industrial Applications of Linear Programming. Wiley, New York (1961)

    Google Scholar 

  4. Chen J.S., Hou J.L., Wu S.M., Chang-Chien Y.W.: Constructing investment strategy portfolios by combination genetic algorithms. Expert. Syst. Appl. 36, 3824–3828 (2009)

    Article  Google Scholar 

  5. Chen W.: Weighted portfolio selection models based on possibility theory. Fuzzy Inf. Eng. 2, 115–127 (2009)

    Article  Google Scholar 

  6. Chow K., Denning K.C.: On variance and lower partial moment betas. The equivalence of systematic risk measures. J. Bus. Finance Account. 21, 231–241 (1994)

    Article  Google Scholar 

  7. Fang Y., Lai K.K., Wang S.Y.: Portfolio rebalancing model with transaction costs based on fuzzy decision theory. Eur. J. Oper. Res. 175, 879–893 (2006)

    Article  MATH  Google Scholar 

  8. Grootveld H., Hallerbach W.: Variance vs downside risk: is there really much difference?. Eur. J. Oper. Res. 114, 304–319 (1999)

    Article  MATH  Google Scholar 

  9. Gupta P., Mehlawat M.K., Saxena A.: Asset portfolio optimization using fuzzy mathematical programming. Inform. Sci. 178, 1734–1755 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  10. Gupta P., Mehlawat M.K., Saxena A.: A hybrid approach to asset allocation with simultaneous consideration of suitability and optimality. Inform. Sci. 180, 2264–2285 (2010)

    Article  Google Scholar 

  11. Gupta P., Inuiguchi M., Mehlawat M.K.: A hybrid approach for constructing suitable and optimal portfolios. Expert. Syst. Appl. 38, 5620–5632 (2011)

    Article  Google Scholar 

  12. Gupta, P., Mehlawat, M.K., Mittal, G.: Asset portfolio optimization using support vector machines and real-coded genetic algorithm. J. Global Optim. 53, 297–315 (2012)

    Google Scholar 

  13. Hasuike T., Katagiri H., Ishii H.: Portfolio selection problems with random fuzzy variable returns. Fuzzy Set. Syst. 160, 2579–2596 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  14. Holland J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)

    Google Scholar 

  15. Huang X.: Portfolio selection with fuzzy returns. J. Intell. Fuzzy Syst. 18, 383–390 (2007)

    MATH  Google Scholar 

  16. Huang X.: Mean-semivariance models for fuzzy portfolio selection. J. Comput. Appl. Math. 217, 1–8 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  17. Huang X.: A review of credibilistic portfolio selection. Fuzzy Optim. Decis. Making 8, 263–281 (2009)

    Article  MATH  Google Scholar 

  18. Inuiguchi M., Ramik J.: Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy Set. Syst. 111, 3–28 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  19. Inuiguchi M., Tanino T.: Portfolio selection under independent possibilistic information. Fuzzy Set. Syst. 115, 83–92 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  20. Konno H., Yamazaki H.: Mean-absolute deviation portfolio optimization model and its applications to the Tokyo Stock Market. Manag. Sci. 37, 519–531 (1991)

    Article  Google Scholar 

  21. Li X., Liu B.: A sufficient and necessary condition for credibility measures. Int. J. Uncertain. Fuzziness Knowledge-Based Syst. 14, 527–535 (2006)

    Article  MATH  Google Scholar 

  22. Li X., Zhang Y., Wong H.S., Qin Z.: A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns. J. Comput. Appl. Math. 233, 264–278 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  23. Li X., Qin Z., Kar S.: Mean-variance-skewness model for portfolio selection with fuzzy returns. Eur. J. Oper. Res. 202, 239–247 (2010)

    Article  Google Scholar 

  24. Liu B., Liu Y.K.: Expected value of fuzzy variable and fuzzy expected value models. IEEE Trans. Fuzzy Syst. 10, 445–450 (2002)

    Article  Google Scholar 

  25. Liu B.: Uncertainty Theory: An Introduction to its Axiomatic Foundations. Springer, Berlin (2004)

    Book  Google Scholar 

  26. Liu B.: A survey of credibility theory. Fuzzy Optim. Decis. Making 5, 387–408 (2006)

    Article  Google Scholar 

  27. Luengo E.A.: Fuzzy mean-variance portfolio selection problems. Adv. Model. Optim. 12, 399–410 (2010)

    MathSciNet  Google Scholar 

  28. Markowitz H.M.: Portfolio selection. J. Finance 7, 77–91 (1952)

    Google Scholar 

  29. Markowitz H.M.: Portfolio Selection: Efficient Diversification of Investments. Wiley, New York (1959)

    Google Scholar 

  30. Markowitz H.M.: Computation of mean-semivariance efficient sets by the critical line algorithm. Ann. Oper. Res. 45, 307–317 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  31. Qin Z., Li X., Ji X.: Portfolio selection based on fuzzy cross-entropy. J. Comput. Appl. Math. 228, 139–149 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  32. Rom B.M., Ferguson K.W.: portfolio theory comes of age. J. Invest. 3, 11–17 (1994)

    Article  Google Scholar 

  33. Speranza M.G.: Linear programming models for portfolio optimization. Finance 14, 107–123 (1993)

    Google Scholar 

  34. Wang S.Y., Zhu S.S.: On fuzzy portfolio selection problem. Fuzzy Optim. Decis. Making 1, 361–377 (2002)

    Article  MATH  Google Scholar 

  35. Yang S.C., Lin T.L., Chang T.J., Chang K.J.: A semi-variance portfolio selection model for military investment assets. Expert. Syst. Appl. 38, 2292–2301 (2011)

    Article  Google Scholar 

  36. Yoshida Y.: An estimation model of value-at-risk portfolio under uncertainity. Fuzzy Set. Syst. 160, 3250–3262 (2009)

    Article  MATH  Google Scholar 

  37. Zadeh L.A.: Fuzzy sets. Inform. Contr. 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  38. Zadeh L.A.: Towards a generalized theory of uncertainity (GTU)-an outline. Inform. Sci. 172, 1–40 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  39. Zhang W.G., Wang Y.L., Chen Z.P., Nie Z.K.: Possibilistic mean-variance models and efficient frontiers for portfolio selection problem. Inform. Sci. 177, 2787–2801 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  40. Zhang X., Zhang W.G., Cai R.: Portfolio adjusting optimization under credibility measures. J. Comput. Appl. Math. 234, 1458–1465 (2010)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Operational Research, University of Delhi, Delhi, India

    Pankaj Gupta & Garima Mittal

  2. Flat No. 01, Kamayani Kunj, Plot No. 69, Indraprastha Extension, Delhi, 110092, India

    Pankaj Gupta

  3. Department of Decision Sciences, Apeejay School of Management, Dwarka, New Delhi, India

    Mukesh Kumar Mehlawat

Authors
  1. Pankaj Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Garima Mittal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mukesh Kumar Mehlawat
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pankaj Gupta.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gupta, P., Mittal, G. & Mehlawat, M.K. Multiobjective expected value model for portfolio selection in fuzzy environment. Optim Lett 7, 1765–1791 (2013). https://doi.org/10.1007/s11590-012-0521-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11590-012-0521-5

Keywords

Search

Navigation