Journal of the Korean Society of Industry Convergence (한국산업융합학회 논문집)

The Korean Society of Industry Convergence (한국산업융합학회)
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A Study on Portfolios Using Simulated Annealing and Tabu Search Algorithms

시뮬레이티드 어닐링와 타부 검색 알고리즘을 활용한 포트폴리오 연구

  • Woo Sik Lee (College of Business Administration, Gyeongsang National University)
  • 이우식 (경상국립대학교 경영대학)
  • Received : 2024.03.28
  • Accepted : 2024.04.09
  • Published : 2024.04.30
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Abstract

Metaheuristics' impact is profound across many fields, yet domestic financial portfolio optimization research falls short, particularly in asset allocation. This study delves into metaheuristics for portfolio optimization, examining theoretical and practical benefits. Findings indicate portfolios optimized via metaheuristics outperform the Dow Jones Index in Sharpe ratios, underscoring their potential to enhance risk-adjusted returns significantly. Tabu search, in comparison to Simulated Annealing, demonstrates superior performance by efficiently navigating the search space. Despite these advancements, practical application remains challenging due to the complexities in metaheuristic implementation. The study advocates for broader algorithmic exploration, including population-based metaheuristics, to refine asset allocation strategies further. This research marks a step towards optimizing portfolios from an extensive array of financial assets, aiming for maximum efficacy in investment outcomes.

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References

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