The problem of optimal portfolio selection has attracted a great attention in the finance and optimization field. The future stock price should be predicted in an acceptable precision, and a suitable model and criterion for risk and the expected return of the stock portfolio should be proposed in order to solve the optimization problem. In this paper, two new criterions for the risk of stock pr...

Portfolio optimization requires the minimal risk with certain expected return. The risk structure of securities, such as their exposure to countries, industrial sectors, or commodity/factor, have to be characterized, and then the optimal weights of securities in a portfolio can be determined to minimize the exposure of the portfolio to any specific risk factor. Typically, the risk factors are n...

this paper proposes a family of robust counterpart for uncertain linear programs (lp) which is obtained for a general definition of the uncertainty region. the relationship between uncertainty sets using norm bod-ies and their corresponding robust counterparts defined by dual norms is presented. those properties lead us to characterize primal and dual robust counterparts. the researchers show t...

Swarm Intelligence (SI) is a relatively new technology that takes its inspiration from the behavior of social insects and flocking animals. In this paper, we focus on two main SI algorithms: Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). An extension of ACO algorithm and a PSO algorithm has been implemented to solve the portfolio optimization problem, which is a continuous...

in this paper, according to high load capacity and rather large workspace characteristics of cable driven robots (cdrs), maximum dynamic load carrying capacity (dlcc) between two given end points in the workspace along with optimal trajectory is obtained. in order to find dlcc of cdrs, joint actuator torque and workspace of the robot constraints concerning to non-negative tension in cables are ...

this paper discusses the portfolio selection based on robust optimization. since the parameters values of the portfolio optimization problem such as price of the stock, dividends, returns, etc. of per share are unknown, variable and their distributions are uncertain because of the market and price volatility, therefore, there is a need for the development and application of methodologies for de...

Portfolio selection process is a subject focused by many researchers. Various criteria involved in this process have undergone alterations over time, necessitating the use of appropriate investment decision support tools. An optimization approach used in different sciences is using meta-heuristic algorithms. In the present study, using Water Cycle Algorithm (WCA), a model was introduced for sel...

To find out an effective way to solve the real estate portfolio optimization, an improved Ant Colony Algorithm based on information entropy was proposed. The information entropy was used to control the path selection and evolutional strategy by self-adjusting to overcome the premature convergence problem of the basic Ant Colony Algorithm. Simulation study on Traveling Salesman Problem and the a...

Here, a quasi-Newton algorithm for constrained multiobjective optimization is proposed. Under suitable assumptions, global convergence of the algorithm is established.

short-selling prohibition has been one of the primary assumptions of markowitz mean-variance model. solving markowitz quadratic model creates investment efficient frontier by considering only two return and budget constraints. in order to develop a more realistic portfolio selection model, in this paper, a new mathematical model is developed to allow short-selling under some practical constrain...