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August 10, 2025SinkrOnOpen Access

Hybrid Genetic Algorithm for Dynamic Portfolio Optimization Problems

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Authors

SNSarah Ayatun NufusUniversitas Sumatera UtaraSSSutarman SutarmanUniversitas Sumatera UtaraEHElvina HerawatiUniversitas Sumatera Utara

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Implication

Hybrid genetic algorithm improves sharpe ratio in dynamic portfolio optimization, suggesting robustness against market changes.

Key Points

  • Hybrid genetic algorithms significantly improve solution quality in dynamic portfolio optimization problems compared to standard methods.
  • Key metrics indicate that the hybrid approach offers better overall best fitness and offline performance solution quality.
  • The method integrates a hill climbing technique, enhancing adaptation in volatile market conditions but may increase computation time.
  • Robustness to dynamic changes was observed with the hybrid algorithm, supporting the hypothesis that combined techniques yield better results.

Cite This Study

Nufus et al. (2025) studied this question.

synapsesocial.com/papers/68af453aad7bf08b1ead286ahttps://doi.org/10.33395/sinkron.v9i3.14868
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Also Consider

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