A Fuzzy Pay-off Method for Real Option Valuation

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.Real Option Valuation; Fuzzy Real Options; Fuzzy Numbers

R.Fuller, Interdependence in fuzzy multiple objective programming,

Abstract In multiple objective programs [MOP], application functions are established to measure the degree of fulfillment of the decision maker's requirements (achievement of goals, nearness to an ideal point, satisfaction, etc.) about the objective functions (see e.g

Stability in Possibilistic Linear Equality Systems Under Continuous Triangular Norms

We consider linear equality systems where all the par1D may be fuzzy var191D specified by their possibilitydistr1D89 the oper38289 addition and multiplication by ar20 number of fuzzypar13081 ar defined via a suptr -11 nor composition, and the equationsar underon od in possibilistic sense. We show that when the tr2801D nor defining the oper03 and equations is continuous, then the possibilitydistr1D39 of the solution of these systems depend continuously on the fuzzy parameters

On Convex Linear Combination of Triangular Fuzzy Numbers

We study the problem: if ξ is a fuzzy number of symmetric triangular form, T is a triangular norm and # i [0, 1], i =1,...,n are real numbers, such that # 1 + # n = 1, then what is the membership function of the convex linear combination # 1 + # n (defined via sup-T-norm convolution)