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...

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 optimization involves the optimal assignment of limited capital to different available financial assets to achieve a reasonable trade-off between profit and risk objectives. In this paper, we studied the extended Markowitz’s meanvariance portfolio optimization model. We considered the cardinality, quantity, pre-assignment and round lot constraints in the extended model. These four rea...

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...

Selecting approaches with appropriate accuracy and suitable speed for the purpose of making decision is one of the managers’ challenges. Also investing decision is one of the main decisions of managers and it can be referred to securities transaction in financial markets which is one of the investments approaches. When some assets and barriers of real world have been considered, optimization of...

Financial returns exhibit stylized facts such as leptokurtosis, skewness and heavy-tailness. Regarding this behavior, in this paper, we apply multivariate generalized hyperbolic (mGH) distribution for portfolio modeling and performance evaluation, using conditional value at risk (CVaR) as a risk measure and allocating best weights for portfolio selection. Moreover, a robust portfolio optimizati...

Dr. V. J.Sebastian (Corresponding author) Institute of Management Technology Gaziabad, Delhi, India E-mail: [email protected] Abstract Portfolio optimization, in case of finance, is the tradeoff between risk and return to maximize profit or return from the portfolio. Financial regulations are country specific and it depends upon the economic conditions prevailing in the country. The portfolio of...