Abstract
In this paper, we employ the Conditional Value at Risk (CVaR) to measure the portfolio risk, and propose a mean-CVaR portfolio selection model. In addition, some real-world constraints are considered. The constructed model is a non-linear discrete optimization problem and difficult to solve by the classic optimization techniques. A novel hybrid algorithm based particle swarm optimization (PSO) and artificial bee colony (ABC) is designed for this problem. The hybrid algorithm introduces the ABC operator into PSO. A numerical example is given to illustrate the modeling idea of the paper and the effectiveness of the proposed hybrid algorithm.
Original language | English |
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Pages (from-to) | 319-327 |
Journal | Lecture Notes in Computer Science |
Volume | 8795 |
DOIs | |
Publication status | Published - 23 Sept 2014 |
Keywords
- CVaR
- Conditional Value at Risk
- Hybrid algorithm
- Port- folio selection