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Multi-Agent Model Based Proactive Risk Management For Equity Investment

Author

Listed:
  • Daiya Mita

    (Nomura Asset Management Co., Ltd.)

  • Akihiko Takahashi

    (Faculty of Economics, The University of Tokyo)

Abstract

Developing and applying new artificial intelligence (AI) techniques in finance has become popular and one of the growing areas. Although many studies focus on return prediction and do not pay much attention to price formation, revealing its mechanism is essential in risk management, particularly in proactive risk management for investment to improve the performance. Thus, this paper introduces a novel multi-agent model, which is able to explain how agents’ portfolio rebalances determine the market price dynamics to clarify the price formation by applying a state space model. The technical novelty is the effective integration of state space modeling and fuzzy logic into a multi-agent model with four types of typical investors and their fuzzy trading strategies. By using the estimated unobservable fund flows of each trader in the model, this work proposes a new proactive warning signal. As a result, the signal improves both the risk and return of the investment in the Japanese and United States equity markets. Our findings indicate that the agents’ estimated fund flows driving asset prices help us to avoid a market crash, reduce the risk and improve the return in investment practice.

Suggested Citation

  • 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.
    • Handle: RePEc:tky:fseres:2022cf1207
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    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2022/2022cf1207.pdf
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    References listed on IDEAS

    as
    1. Masafumi Nakano & Akihiko Takahashi & Muhammad Soichiro Takahashi, 2017. "Creating Investment Scheme with State Space Modeling," CIRJE F-Series CIRJE-F-1038, CIRJE, Faculty of Economics, University of Tokyo.
    2. Akihiko Takahashi & Soichiro Takahashi, 2022. "A State Space Modeling for Proactive Management in Equity Investment," CIRJE F-Series CIRJE-F-1197, CIRJE, Faculty of Economics, University of Tokyo.
    3. Souta Nakatani & Kiyohiko G. Nishimura & Taiga Saito & Akihiko Takahashi, 2020. "Interest Rate Model with Investor Attitude and Text Mining," CIRJE F-Series CIRJE-F-1152, CIRJE, Faculty of Economics, University of Tokyo.
    4. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Fuzzy Logic-based Portfolio Selection with Particle Filtering and Anomaly Detection," CIRJE F-Series CIRJE-F-1037, CIRJE, Faculty of Economics, University of Tokyo.
    5. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Fuzzy Logic-based Portfolio Selection with Particle Filtering and Anomaly Detection," CIRJE F-Series CIRJE-F-1037, CIRJE, Faculty of Economics, University of Tokyo.
    6. Daniel Poh & Bryan Lim & Stefan Zohren & Stephen Roberts, 2021. "Enhancing Cross-Sectional Currency Strategies by Context-Aware Learning to Rank with Self-Attention," Papers 2105.10019, arXiv.org, revised Jan 2022.
    7. Akihiko Takahashi & Soichiro Takahashi, 2022. "A state space modeling for proactive management in equity investment "Forthcoming in International Journal of Financial Engineering"," CARF F-Series CARF-F-543, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    8. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Creating Investment Scheme with State Space Modeling," CARF F-Series cf406, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    9. Akihiko Takahashi & Soichiro Takahashi, 2022. "A state space modeling for proactive management in equity investment," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(04), pages 1-29, December.
    10. Masafumi Nakano & Akihiko Takahashi, 2020. "A new investment method with AutoEncoder: Applications to crypto currencies(Forthcoming in "Expert Systems with Applications")," CARF F-Series CARF-F-489, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    11. Souta Nakatani & Kiyohiko G. Nishimura & Taiga Saito & Akihiko Takahashi, 2020. "Interest Rate Model with Investor Attitude and Text Mining (Published in IEEE Access)," CARF F-Series CARF-F-479, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
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