New model and method for portfolios selection

Hadi, Ali S.; Naggar, Azza A. El; Bary, Mona N. Abdel

doi:10.12988/ams.2016.58541

Cited by 12 publications

(6 citation statements)

References 33 publications

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“…A fundamental answer to this problem was given by Markowitz [38], who proposed the mean-variance model laying the basis of modern portfolio theory [40][41][42][43]. Markowitz defined the problem as a trade-off between the expected return and the expected risk of a portfolio [44].…”

Section: The Application Of Multi-criteria Decision-making Methods Inmentioning

confidence: 99%

“…This paper will not address the first two directions and will only focus on the third development direction, even though it is interwoven with the second one, namely the introduction of alternative measures of risk. Lately, more and more authors come to realize the benefit of incorporating an additional criterion and/or constraint in project selection [41][42][43][44][45]47]. The analysis of this direction demonstrates mean-risk-third parameter models [41,42,46,[48][49][50][51][52][53][54].…”

Section: The Application Of Multi-criteria Decision-making Methods Inmentioning

confidence: 99%

“…Quite a few authors use semi-deviation or semi-variance below the mean as a risk measure (downside risk) in portfolio selection [29,39,51,[84][85][86][87][88]. However, given that semi-variance is difficult to calculate [89], we, like many other authors [41,44,52,54,90], use variance in our work.…”

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confidence: 99%

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Sustainability-Oriented Financial Resource Allocation in a Project Portfolio through Multi-Criteria Decision-Making

Dobrovolskienė

Tamošiūnienė

2016

Sustainability

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Abstract:Modern portfolio theory attempts to maximize the expected return of a portfolio for a given level of portfolio risk, or equivalently minimize risk for a given level of expected return. The reality, however, shows that, when selecting projects to a portfolio and allocating resources in the portfolio, an increasing number of organizations take into account other aspects as well. As a result of the sole purpose (risk-return), it offers only a partial solution for a sustainable organization. Existing project portfolio selection and resource allocation methods and models do not consider sustainability. Therefore, the aim of this article is to develop a sustainability-oriented model of financial resource allocation in a project portfolio by integrating a composite sustainability index of a project into Markowitz's classical risk-return scheme (mean-variance model). The model was developed by applying multi-criteria decision-making methods. The practicability of the model was tested by an empirical study in a selected construction company. The proposed sustainability-oriented financial resource allocation model could be used in allocating financial resources in any type of business. The use of the model would not only help organisations to manage risk and achieve higher return but would also allow carrying out sustainable projects, thereby promoting greater environmental responsibility and giving more consideration to the wellbeing of future generations. Moreover, the model allows quantifying the impact of the integration of sustainability into financial resource allocation on the return of a portfolio.

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Section: The Application Of Multi-criteria Decision-making Methods Inmentioning

confidence: 99%

Section: The Application Of Multi-criteria Decision-making Methods Inmentioning

confidence: 99%

See 1 more Smart Citation

Sustainability-Oriented Financial Resource Allocation in a Project Portfolio through Multi-Criteria Decision-Making

Dobrovolskienė

Tamošiūnienė

2016

Sustainability

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“…Moreover, Genetic Algorithms have been used for selecting and evaluating investment portfolios [11]. As seen in [12], the mean-variance approach was used as a reference to propose a new model which included different constraints, using GA as an optimization method. Chen et al, applied machine learning algorithms to predict asset values of the Shanghai stock market; they used a GA to solve a multi-objective optimization problem [13].…”

Section: Introductionmentioning

confidence: 99%

SAIPO-TAIPO and Genetic Algorithms for Investment Portfolios

Frausto–Solís

Aldaz

Angel

et al. 2022

Axioms

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The classic model of Markowitz for designing investment portfolios is an optimization problem with two objectives: maximize returns and minimize risk. Various alternatives and improvements have been proposed by different authors, who have contributed to the theory of portfolio selection. One of the most important contributions is the Sharpe Ratio, which allows comparison of the expected return of portfolios. Another important concept for investors is diversification, measured through the average correlation. In this measure, a high correlation indicates a low level of diversification, while a low correlation represents a high degree of diversification. In this work, three algorithms developed to solve the portfolio problem are presented. These algorithms used the Sharpe Ratio as the main metric to solve the problem of the aforementioned two objectives into only one objective: maximization of the Sharpe Ratio. The first, GENPO, used a Genetic Algorithm (GA). In contrast, the second and third algorithms, SAIPO and TAIPO used Simulated Annealing and Threshold Accepting algorithms, respectively. We tested these algorithms using datasets taken from the Mexican Stock Exchange. The findings were compared with other mathematical models of related works, and obtained the best results with the proposed algorithms.

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“…Hadi et. al., [8] applied a pareto based enhanced genetic algorithm with four further constraints for portfolio optimization and used data selected from the Egyptian Exchange. They show that the proposed model is best among all the conventional optimization models.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Genetic Algorithm & Fuzzy Logic for Portfolio Optimization

Panwar*¹,

Jha²,

Srivastava³

2019

IJRTE

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Teaching-learning based optimization (TLBO), biogeography-based optimization (BBO) and fuzzy multiobjective linear programming (FMOLP) are compared in this paper for portfolio optimization. A hybrid approach has been adopted for this comparative study which is a combination of a few methods, such as investor topology, cluster analysis, analytical hierarchy process (AHP) and optimization techniques. Return, risk, liquidity, coefficient of variation (CV) and AHP weighted scores are used as the objective function for optimization.

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New model and method for portfolios selection

Cited by 12 publications

References 33 publications

Sustainability-Oriented Financial Resource Allocation in a Project Portfolio through Multi-Criteria Decision-Making

Sustainability-Oriented Financial Resource Allocation in a Project Portfolio through Multi-Criteria Decision-Making

SAIPO-TAIPO and Genetic Algorithms for Investment Portfolios

Performance Evaluation of Genetic Algorithm & Fuzzy Logic for Portfolio Optimization

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