Skip to main content

A Possibilistic Mean Absolute Deviation Portfolio Selection Model

  • Conference paper
Fuzzy Information and Engineering

Part of the book series: Advances in Soft Computing ((AINSC,volume 54))

Abstract

This paper deals with a mean absolute deviation portfolio selection problem with fuzzy return rates under fuzzy liquidity constraint, a new possibilistic programming approach based on possibilistic mean and fuzzy liquidity has been proposed, the problem can be reduced to a linear programming by possibility theory. A numerical example of portfolio selection problem is given to illustrate our proposed approach.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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. Arnott, R.D., Wanger, W.H.: The measurement and control of trading costs. Financial Analysts Journal 46(6), 73–80 (1990)

    Article  Google Scholar 

  2. Bellman, R., Zadeh, L.A.: Decision making in a fuzzy environment. Management Science 17, 141–164 (1970)

    Article  MathSciNet  Google Scholar 

  3. Carlsson, C., Fuller, R.: On possibilistic mean value and variance of fuzzy numbers. Fuzzy sets and systems 122, 315–326 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  4. Carlsson, C., Fuller, R., Majlender, P.: A possibilistic approach to selecting portfolios with highest utilty score. Fuzzy sets and systems 131, 13–21 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  5. Dubois, D., Prade, H.: Possibility theory. Plenum press, New York (1998)

    Google Scholar 

  6. Inuiguchi: Stochastic programming problems versus fuzzy mathematical programming probblems. Jpn. J. Fuzzy Theory Systems 4, 97–109 (1992)

    MATH  MathSciNet  Google Scholar 

  7. Konno, H., Yamazaki, H.: Mean absolute deviation portfolio optimization model and its application to Tokyo stock market. Manage. Sci. 37, 519–531 (1991)

    Article  Google Scholar 

  8. Konno, H., Wijayanayake, A.: Mean absolute deviation Portfolio optimization model under transaction costs. Journal of the operation researchp society of japan 42(4), 367–374 (1999)

    MathSciNet  Google Scholar 

  9. Konno, H., Wijayanayake, A.: Portfolio optimization problem under concave transaction costs and minimal transaction unit constraints. Math. Program. Ser. B 89, 233–250 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  10. Leon, T., Liern, V., Vercher, E.: Viability of infeasible portfolio selection problem: a fuzzy approach. European Journal of Operational Research 139, 178–189 (2002)

    Article  MATH  Google Scholar 

  11. Luhandjula, M.K., Gupta, M.M.: On fuzzy stochastic optimization. Fuzzy Sets and Systems 81, 47–55 (1996)

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  13. Ogryczak, W., Ruszczynski, A.: From stochastic dominance to mean-risk model. Eur. J. Oper. Res. 116, 33–50 (1999)

    Article  MATH  Google Scholar 

  14. Ostermask, R.: A fuzzy control model (FCM) for dynamic portfolio management. Fuzzy sets and Systems 78, 243–254 (1998)

    Article  Google Scholar 

  15. Ramaswamy, S.: Portfolio selection using fuzzy decision theory, working paper of bank for international settlements (59) (1998)

    Google Scholar 

  16. Tanaka, H., Guo, P., Trksen, I.B.: Portfolio selection based on fuzzy probabilities and possibility distributions. Fuzzy Sets and Systems 111, 387–397 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  17. Watada, J.: Fuzzy portfolio model for decision making in investment. In: Yoshida, Y. (ed.) Dynamical Aspects in fuzzy decision making, pp. 141–162. Physica Verlag, Heidelberg (2001)

    Google Scholar 

  18. Yoshimoto, A.: The mean-variance approach to portfolio optimization subject to transaction costs. Journal of the Operational Research Society of Japan 39, 99–117 (1996)

    MATH  MathSciNet  Google Scholar 

  19. Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy sets and systems 1, 3–28 (1978)

    Article  MATH  MathSciNet  Google Scholar 

  20. Lacagnina, V., Pecorella, A.: A stochastic soft constraints fuzzy model for a portfolio selection problem. Fuzzy Sets and Systems 157, 1317–1327 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  21. Zhang, W.: Possibilistic mean-standard deviation models to portfolio selection for bounded assets. Applied mathematics and computation 189, 1614–1623 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  22. Huang, X.: Risk curve and fuzzy portfolio selection. Applied mathematics and computation 55, 1102–1112 (2008)

    Article  MATH  Google Scholar 

  23. Enriqueta, V., Jos, B., Josicente, S.: Fuzzy portfolio optimization under downside risk measures. Fuzzy sets and systems 158, 769–782 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  24. Liu, S., Wang, R.-T.: A numerical solution method to interval quadratic programming. Applied mathematics and computation (2007), doi:10.1016/j.amc.2006.12.007

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chen, Gh., Liao, Xl. (2009). A Possibilistic Mean Absolute Deviation Portfolio Selection Model. In: Cao, By., Zhang, Cy., Li, Tf. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88914-4_49

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-88914-4_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88913-7

  • Online ISBN: 978-3-540-88914-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics