Solving Discounting Problem Using Piece-Wise Quadratic Fuzzy Numbers

2021 ◽  
Vol 10 (4) ◽  
pp. 1-13
Author(s):  
Hemiden Abd El-Wahed Khalifa ◽  
Pavan Kumar
Keyword(s):  
Portfolio Selection ◽  
Fuzzy Numbers ◽  
Interval Number ◽  
Fuzzy Arithmetic ◽  
Investment Portfolio ◽  
Numerical Example ◽  
Research Article ◽  
Close Interval ◽  
Interval Approximation

The discounting problem is one of the important aspects in investment, portfolio selection, purchasing with credit, and many other financial operations. In this paper, a discounting problem using piecewise quadratic fuzzy numbers is proposed. The implementation of piecewise quadratic fuzzy numbers is described based on such operations. Fuzzy arithmetic and interval number arithmetic are used for computation. The close interval approximation of piecewise quadratic fuzzy numbers is used for solving the proposed discounting problem. This research article addresses the discounted investment for Year 1, Year 2, and Year 3. Additionally, the authors determine the cumulative discounted investment for different values of the parameter α ranging from 0 to 1. A discounting problem using piecewise quadratic fuzzy numbers is solved as a numerical example to illustrate the proposed procedure.

scholarly journals Defuzzification Formula for Modelling and Scheduling A Furniture Fuzzy Project Network

2019 ◽  
Vol 9 (1S5) ◽  
pp. 279-283
Keyword(s):  
Fuzzy Numbers ◽  
Critical Path ◽  
Numerical Example ◽  
Research Article ◽  
Duration Time ◽  
Project Network

-This research article presents a new defuzzification formula for deciding the critical path in a proposed network. Here we introduce an octagonal fuzzy numbers for representing the duration time. It is shown that it is better to use octagonal fuzzy numbers towards determining the critical path. A numerical example is given and the proposed formula as compared with the existing fuzzy numbers.

scholarly journals DUAL HESITANT FUZZY AGGREGATION OPERATORS

2015 ◽  
Vol 22 (2) ◽  
pp. 194-209 ◽  
Author(s):  
Dejian YU ◽  
Wenyu ZHANG ◽  
George HUANG
Keyword(s):  
Human Resources ◽  
Fuzzy Sets ◽  
Geometric Mean ◽  
Arithmetic Mean ◽  
Aggregation Operators ◽  
Fuzzy Arithmetic ◽  
Hesitant Fuzzy Sets ◽  
Numerical Example ◽  
Fuzzy Environment ◽  
Fuzzy Aggregation

Dual hesitant fuzzy sets (DHFSs) is a generalization of fuzzy sets (FSs) and it is typical of membership and non-membership degrees described by some discrete numerical. In this article we chiefly concerned with introducing the aggregation operators for aggregating dual hesitant fuzzy elements (DHFEs), including the dual hesitant fuzzy arithmetic mean and geometric mean. We laid emphasis on discussion of properties of newly introduced operators, and give a numerical example to describe the function of them. Finally, we used the proposed operators to select human resources outsourcing suppliers in a dual hesitant fuzzy environment.

Fuzzy Improvement-Project Portfolio Selection Considering Financial Performance and Customer Satisfaction

2020 ◽  
Vol 11 (2) ◽  
pp. 41-70
Author(s):  
Nantasak Tansakul ◽  
Pisal Yenradee
Keyword(s):  
Portfolio Selection ◽  
Employee Satisfaction ◽  
Significant Contribution ◽  
Fuzzy Numbers ◽  
Practical Method ◽  
Project Portfolio ◽  
Favorable Result ◽  
Triangular Fuzzy Numbers ◽  
Improvement Project ◽  
Project Portfolio Selection

This article develops a suitable and practical method for improvement-project portfolio selection under uncertainty, based on the requirements of a bank in Thailand. A significant contribution of this article is that the proposed method can determine an optimal project portfolio, to satisfy the customer/employee satisfaction targets and an investment budget constraint. This allows users to estimate parameters as triangular fuzzy numbers under pessimistic, most likely, and optimistic situations. Four mathematical models are proposed to maximize the defuzzified values of fuzzy NPV and fuzzy BCR, and to maximize the possibility that the project portfolio is economically justified under fuzzy situations of NPV and BCR. Results reveal that maximizing the defuzzified value of fuzzy NPV offers the most favorable result since it maximizes the current wealth of the bank. Additionally, the possibility that the entire project portfolio is economically justified under all fuzzy situations is relatively high for all numerical cases.

Extending TOPSIS in fuzzy environment by using the nearest weighted interval approximation of fuzzy numbers

2014 ◽  
Vol 27 (6) ◽  
pp. 2725-2736 ◽  
Author(s):  
Mohammad Izadikhah ◽  
Abolfazl Saeidifar ◽  
Razieh Roostaee
Keyword(s):  
Fuzzy Numbers ◽  
Fuzzy Environment ◽  
Interval Approximation

scholarly journals Discrete Analysis of Portfolio Selection with Optimal Stopping Time

2009 ◽  
Vol 2009 ◽  
pp. 1-9
Author(s):  
Jianfeng Liang
Keyword(s):  
Linear Programming ◽  
Portfolio Selection ◽  
Integer Linear Programming ◽  
Optimal Stopping ◽  
Programming Model ◽  
Stopping Time ◽  
Integer Linear Programming Model ◽  
Numerical Example ◽  
Expected Time ◽  
Selection Policy

Most of the investments in practice are carried out without certain horizons. There are many factors to drive investment to a stop. In this paper, we consider a portfolio selection policy with market-related stopping time. Particularly, we assume that the investor exits the market once his wealth reaches a given investment target or falls below a bankruptcy threshold. Our objective is to minimize the expected time when the investment target is obtained, at the same time, we guarantee the probability that bankruptcy happens is no larger than a given level. We formulate the problem as a mix integer linear programming model and make analysis of the model by using a numerical example.

On product of positive L-R fuzzy numbers and its application to multi-period portfolio selection problems

2019 ◽  
Vol 19 (1) ◽  
pp. 53-79 ◽  
Author(s):  
Xiang Li ◽  
Hui Jiang ◽  
Sini Guo ◽  
Wai-ki Ching ◽  
Lean Yu
Keyword(s):  
Portfolio Selection ◽  
Fuzzy Numbers ◽  
Selection Problems

scholarly journals A fuzzy approach to option pricing in a Levy process setting

2013 ◽  
Vol 23 (3) ◽  
pp. 613-622 ◽  
Author(s):  
Piotr Nowak ◽  
Maciej Romaniuk
Keyword(s):  
Option Pricing ◽  
Lévy Process ◽  
Fuzzy Numbers ◽  
Levy Process ◽  
Martingale Measure ◽  
Fuzzy Arithmetic ◽  
European Option ◽  
European Call Option ◽  
Log Price ◽  
Geometric Levy Process

Abstract In this paper the problem of European option valuation in a Levy process setting is analysed. In our model the underlying asset follows a geometric Levy process. The jump part of the log-price process, which is a linear combination of Poisson processes, describes upward and downward jumps in price. The proposed pricing method is based on stochastic analysis and the theory of fuzzy sets.We assume that some parameters of the financial instrument cannot be precisely described and therefore they are introduced to the model as fuzzy numbers. Application of fuzzy arithmetic enables us to consider various sources of uncertainty, not only the stochastic one. To obtain the European call option pricing formula we use the minimal entropy martingale measure and Levy characteristics.

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