Published 04-12-2022
Keywords
- Evolutionary Computation,
- Genetic Algorithms,
- Particle Swarm Optimization,
- Portfolio Management,
- Financial Optimization
- Optimization Techniques ...More
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Abstract
Evolutionary computation techniques, such as genetic algorithms and particle swarm optimization, have gained significant attention in recent years for their applications in solving complex optimization problems. In the field of finance, these techniques have been applied to portfolio management and asset allocation, offering promising results. This paper provides a comprehensive analysis of the use of evolutionary computation in finance, specifically focusing on portfolio management. We discuss the theoretical foundations of genetic algorithms and particle swarm optimization, and then explore their applications in portfolio optimization. We also compare these techniques with traditional optimization methods and highlight the advantages and limitations of evolutionary computation in the context of finance. Additionally, we discuss the challenges and future research directions in this area. Keywords: Evolutionary Computation, Genetic Algorithms, Particle Swarm Optimization, Portfolio Management, Asset Allocation, Finance, Optimization.
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