Abstract
Portfolio selection is one of the most important areas in financial decision-making; A portfolio of stocks that could bring the highest rate of return and the lowest risk investment for its owner simultaneously. However in choosing the most prefered portfolio More
Abstract
Portfolio selection is one of the most important areas in financial decision-making; A portfolio of stocks that could bring the highest rate of return and the lowest risk investment for its owner simultaneously. However in choosing the most prefered portfolio just these factors are not decisive and according to the economic environment, many factors can affect this process which should be employed. Therefore, these diversity of factors, bring to the limelight the importance of multi-criteria decision-making approaches. Data Envelopment Analysis (DEA) is one of this approaches.
The main purpose of this paper is comparing the traditional DEA approaches to a new proposed algorithm. In traditional approaches simply assumed that return to scale is constant or variable. This simplification may cause large errors. In the new algorithm by analyzing the behavior of return to scale, appropriate model will be used.
As a case study, the models have been solved with real data belonging to Tehran stock exchange and the results have been analyzed.
Manuscript profile
Portfolio is a collection or combination of investments in financial and non-financial assets that may be carried out by an individual or organization. How to select and optimize of portfolio is very important. One of the most important points that should be considered More
Portfolio is a collection or combination of investments in financial and non-financial assets that may be carried out by an individual or organization. How to select and optimize of portfolio is very important. One of the most important points that should be considered in the proposed approach for portfolio selection, is uncertainty. Because, one of the most important features of financial markets is their uncertainty. Thus, the purpose of this study is to present a bi-objective model for portfolio selection that is capable to be used under uncertainty of financial data and for this purpose, a robust optimization approach has been used. It should be noted that return and conditional value at risk (CVaR) are considered as model objectives, and the constraints of the number of shares and the purchasing volume of each share have been added to the model. Also, due to the complexity of the proposed model, a NSGA-II meta-heuristic algorithm has been used to solve the suggested model of research. Finally, the presented model was solved by using the actual data of 200 stocks of Tehran stock market for the period of 2017 and the results were analyzed. The results indicate the efficiency of the proposed approach portfolio selection according to the investor's preferences and constraints under uncertainty of financial data.
Manuscript profile
