Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5102726 | Physica A: Statistical Mechanics and its Applications | 2017 | 15 Pages |
Abstract
Intelligent algorithms have been widely applied to portfolio optimization problems. In this paper, we introduce a novel intelligent algorithm, named fireworks algorithm, to solve the mean-VaR/CVaR model for the first time. The results show that, compared with the classical genetic algorithm, fireworks algorithm not only improves the optimization accuracy and the optimization speed, but also makes the optimal solution more stable. We repeat our experiments at different confidence levels and different degrees of risk aversion, and the results are robust. It suggests that fireworks algorithm has more advantages than genetic algorithm in solving the portfolio optimization problem, and it is feasible and promising to apply it into this field.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Tingting Zhang, Zhifeng Liu,