An Artificial Bee Colony Algorithm for Fuzzy Portfolio Model with Concave Transaction Costs

In the financial market, the expected rates of security returns cannot be well reflected by historical data because of the high volatility of market environment. This paper deals with a fuzzy portfolio selection problem based on possibility theory. Due to ignoring transaction costs would result in inefficient portfolio, a possibilistic portfolio selection model with concave transaction cost is proposed. In addition, Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. To solve this nonlinear programming, the ABC algorithm is utilized. Finally, we illustrate the new model by a numerical example and compare results with Genetic Algorithms (GA), which shows that the ABC algorithm is more effective and powerful than GA.