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Fuzzy Logic-based Portfolio Selection with Particle Filtering and Anomaly Detection (Subsequently published in "Knowledge-Based Systems")

Author

Listed:
  • Masafumi Nakano

    (Graduate School of Ecnonomics, University of Tokyo)

  • Akihiko Takahashi

    (Faculty of Economics, University of Tokyo)

  • Soichiro Takahashi

    (Graduate School of Ecnonomics, University of Tokyo)

Abstract

This paper proposes a new knowledge-based system (KBS) featuring fuzzy logic (FL) with particle filtering and anomaly detection to create high-performance investment port-folios. In particular, our FL system selects a portfolio with fine risk-return profiles from a number of candidates by integrating multilateral performance measures. The candidates consist of various portfolios based on multiple time-series models estimated by a particle filter with anomaly detectors. In an out-of-sample numerical experiment with a dataset of international financial assets, we demonstrate our KBS successfully generates a series of selected portfolios with satisfactory investment records.

Suggested Citation

  • Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Fuzzy Logic-based Portfolio Selection with Particle Filtering and Anomaly Detection (Subsequently published in "Knowledge-Based Systems")," CARF F-Series CARF-F-405, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Handle: RePEc:cfi:fseres:cf405
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    References listed on IDEAS

    as
    1. Fang, Yong & Lai, K.K. & Wang, Shou-Yang, 2006. "Portfolio rebalancing model with transaction costs based on fuzzy decision theory," European Journal of Operational Research, Elsevier, vol. 175(2), pages 879-893, December.
    2. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    3. Li, Jun & Xu, Jiuping, 2009. "A novel portfolio selection model in a hybrid uncertain environment," Omega, Elsevier, vol. 37(2), pages 439-449, April.
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    Cited by:

    1. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2018. "State Space Approach to Adaptive Artificial Intelligence Modeling: Application to Financial Portfolio with Fuzzy System," CARF F-Series CARF-F-422, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    2. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "State Space Approach to Adaptive Fuzzy Modeling: Application to Financial Investment," CIRJE F-Series CIRJE-F-1067, CIRJE, Faculty of Economics, University of Tokyo.
    3. Souta Nakatani & Kiyohiko G. Nishimura & Taiga Saito & Akihiko Takahashi, 2019. "Online Appendix for Interest Rate Model with Investor Attitude and Text Mining," CARF F-Series CARF-F-470, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    4. Masafumi Nakano & Akihiko Takahashi, 2019. "A New Investment Method with AutoEncoder: Applications to Cryptocurrencies," CIRJE F-Series CIRJE-F-1128, CIRJE, Faculty of Economics, University of Tokyo.
    5. Souta Nakatani & Kiyohiko G. Nishimura & Taiga Saito & Akihiko Takahashi, 2019. "Online Appendix for Interest Rate Model with Investor Attitude and Text Mining," CIRJE F-Series CIRJE-F-1136, CIRJE, Faculty of Economics, University of Tokyo.

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