Real Option Analysis with Interval-Valued Fuzzy Numbers and the Fuzzy Pay-Off Method | SpringerLink
Skip to main content
Springer Nature Link
Log in

Real Option Analysis with Interval-Valued Fuzzy Numbers and the Fuzzy Pay-Off Method

  • Conference paper
  • First Online:
Advances in Fuzzy Logic and Technology 2017 (EUSFLAT 2017, IWIFSGN 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 641))

  • 959 Accesses

Abstract

This paper presents an extension of the fuzzy pay-off method for real option valuation using interval-valued fuzzy numbers. To account for a higher level of imprecision that can be present in many applications, we propose to use triangular upper and lower membership functions as the basis of real option analysis. In the paper, analytical formulas are derived for the triangular case by calculating the possibilistic mean of truncated interval-valued triangular fuzzy numbers. A numerical example of a cash-flow analysis is presented to illustrate the use of the proposed approach.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 22879
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 28599
Price includes VAT (Japan)
  • 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

Similar content being viewed by others

References

  1. Carlsson, C., Fullér, R.: On possibilistic mean value and variance of fuzzy numbers. Fuzzy Set. Syst. 122, 315–326 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  2. Carlsson, C., Fullér, R., Mezei, J.: Project selection with interval-valued fuzzy numbers. In: Proceedings of the Twelfth IEEE International Symposium on Computational Intelligence and Informatics (CINTI 2011), Budapest, Hungary, pp. 23–26. IEEE (2011)

    Google Scholar 

  3. Collan, M., Fullér, R., Mezei, J.: A fuzzy pay-off method for real option valuation. J. Appl. Math. Decis. Sci. 2009 (2009). Advances in Decision Sciences, Article ID 238196, 14 pages

    Google Scholar 

  4. Datar, V., Mathews, S.: A practical method for valuing real options: the boeing approach. J. Appl. Corp. Fin. 19, 95–104 (2007)

    Article  Google Scholar 

  5. Dubois, D., Prade, H.: Interval-valued fuzzy sets, possibility theory and imprecise probability. In: Proceedings of the International Conference in Fuzzy Logic and Technology, Barcelona, Spain, pp. 314–319 (2005)

    Google Scholar 

  6. Ho, S.-H., Liao, S.H.: A fuzzy real option approach for investment project valuation. Exp. Syst. Appl. 38, 15296–15302 (2011)

    Article  Google Scholar 

  7. Liu, P.: Some Hamacher aggregation operators based on the interval-valued intuitionistic fuzzy numbers and their application to group decision making. IEEE Trans. Fuzzy Syst. 22, 83–97 (2014)

    Article  Google Scholar 

  8. Mathews, S., Salmon, J.: Business engineering: a practical approach to valuing high-risk, high-return projects using real options. In: Gray, P. (ed.) Tutorials in Operations Research: Informs (2007)

    Google Scholar 

  9. Muzzioli, S., De Baets, B.: Fuzzy approaches to option price modelling. IEEE Trans. Fuzzy Syst. doi:10.1109/TFUZZ.2016.2574906

  10. Ozen, T., Garibaldi, J.M.: Effect of type-2 fuzzy membership function shape on modelling variation in human decision making. In: Proceedings of Thee IEEE International Conference on Fuzzy Systems, Budapest, Hungary, pp. 971–976. IEEE (2004)

    Google Scholar 

  11. Pedrycz, W.: Why triangular membership functions. Fuzzy Set. Syst. 64, 21–30 (1994)

    Article  MathSciNet  Google Scholar 

  12. Wang, G., Li, X.: The applications of interval-valued fuzzy numbers and interval-distribution numbers. Fuzzy Set. Syst. 98, 331–335 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  13. Wang, Z., Kerre, E.E.: Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Set. Syst. 118, 375–385 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  14. Wu, J., Chiclana, F.: A social network analysis trustconsensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations. Knowl. Based Syst. 59, 97–107 (2014)

    Article  Google Scholar 

  15. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  MATH  Google Scholar 

  16. Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning-I. Inf. Sci. 8, 199–249 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  17. Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Set. Syst. 1, 3–28 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  18. Zmeškal, Z.: Generalised soft binomial American real option pricing model (fuzzystochastic approach). Eur. J. Oper. Res. 207, 1096–1103 (2010)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Business and Management, Lappeenranta University of Technology, Lappeenranta, Finland

    József Mezei, Mikael Collan & Pasi Luukka

Authors
  1. József Mezei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mikael Collan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pasi Luukka
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to József Mezei .

Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Eulalia Szmidt

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Sławomir Zadrożny

  4. Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir T. Atanassov

  5. WIT - Warsaw School of Information Technology, Warsaw, Poland

    Maciej Krawczak

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Mezei, J., Collan, M., Luukka, P. (2018). Real Option Analysis with Interval-Valued Fuzzy Numbers and the Fuzzy Pay-Off Method. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds) Advances in Fuzzy Logic and Technology 2017. EUSFLAT IWIFSGN 2017 2017. Advances in Intelligent Systems and Computing, vol 641. Springer, Cham. https://doi.org/10.1007/978-3-319-66830-7_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-66830-7_46

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66829-1

  • Online ISBN: 978-3-319-66830-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation