This paper examines the problem of choosing the optimal portfolio for an investor with asymmetric attitude to gains and losses described in the prospect theory of A. Tversky and D. Kahneman. We consider the portfolio optimization problem for an investor who follows the assumptions of the prospect theory and the cumulative prospect theory under conditions on the stochastic behavior both of the p...

The purpose of this paper is to propose a practical branch and bound algorithm for solving a class of long-short portfolio optimization problem with concave and d.c. transaction cost and complementarity conditions on the variables. We will show that this algorithm can solve a problem of practical size and that the longshort strategy leads to a portfolio with significantly better risk-return str...

One of the popular methods for optimizing combinational problems such as portfolio selection problem is swarmbased methods. In this paper, we have proposed an approach based on Quantum-Behaved Particle Swarm Optimization (QPSO) for the portfolio selection problem. The particle swarm optimization (PSO) is a well-known population-based swarm intelligence algorithm. QPSO is also proposed by combin...

We introduce a new methodology that incorporates advanced higher moments evaluation in a new approach of the Portfolio Selection problem, supported by effective Computational Intelligence models. The Evolutional Portfolio Optimization System (EPOS) extracts hidden patterns out of the numerous accounting data and financial statements filtering misguiding effects such as noise or fraud, offering ...

In this paper we present a framework, i.e. a concept and design as well as results with a prototypical implementation of a metaheuristic-based decision support system PM-DSS c © for portfolio optimization and managing investment guidelines. PM-DSS c © can be used for active as well as passive fund management. 1 The general problem In this paper we present a framework, i.e. a concept and design ...

Optimization refers to the minimization (or maximization) of an objective function of several decision variables that have to satisfy specified constraints. There are many applications of optimization. One example is the portfolio optimization problem where we seek the best way to invest some capital in a set of n assets. The constraints might represent a limit on the budget (i.e., a limit on t...

In this work, the ability of the Dynamic Objectives Aggregation Methods to solve the portfolio rebalancing problem is investigated conducting a computational study on a set of instances based on real data. The portfolio model considers a set of realistic constraints and entails the simultaneously optimization of the risk on portfolio, the expected return and the transaction cost.

Nonlinear constrained programing problem (NCPP) has been arisen in diverse range of sciences such as portfolio, economic management etc.. In this paper, a multiobjective imperialist competitive evolutionary algorithm for solving NCPP is proposed. Firstly, we transform the NCPP into a biobjective optimization problem. Secondly, in order to improve the diversity of evolution country swarm, and he...

Given a polynomial optimization problem (POP), any affine transformation on its variable vector induces an equivalent POP. Applying Lasserre's SDP relaxation to the original and the transformed POPs, we have two SDPs. This paper shows that these two SDPs are isomorphic to each other under a nonsingular linear transformation, which maps the feasible region of one SDP onto that of the other isomo...

Robust optimization, one of the most popular topics in the field of optimization and control since the late 1990s, deals with an optimization problem involving uncertain parameters. In this paper, we consider the relative robust conditional value-at-risk portfolio selection problem where the underlying probability distribution of portfolio return is only known to belong to a certain set. Our ap...