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On portfolio analysis using oriented fuzzy numbers for the trade-related sector of the Warsaw Stock Exchange

Author

Listed:
  • Anna Łyczkowska-Hanćkowiak
  • Aleksandra Wójcicka-Wójtowicz

Abstract

Oriented fuzzy numbers are useful in portfolio management since they convey information regarding uncertainty and imprecision when considering financial markets. One may apply a fuzzy discount factor and an imprecise present value in the form of a trapezoidal oriented fuzzy number. An investor can obtain recommendations on individual stocks (buy, sell, accumulate, reduce). Analogous recommendations are also issued by experts. In such cases, recommendations are mostly based on available data and expert’s knowledge and experience. The purpose of the paper is to present a procedure for comparing the accuracy of both types of recommendations. Also, the real impact the recommendations have on potential changes in portfolio composition in trading-related industries is considered. The research uses quotations from companies from the trading sector of the Warsaw Stock Exchange (WSE). Theoretical considerations are presented in the form of an empirical case study.

Suggested Citation

  • Anna Łyczkowska-Hanćkowiak & Aleksandra Wójcicka-Wójtowicz, 2023. "On portfolio analysis using oriented fuzzy numbers for the trade-related sector of the Warsaw Stock Exchange," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(4), pages 155-170.
    • Handle: RePEc:wut:journl:v:33:y:2023:i:4:p:155-170:id:9
    DOI: 10.37190/ord230409
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    References listed on IDEAS

    as
    1. Aleksandra Wójcicka-Wójtowicz & Krzysztof Piasecki, 2021. "Application of the Oriented Fuzzy Numbers in Credit Risk Assessment," Mathematics, MDPI, vol. 9(5), pages 1-13, March.
    2. Krzysztof Piasecki & Anna Łyczkowska-Hanćkowiak, 2019. "Representation of Japanese Candlesticks by Oriented Fuzzy Numbers," Econometrics, MDPI, vol. 8(1), pages 1-24, December.
    3. Womack, Kent L, 1996. "Do Brokerage Analysts' Recommendations Have Investment Value?," Journal of Finance, American Finance Association, vol. 51(1), pages 137-167, March.
    4. Krzysztof Piasecki, 2012. "The basis of financial arithmetic from the viewpoint of utility theory," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 22(3), pages 37-53.
    5. Aleksandra Wójcicka-Wójtowicz & Krzysztof Piasecki, 2022. "Modifications of order scales for assessing debtors," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 32(3), pages 142-151.
    6. Green, T. Clifton, 2006. "The Value of Client Access to Analyst Recommendations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(1), pages 1-24, March.
    7. Anna Łyczkowska-Hanćkowiak & Krzysztof Piasecki, 2018. "The present value of a portfolio of assets with present values determined by trapezoidal ordered fuzzy numbers," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 28(2), pages 41-56.
    8. repec:wut:journl:v:3:y:2012:id:1044 is not listed on IDEAS
    9. Krzysztof Piasecki & Anna Łyczkowska-Hanćkowiak, 2021. "Oriented Fuzzy Numbers vs. Fuzzy Numbers," Mathematics, MDPI, vol. 9(5), pages 1-27, March.
    10. Gutiérrez, Isabel, 1989. "Fuzzy numbers and net present value," Scandinavian Journal of Management, Elsevier, vol. 5(2), pages 149-159.
    11. Cédric Lesage, 2001. "Discounted cash-flows analysis: An interactive fuzzy arithmetic approach," Post-Print hal-00485731, HAL.
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