Using Fuzzy Set Theory to Analyse Investments  and Select Portfolios of Tangible Investments in Uncertain Environments

Terceño, Antonio; Andrés, Jorge; Barberà, Glòria; Lorenzana, Tomás

doi:10.1142/s0218488503002077

Cited by 26 publications

(6 citation statements)

References 19 publications

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“…Let us now analyse the goodness of the approximation to the variables embedded in our analysis (volatility, Euribor one month rates and derivative prices) by TFNs with the same support and core as the original fuzzy number. This simple triangular approximation has been widely used in financial issues in contexts such as the final value of a pension plan (Jiménez and Rivas, 1998), capital budgeting (Terceño et al, 2003) and option pricing (Andrés-Sánchez, 2018).…”

Section: Empirical Applicationmentioning

confidence: 99%

A Systematic Overview of Fuzzy Random Option Pricing in Discrete Time and a Binomial Extension to Temporal Structure of Interest Rates

Andrés-Sánchez

2023

Preprint

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This paper makes a bibliographical analysis of fuzzy set theory (FST) contributions to option pricing with a fuzzy-random approach with detailed attention to those based in the binomial lattice. Likewise, we extend the fuzzy-random approach to yield curve binomial modelling. The bibliographical analysis was performed by applying PRISMA guidelines in the SCOPUS and WoS databases. We first present a structured report of papers about the more general fuzzy-random option pricing (FROP) field and identify principal outlets. Within FROP, we focus on the more concrete fuzzy random discrete time option pricing (FROPDT) in binomial and trinomial lattices, which is developed in greater detail. We detect that this groundwork has been extended to price options on stocks, stock indexes and real options, but no work has been done in the field of the term structure of interest rates and fixed income securities. Thus, we propose a fuzzy extension of the Ho-Lee model that we apply to the European interbank market and to price caplets.

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Section: Empirical Applicationmentioning

confidence: 99%

A Systematic Overview of Fuzzy Random Option Pricing in Discrete Time and a Binomial Extension to Temporal Structure of Interest Rates

Andrés-Sánchez

2023

Preprint

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“…Xu et al (2009) developed a fuzzy chance-constrained programming model for multi-project investment combination problem. Furthermore, Terceno et al (2003), Huang (2007), Bhattacharyya et al (2011), Tsao (2012 and Pérez and G omez (2016) are examples of using fuzzy set theory to deal with the capital budgeting and project selection problem. proposed two risk-based mathematical programming models to deal with the problem of project selection and scheduling, in a situation where experts estimate the project cash flows.…”

Section: Literature Reviewmentioning

confidence: 99%

Bi-objective optimization of a project selection and adjustment problem under risk controls

Heidari-Fathian

Davari-Ardakani

2019

JM2

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Purpose This study aims to deal with a project portfolio selection problem aiming to maximize the net present value of the project portfolio and minimize the resource usage variation between successive time periods. Design/methodology/approach A bi-objective mixed integer programming model is presented under resource constraints. The parameters related to outlays and net cash flows of existing and new projects are considered to be uncertain. An augmented ε-constraint (AUGMECON) method is used to solve the proposed model, and a fuzzy approach is used to find the most preferred Pareto-optimal solutions among those generated by AUGMECON method. The effectiveness of the proposed solution method is compared with three other multi-objective optimization methods. Finally, some sensitivity analyses are performed to assess the effect of changing a number of parameters on the values of objective functions. Findings The proposed approach helps corporations make optimal decisions for rebalancing their project portfolio, through launching some new candidate projects and upgrading some of the existing projects. Originality/value A novel bi-objective optimization model is proposed for designing a project portfolio problem under budget constraints and profit risk controls. Two types of projects including existing and new projects are considered in the problem. Minimization of resource usage variation between successive periods is considered in the model as one objective function. An AUGMECON method is used to solve the proposed bi-objective mathematical model. A fuzzy approach is applied to find the best Pareto-optimal solutions of AUGMECON method. Results of the proposed solution approach are compared with three other multi-objective decision-making methods in different numerical examples.

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“…However, the additional information about experts in the form of their weights might be very useful and would allow us to make more accurate results of the NPV analysis 6 . Suppose that Q experts provide information about every parameter of NPV such that the q-th expert supplies at most one interval from V k , k = 1, ..., T , or from R (see (4) and (5)). Suppose that the interval V ki is given by the experts with numbers belonging to the set W ki .…”

Section: Applying Information About Expertsmentioning

confidence: 99%

“…The fourth type of methods [4] is based on using fuzzy set theory or possibility theory [5,6], i.e., every parameter of a project is viewed as a fuzzy variable with a given possibility distribution or a membership function. However, these methods also have shortcomings.…”

Section: Introductionmentioning

confidence: 99%

Cautious Analysis of Project Risks by Interval-Valued Initial Data

Utkin

2006

Int. J. Unc. Fuzz. Knowl. Based Syst.

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One of the most common performance measures in selection and management of projects is the Net Present Value (NPV). In the paper, we study a case when initial data about the NPV parameters (cash flows and the discount rate) are represented in the form of intervals supplied by experts. A method for computing the NPV based on using random set theory is proposed and three conditions of independence of the parameters are taken into account. Moreover, the imprecise Dirichlet model for obtaining more cautious bounds for the NPV is considered. Numerical examples illustrate the proposed approach for computing the NPV.

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Using Fuzzy Set Theory to Analyse Investments and Select Portfolios of Tangible Investments in Uncertain Environments

Cited by 26 publications

References 19 publications

A Systematic Overview of Fuzzy Random Option Pricing in Discrete Time and a Binomial Extension to Temporal Structure of Interest Rates

A Systematic Overview of Fuzzy Random Option Pricing in Discrete Time and a Binomial Extension to Temporal Structure of Interest Rates

Bi-objective optimization of a project selection and adjustment problem under risk controls

Cautious Analysis of Project Risks by Interval-Valued Initial Data

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