The FPOM calculator is based on research conducted at LUT University.
Real Options analysis offers interesting insights on the value of assets and on the profitability of investments, which has made real options a growing field of academic research and practical application. Real option valuation is, however, often found to be difficult to understand and to implement due to the quite complex mathematics involved. Recent advances in modeling and analysis methods have made real option valuation easier to understand and to implement. This paper presents a new method (fuzzy pay-off method) for real option valuation using fuzzy numbers that is based on findings from earlier real option valuation methods and from fuzzy real option valuation. The method is intuitive to understand and far less complicated than any previous real option valuation model to date. The paper also presents the use of number of different types of fuzzy numbers with the method and an application of the new method in an industry setting.
Collan M., Fuller R., Mezei J. 2009. A Fuzzy Pay-Off Method for Real Option Valuation. Journal of Applied Mathematics and Decision Sciences.
By investigating issues facing Real Option (RO) adoption, this study attempts to dissect the perceived complexity of RO-theory and simplify its use for practitioners. Three real-world inspired business cases from Finland are analyzed using emerging methods for Real Options valuation (ROV), namely the Datar-Mathews (DM) underpinned by Monte Carlo (MC) simulation, and the Fuzzy Pay-Off (FPOM) methods.
Identified challenges of RO-theory adoption informed the implementation of chosen methods using spreadsheet software and the Python programming language. This process was conducted by developing a simplified set of universally applicable input parameters and procedures needed for Real Options analysis (ROA).
To evaluate the impact and insights achievable from simplifying ROA, three application cases from different contexts were selected: (1) evaluating strategic decisions involved in R&D initiatives, (2) estimating the value of flexibility “in” complex engineering systems, and (3) supporting inter-stakeholder negotiations and interactions by helping partners share risks and incentivize project stakeholders.
It is found that RO-theory can support decision-makers by helping evaluate, quantify, and harness the inherent risks and uncertainties encountered in investment decision-making. The performance and decision-making value of the two methods were compared. General-use spreadsheet and Jupyter notebook templates were created. The outcomes of the thesis would be of value to corporate and state decision-makers having potential for helping democratize Real Options methods.
Liukkonen S. 2023. Investigating real options valuation methods for high-value, high-uncertainty investments. LUT University of Technology.