The fuzzy pay-off method for real option valuation (FPOM or pay-off method)
is a method for
valuing real options
Real options valuation, also often termed real options analysis,Adam Borison (Stanford University)''Real Options Analysis: Where are the Emperor's Clothes?''
(ROV or ROA) applies option (finance), option Valuation of options, valuation technique ...
, developed by Mikael Collan, Robert Fullér, and József Mezei; and published in 2009. It is based on the use of
fuzzy logic
Fuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely ...
and
fuzzy numbers for the creation of the possible pay-off
distribution Distribution may refer to:
Mathematics
*Distribution (mathematics), generalized functions used to formulate solutions of partial differential equations
*Probability distribution, the probability of a particular value or value range of a varia ...
of a project (real option). The structure of the method is similar to the probability theory based
Datar–Mathews method for real option valuation, but the method is not based on probability theory and uses fuzzy numbers and possibility theory in framing the real option valuation problem.
Method
The Fuzzy pay-off method derives the real option value from a pay-off distribution that is created by using three or four cash-flow scenarios (most often created by an expert or a group of experts). The pay-off distribution is created simply by assigning each of the three cash-flow scenarios a corresponding definition with regards to a fuzzy number (triangular fuzzy number for three scenarios and a trapezoidal fuzzy number for four scenarios). This means that the pay-off distribution is created without any simulation whatsoever. This makes the procedure easy and transparent. The scenarios used are a minimum possible scenario (the lowest possible outcome), the maximum possible scenario (the highest possible outcome) and a best estimate (most likely to happen scenario) that is mapped as a fully possible scenario with a full degree of membership in the set of possible outcomes, or in the case of four scenarios used - two best estimate scenarios that are the upper and lower limit of the interval that is assigned a full degree of membership in the set of possible outcomes.
The main observations that lie behind the model for deriving the real option value are the following:
# The fuzzy NPV of a project is (equal to) the pay-off distribution of a project value that is calculated with
fuzzy numbers.
# The mean value of the positive values of the fuzzy
NPV is the "possibilistic" mean value of the positive fuzzy NPV values.
# Real option value, ROV, calculated from the fuzzy NPV is the "possibilistic"
mean value
A mean is a quantity representing the "center" of a collection of numbers and is intermediate to the extreme values of the set of numbers. There are several kinds of means (or "measures of central tendency") in mathematics, especially in statist ...
of the positive fuzzy NPV values multiplied with the positive area of the fuzzy NPV over the total area of the fuzzy NPV.
The real option formula can then be written simply as:
: