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A New Interval Type-2 Fuzzy Logic System Under Dynamic Environment: Application to Financial Investment (Subsequently published in "Engineering Applications of Artificial Intelligence")

Author

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  • Akihiko Takahashi

    (Faculty of Economics, University of Tokyo)

  • Soichiro Takahashi

    (GCI Asset Management, Inc.,)

Abstract

This paper proposes a new interval type-2 fuzzy logic system (IT2 FLS) for financial investment with time-varying parameters adaptive to real-time data streams by using an on-line learning method based on a state-space framework. Particularly, our state-space approach regards the parameters of IT2 FLSs as state variables to sequentially learn by Bayesian filtering algorithms under dynamic environments, where time-series data are continuously observed with occasional structural changes. Moreover, our proposal is effective for financial investment, which often involves various practical complex constraints, because general state-space model makes it possible to flexibly deal with non-linearities. In our empirical experiment with time-series data of global financial assets, our approach is applied to on-line parameter learning of type-1 and type-2 FLSs for portfolio decision making. As a result, it is shown that the IT2 FLS holds its advantage against the type-1 FLS, even though both of the type-1 and type-2 models have the adaptive time-varying parameters, which is an unexplored topic for empirical studies of this area.

Suggested Citation

  • Akihiko Takahashi & Soichiro Takahashi, 2021. "A New Interval Type-2 Fuzzy Logic System Under Dynamic Environment: Application to Financial Investment (Subsequently published in "Engineering Applications of Artificial Intelligence")," CARF F-Series CARF-F-503, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Handle: RePEc:cfi:fseres:cf503
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    Cited by:

    1. Daiya Mita & Akihiko Takahashi, 2022. "Multi-Agent Model Based Proactive Risk Management For Equity Investment," CIRJE F-Series CIRJE-F-1207, CIRJE, Faculty of Economics, University of Tokyo.
    2. Zuzana JANKOVÁ & Petr DOSTÁL, 2022. "Evaluation of the Degree of Uncertainty in the Type-2 Fuzzy Logic System for Forecasting Stock Index," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 41-57, December.
    3. Daiya Mita & Akihiko Takahashi, 2024. "A New Equity Investment Strategy with Artificial Intelligence, Multi Factors, and Technical Indicators," CIRJE F-Series CIRJE-F-1230, CIRJE, Faculty of Economics, University of Tokyo.
    4. Daiya Mita & Akihiko Takahashi, 2024. "A New Equity Investment Strategy with Artificial Intelligence, Multi Factors, and Technical Indicators," CARF F-Series CARF-F-588, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

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