Biogeography-Based Optimization of the Portfolio Optimization Problem with Second Order Stochastic Dominance Constraints
School of economic and management, Hainan University, No. 58 Renmin Avenue, Haikou 570228, China
College of Information Science & Technology, Hainan University, No. 58 Renmin Avenue, Haikou 570228, China
Author to whom correspondence should be addressed.
Received: 7 August 2017 / Revised: 21 August 2017 / Accepted: 23 August 2017 / Published: 25 August 2017
The portfolio optimization problem is the central problem of modern economics and decision theory; there is the Mean-Variance Model and Stochastic Dominance Model for solving this problem. In this paper, based on the second order stochastic dominance constraints, we propose the improved biogeography-based optimization algorithm to optimize the portfolio, which we called
BBO. In order to test the computing power of
BBO, we carry out two numerical experiments in several kinds of constraints. In experiment 1, comparing the Stochastic Approximation (SA) method with the Level Function (LF) algorithm and Genetic Algorithm (GA), we get a similar optimal solution by
constraints with the return of 1.174% and 1.178%. In
constraint, we get the optimal return of 1.3043% by
BBO, while the return of SA and LF is 1.23% and 1.26%. In experiment 2, we get the optimal return of 0.1325% and 0.3197% by
constraints. As a comparison, the return of FTSE100 Index portfolio is 0.0937%. The results prove that
BBO algorithm has great potential in the field of financial decision-making, it also shows that
BBO algorithm has a better performance in optimization problem.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
Scifeed alert for new publications
Never miss any articles
matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
Define your Scifeed now
Share & Cite This Article
MDPI and ACS Style
Ye, T.; Yang, Z.; Feng, S. Biogeography-Based Optimization of the Portfolio Optimization Problem with Second Order Stochastic Dominance Constraints. Algorithms 2017, 10, 100.
Ye T, Yang Z, Feng S. Biogeography-Based Optimization of the Portfolio Optimization Problem with Second Order Stochastic Dominance Constraints. Algorithms. 2017; 10(3):100.
Ye, Tao; Yang, Ziqiang; Feng, Siling. 2017. "Biogeography-Based Optimization of the Portfolio Optimization Problem with Second Order Stochastic Dominance Constraints." Algorithms 10, no. 3: 100.
Show more citation formats
Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
[Return to top]
For more information on the journal statistics, click here
Multiple requests from the same IP address are counted as one view.