Fireworks algorithm applied to constrained portfolio optimization problem

This paper presents implementation of the fireworks algorithm for portfolio optimization problem with constraints. Fireworks algorithm is a relatively new nature-inspired meta-heuristic which emulates the process of fireworks' explosion. We adapted fireworks algorithm for solving constrained portfolio selection problem that extends classical mean-variance portfolio model by adding additional constraints. Comparative analysis was conducted with three other swarm intelligence algorithms and three variants of genetic algorithm from the literature, using the same problem formulation and the same test data. Results show that the fireworks algorithm has great potential for tackling portfolio optimization problem since it performed better than mentioned algorithms considering all performance indicators.