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Self-Management Portfolio System with Adaptive Association Mining: A Practical Application on Taiwan Stock Market

Author

Listed:
  • Jia-Hao Syu

    (Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan)

  • Yi-Ren Yeh

    (Department of Mathematics, National Kaohsiung Normal University, Kaohsiung 82444, Taiwan)

  • Mu-En Wu

    (Department of Information and Finance Management, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Jan-Ming Ho

    (Institute of Information Science, Academia Sinica, Taipei 11529, Taiwan)

Abstract

A well-established financial trading system should well perform in resource allocation, risk management, and sustainability. In this paper, we propose a self-management portfolio system with adaptive association mining for practical applications. The system allocates funds into independent units for risk management, and utilizes association mining and adaptive closing mechanism for resource allocation and sustainability, and adopts a self-management module for monitoring positions. The proposed system boosts the annual return and Sharpe ratio to 9.1% and 0.578 (increased to 2.28 and 2.48 times), and reduces the drawdown risk to 34.6% (decreased to almost half). Furthermore, the system rapidly closes the stock positions to avoid drawdown risk in the bear markets, and gradually increases the stock positions when the market turns into bull. Compared with benchmarks, proposed system outperforms all benchmarks in all measurements and on randomly sampled dataset.

Suggested Citation

  • Jia-Hao Syu & Yi-Ren Yeh & Mu-En Wu & Jan-Ming Ho, 2021. "Self-Management Portfolio System with Adaptive Association Mining: A Practical Application on Taiwan Stock Market," Mathematics, MDPI, vol. 9(10), pages 1-15, May.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:10:p:1093-:d:553336
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    References listed on IDEAS

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