Clustered stocks weighting with ant colony optimization in portfolio optimization

Steven, A.; Hertono, Gatot Fatwanto; Handari, Bevina D.

doi:10.1063/1.5064201

Cited by 3 publications

(1 citation statement)

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“…In the article [2], the authors employed the K-Means Clustering Algorithm and Ant Colony Optimization (ACO) to derive portfolio management solutions. In this work, K-Means Clustering is utilized to cluster the stocks based on the financial crisis, whereas the ACO does the weighting of each cluster.…”

Section: Related Studiesmentioning

confidence: 99%

Optimization of Virtual Network Mapping Based on Improved Ant Colony Algorithm in Complex Network Environments

Zhang

Sheng²

2022

Scientific Programming

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Financial marketing is a method of risky investment, but in a shorter duration, the individual can expect a profit or loss, depending on the current market rate for the organization. Though it has a higher risk of getting a profit, many individuals are ready to take a chance to benefit. In the current era, much research is going on to provide a better prediction rate. Most researchers prefer Ant Colony Optimization (ACO) as a more trustworthy optimization algorithm among the existing optimization algorithms. In this research work, a novel optimization algorithm is proposed; it is a hybrid algorithm with Ant Colony Optimization (ACO) and financial marketing crisis prediction (FMCP) and is termed ACO-FMCP. This hybrid algorithm was applied to the economic sanctions dataset, and the results were generated. The results were compared with ACO and FMCP algorithms and it was found that the hybrid ACO-FMCP shows improved performance than the other two algorithms.

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Section: Related Studiesmentioning

confidence: 99%