In this paper, the portfolio model with the constraints of a number of assets and the proportion of investment is established on the basis of the Markowitz mean-variance model. For solving the model and the simulated actual investment, a quantum particle swarm hybrid algorithm is constructed by differential evolution and chaotic search. Numerical experiments show that the proposed algorithm is effective, and that the proposed hybrid algorithm performs better than other improved particle swarm optimization algorithm, differential evolution algorithm, genetic algorithm, simulated annealing algorithm and tabu search algorithm. Besides, the empirical results show that the proposed algorithm is a good solution to the portfolio model, and the simulation results show that the proposed model is effective.