جستجوی مقالات مرتبط با کلیدواژه « الگوریتم ممتیک » در نشریات گروه « مالی »

In this paper, Symbiotic organism search and memetic algorithms are used to solve constrained mean-semi variance portfolio problem. Then AR model, Neural network and ANFIS are compared to predict expected return of stocks. 23 active stocks from June 22, 2014 to Jan 21, 2016 are used as our sample. The results indicate that, memetic algorithm despite its longer time consuming has better performance than SOS algorithm. And ANFIS has more accurate prediction than others in predicting expected rate of return. Finally, we compare expected and real efficient frontier, the results indicate that, in lower risk, ANFIS has better prediction accuracy. So in that area, we can allocate our asset with higher certainty.

The purpose of this article is creating the suitable model for investment. First, according to the literature review, we extract the effective criteria for portfolio selection. Then we use expert's opinions about the importance of each criterion to find criteria pair wise comparisons. In this stage, because of interrelationship among the criteria, ANP is used as the most appropriate technique for this analysis. At the next step, we use TOPSIS technique for ranking the population members, including companies of seven industries (cement, main mineral, petrochemicals, medicines, real estate, automobile). Real data average of three years – from 2007 to 2009 – is used as input for TOPSIS technique. After determining the companies ranking, the selected portfolio includes 40 top companies. In order to confirm the selected portfolio, the three years return of the selected companies is compared with non selected companies. After benchmarking portfolio based on Sharp and Treynor criteria, we use Memetic algorithm to optimize the selected portfolio.