Özet:

On the basis of financial criteria, the process of creating a portfolio within the investor by choosing a certain rate between the shareholders is called portfolio optimization. The portfolio return and risk elements were first evaluated together on the basis of the normal assumption of the average variance model. However, most of the historical returns of the stock markets are not normally distributed. The inclusion of high-degree moments, such as disappointment and depression, into the portfolio selection model becomes meaningful when the normality assumption is not provided. If the number of shares that will be included in the portfolio is limited, the problem of portfolio choice becomes quantity-limited portfolio optimization. In the study, the recommended particle volume optimization algorithm was compared with three different particle volume optimization algorithms, in the quantity limited portfolio optimization problem. Portfolios have been obtained according to different target functions, which contain different quantity limit values and high-degree moments. The results show the effectiveness of the recommended algorithm in solving the problem.