The portfolio optimization problem is the central problem of modern economics and decision theory; there is the Mean-Variance Model and Stochastic Dominance Model for solving this problem. In this paper, based on the second order stochastic dominance constraints, we propose the improved biogeography-based optimization algorithm to optimize the portfolio, which we called εBBO. In order to test t...

Absolute deviation is utilized as a measure of risk and a new function is provided for it. We consider the mean-absolute deviation (MAD) portfolio optimization problem in a frictional market with additional constraints representing the socalled short sales. An algorithm for solving the optimization problem is thus presented, which uses the special structure of the original problem to reduce to ...

Human resource is a key factor for IT new product development. Considering multi-skilled employees in IT Project Portfolio Scheduling, a mixed integer nonlinear programming model with three optimization objectives is proposed from the view of project or product managers. The three objectives are to maximize the increments of skill efficiency values for all multi-skilled employees, to minimize R...

In conventional mean-variance model of portfolio optimization problem the expected return is taken as the mean of the past returns. This assumption is not correct and hence the method leads to poor portfolio optimization performance. Hence an alternative but efficient method is proposed in which the mean and variance of expected return are first predicted with a low complexity functional link a...

Portfolio managers are typically constrained by turnover limits, minimum and maximum stock positions, cardinality, a target market capitalization and sometimes the need to hew to a style (such as growth or value). In addition, portfolio managers often use multifactor stock models to choose stocks based upon their respective fundamental data. We use multiobjective evolutionary algorithms (MOEAs)...

In this research, we proposed a new metaheuristic technique for stock portfolio multi-objective optimization employing the combination of Strength Pareto Evolutionary Algorithm (SPEA), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Arbitrage Pricing Theory (APT). To generate the more precise model, ANFIS has implemented to envisage long-term movement values of the Tehran Stock Exchange (TSE)...

Optimization of the product portfolio has been recognized as a critical problem in industry, management, economy and so on. It aims at the selection of an optimal mix of the products to offer in the target market. As a probability function, reliability is an essential objective of the problem which linear models often fail to evaluate it. Here, we develop a multiobjective integer nonlinear cons...

With the aim of portfolio optimization and management, this article utilizes the Clayton-copula along with copula theory measures. Portfolio-Optimization is one of the activities in investment funds. Thus, it is essential to select an appropriate optimization method. In modern financial analyses, there is growing evidence indicating the distribution of proceeds of financial properties is not cu...

Using advanced techniques of econometrics and a metaheuristic optimization approach, this study attempts to evaluate the potential advantages of international portfolio diversification for East Asian international investors when investing in the Middle Eastern emerging markets. Overall, the results of both econometric and the metaheuristic optimization methods are supporting each other. Finding...