Granular fuzzy pay-off method for real option valuation

Francisco Javier Cabrerizo*, Markku Heikkilä, Jozsef Mezei, Juan Antonio Morente-Molinera, Enrique Herrera-Viedma, Christer Carlsson

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review


In the last decade, the fuzzy pay-off method has emerged as a widely used alternative approach for real option valuation thanks to its simplicity that makes it easily approachable by practitioners from various application domains. In this study, a new direction for real option valuation is pursued by proposing a granular fuzzy pay-off method. We motivate the proposal by discussing how the extension of the original approach with granular representation can further improve the fuzzy pay-off method. The design of the granular fuzzy pay-off method is founded on the principle of justifiable granularity, which in turn relies on numeric data to build information granules that are semantically sound and experimentally justified. To illustrate the method, a case study in R&D investment in manufacturing is worked out. The extended granular fuzzy pay-off method improves performance and usability in cases with uncertainty.
Original languageEnglish
JournalExpert Systems with Applications
Publication statusPublished - 2020
MoE publication typeA1 Journal article-refereed


  • Real options
  • Fuzzy pay-off method
  • Principle of justifiable granularity
  • Granular computing
  • Information granules

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