IDEAS home Printed from https://ideas.repec.org/p/tky/fseres/2016cf1037.html
   My bibliography  Save this paper

Fuzzy Logic-based Portfolio Selection with Particle Filtering and Anomaly Detection

Author

Listed:
  • Masafumi Nakano

    (Graduate School of Economics, The University of Tokyo)

  • Akihiko Takahashi

    (Faculty of Economics, The University of Tokyo)

  • Soichiro Takahashi

    (Graduate School of Economics, The University of Tokyo)

Abstract

This paper proposes a new fuzzy logic (FL)-based expert system with particle filtering and anomaly detection to create high-performance investment portfolios. In particular, our FL system selects a portfolio with fine risk-return profiles from a number of candidates by integrating multilateral performance measures including Sharpe, Sortino and Sterling ratios. The candidates consist of various mean-variance portfolios with multiple time-series models estimated by a particle filter and anomaly detectors. In an out-of-sample numerical experiment with a dataset of international financial assets, we demonstrates our expert system successfully generates a series of mean-variance 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," CIRJE F-Series CIRJE-F-1037, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2016cf1037
    as

    Download full text from publisher

    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2017/2017cf1037.pdf
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Masaaki Fujii & Akihiko Takahashi & Masayuki Takahashi, 2017. "Asymptotic Expansion as Prior Knowledge in Deep Learning Method for high dimensional BSDEs," Papers 1710.07030, arXiv.org, revised Mar 2019.
    2. 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.
    3. Marc Sanchez-Roger & María Dolores Oliver-Alfonso & Carlos Sanchís-Pedregosa, 2019. "Fuzzy Logic and Its Uses in Finance: A Systematic Review Exploring Its Potential to Deal with Banking Crises," Mathematics, MDPI, vol. 7(11), pages 1-22, November.
    4. C. Veeramani & R. Venugopal & S. Muruganandan, 2023. "An Exploration of the Fuzzy Inference System for the Daily Trading Decision and Its Performance Analysis Based on Fuzzy MCDM Methods," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1313-1340, October.
    5. 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.
    6. 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.
    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. Masaaki Fujii & Akihiko Takahashi & Masayuki Takahashi, 2019. "Asymptotic Expansion as Prior Knowledge in Deep Learning Method for high dimensional BSDEs (Forthcoming in Asia-Pacific Financial Markets)," CARF F-Series CARF-F-456, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi & Takami Tokioka, 2018. "On the Effect of Bank of Japan’s Outright Purchase on the JGB Yield Curve," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(1), pages 47-70, March.
    16. Masaaki Fujii & Akihiko Takahashi & Masayuki Takahashi, 2019. "Asymptotic Expansion as Prior Knowledge in Deep Learning Method for High dimensional BSDEs," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(3), pages 391-408, September.
    17. Masaaki Fujii & Akihiko Takahashi & Masayuki Takahashi, 2017. "Asymptotic Expansion as Prior Knowledge in Deep Learning Method for high dimensional BSDEs," CIRJE F-Series CIRJE-F-1069, CIRJE, Faculty of Economics, University of Tokyo.
    18. Masaaki Fujii & Akihiko Takahashi & Masayuki Takahashi, 2017. "Asymptotic Expansion as Prior Knowledge in Deep Learning Method for high dimensional BSDEs," CARF F-Series CARF-F-423, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Robust Technical Trading with Fuzzy Knowledge-based Systems," CIRJE F-Series CIRJE-F-1053, CIRJE, Faculty of Economics, University of Tokyo.
    2. 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.
    3. 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.
    4. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Robust technical trading with fuzzy knowledge-based systems (Forthcoming in "Frontiers in Artificial Intelligence and Applications".)," CARF F-Series CARF-F-413, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Gupta, Pankaj & Mittal, Garima & Mehlawat, Mukesh Kumar, 2013. "Expected value multiobjective portfolio rebalancing model with fuzzy parameters," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 190-203.
    6. Li, Bo & Zhang, Ranran, 2021. "A new mean-variance-entropy model for uncertain portfolio optimization with liquidity and diversification," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    7. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
    8. Zhang, Wei-Guo & Liu, Yong-Jun & Xu, Wei-Jun, 2012. "A possibilistic mean-semivariance-entropy model for multi-period portfolio selection with transaction costs," European Journal of Operational Research, Elsevier, vol. 222(2), pages 341-349.
    9. Fang, Yong & Chen, Lihua & Fukushima, Masao, 2008. "A mixed R&D projects and securities portfolio selection model," European Journal of Operational Research, Elsevier, vol. 185(2), pages 700-715, March.
    10. Zhang, Wei-Guo & Zhang, Xili & Chen, Yunxia, 2011. "Portfolio adjusting optimization with added assets and transaction costs based on credibility measures," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 353-360.
    11. Zeng, Ziqiang & Nasri, Ehsan & Chini, Abdol & Ries, Robert & Xu, Jiuping, 2015. "A multiple objective decision making model for energy generation portfolio under fuzzy uncertainty: Case study of large scale investor-owned utilities in Florida," Renewable Energy, Elsevier, vol. 75(C), pages 224-242.
    12. Tsaur, Ruey-Chyn, 2013. "Fuzzy portfolio model with different investor risk attitudes," European Journal of Operational Research, Elsevier, vol. 227(2), pages 385-390.
    13. Sehgal, Ruchika & Sharma, Amita & Mansini, Renata, 2023. "Worst-case analysis of Omega-VaR ratio optimization model," Omega, Elsevier, vol. 114(C).
    14. Hasuike, Takashi & Ishii, Hiroaki, 2009. "On flexible product-mix decision problems under randomness and fuzziness," Omega, Elsevier, vol. 37(4), pages 770-787, August.
    15. Zhao, Daping & Bai, Lin & Fang, Yong & Wang, Shouyang, 2022. "Multi‐period portfolio selection with investor views based on scenario tree," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    16. P. Kumar & Jyotirmayee Behera & A. K. Bhurjee, 2022. "Solving mean-VaR portfolio selection model with interval-typed random parameter using interval analysis," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 41-77, March.
    17. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Creating Investment Scheme with State Space Modeling ," CIRJE F-Series CIRJE-F-1038, CIRJE, Faculty of Economics, University of Tokyo.
    18. Gruszka, Jarosław & Szwabiński, Janusz, 2020. "Best portfolio management strategies for synthetic and real assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    19. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2013. "Portfolio rebalancing with an investment horizon and transaction costs," Omega, Elsevier, vol. 41(2), pages 406-420.
    20. Yu, Jing-Rung & Lee, Wen-Yi, 2011. "Portfolio rebalancing model using multiple criteria," European Journal of Operational Research, Elsevier, vol. 209(2), pages 166-175, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tky:fseres:2016cf1037. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CIRJE administrative office (email available below). General contact details of provider: https://edirc.repec.org/data/ritokjp.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.