Markowitz theorem is one of the most popular techniques for asset management. The method has been widely used to solve many applications, successfully. In this paper, we present a multi objective Markowitz model to determine asset allocation by considering cardinality constraints. The resulted model is an NP-Hard problem and the proposed study uses two metaheuristics, namely genetic algorithm (GA) and particle swarm optimization (PSO) to find efficient solutions. The proposed study has been applied on some data collected from Tehran Stock Exchange over the period 2009-2011. The study considers four objectives including cash return, 12-month return, 36-month return and Lower Partial Moment (LPM). The results indicate that there was no statistical difference between the implementation of PSO and GA methods.

It has been a long time that researchers are trying to find out on why some people have better mental health than others do and some are more successful than the others are. There are many evidences to believe that having general intelligence does not necessarily yield prosperity and success and it could be accounted up to 20% of the success, whereas the remaining 80% is associated with other issues. The present study attempts to perform a comparative study on emotional intelligence and cognitive among successful and unsuccessful entrepreneurs. We adopt a standard test, which includes 133 questions and distribute it between two groups of successful and unsuccessful entrepreneurs in province of Sistan and Balochestan located in south west of Iran. The results of our ANOVA test when the level of significance is five percent reveal that emotional intelligence can substantially impact on the success of entrepreneurs.