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

doi:10.1016/j.eswa.2020.113597

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

Information Systems

Research output: Contribution to journal › Article › Scientific › peer-review

Abstract

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 language	English
Journal	Expert Systems with Applications
Volume	159
DOIs	https://doi.org/10.1016/j.eswa.2020.113597
Publication status	Published - 2020
MoE publication type	A1 Journal article-refereed

Keywords

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

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title = "Granular fuzzy pay-off method for real option valuation",

abstract = "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.",

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author = "Cabrerizo, {Francisco Javier} and Markku Heikkil{\"a} and Jozsef Mezei and Morente-Molinera, {Juan Antonio} and Enrique Herrera-Viedma and Christer Carlsson",

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doi = "10.1016/j.eswa.2020.113597",

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T1 - Granular fuzzy pay-off method for real option valuation

AU - Cabrerizo, Francisco Javier

AU - Heikkilä, Markku

AU - Mezei, Jozsef

AU - Morente-Molinera, Juan Antonio

AU - Herrera-Viedma, Enrique

AU - Carlsson, Christer

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Real options

KW - Fuzzy pay-off method

KW - Principle of justifiable granularity

KW - Granular computing

KW - Information granules

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DO - 10.1016/j.eswa.2020.113597

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