Hamid Nayebpur and Mohsen Nazem Bokaei
The purpose of this paper is to present a new technique to portfolio selection using a genetic algorithm (GA) and fuzzy synthetic evaluation (FSE). Portfolio selection is a…
Abstract
Purpose
The purpose of this paper is to present a new technique to portfolio selection using a genetic algorithm (GA) and fuzzy synthetic evaluation (FSE). Portfolio selection is a multi-objective/criteria decision-making problem in financial management.
Design/methodology/approach
The proposed approach solves the problem in two stages. In the first stage, by using a GA and FSE, the weight of criteria will be calculated. Euclidean distance between the computed overall performance evaluation and the surveyed overall performance evaluation is used to determine the weight of criteria. In the second stage, by using a GA and FSE, portfolios will be prioritized. A multi-objective GA is used to determine return and risk in the efficient frontier. A decision making approach is based on FSE to select the best portfolio from among the solutions obtained by a multi objective GA.
Findings
The main advantage of the proposed approach is to help an investor to find a portfolio which has best performance, and portfolio selection does not rely on expert knowledge.
Originality/value
The value of the paper is in it using a new approach to determine the weight of criteria and portfolio selection. It surveys firms’ performance in the stock market, based on which the weight of criteria will be determined and portfolios will be prioritized.
Details
Keywords
Hamid Nayebpour and Mohsen Nazem Bokaei
The purpose of this paper is to present a new technique for the determination of effective criteria weight on satisfaction using genetic algorithm and fuzzy synthetic evaluation.
Abstract
Purpose
The purpose of this paper is to present a new technique for the determination of effective criteria weight on satisfaction using genetic algorithm and fuzzy synthetic evaluation.
Design/methodology/approach
The weight values express the relative importance of criteria. In most of research works, weight values depend heavily on expert knowledge, and customer’s perspective have not been considered. The proposed approach determines the criteria weight on satisfaction using genetic algorithm and fuzzy synthetic evaluation considering Euclidean distance between the computed overall satisfaction evaluation and the surveyed overall satisfaction evaluation.
Findings
The research findings show that different segments of customer have various needs and explain causes of various needs in customers using genetic algorithm and fuzzy synthetic evaluation.
Originality/value
The value of the paper is in it using a new approach in order to determine the weight of criteria. The main advantage of proposed approach is that it will help managers and researchers to determine the weight of criteria on satisfaction, and this process will no longer just rely on expert knowledge.