IDEAS home Printed from https://ideas.repec.org/a/wut/journl/v33y2023i4p155-170id9.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://ord.pwr.edu.pl/assets/papers_archive/ord2023vol33no4_9.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.37190/ord230409?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. 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.
    6. 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.
    7. Gutiérrez, Isabel, 1989. "Fuzzy numbers and net present value," Scandinavian Journal of Management, Elsevier, vol. 5(2), pages 149-159.
    8. 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.
    9. repec:wut:journl:v:3:y:2012:id:1044 is not listed on IDEAS
    10. Krzysztof Piasecki & Anna Łyczkowska-Hanćkowiak, 2021. "Oriented Fuzzy Numbers vs. Fuzzy Numbers," Mathematics, MDPI, vol. 9(5), pages 1-27, March.
    11. Cédric Lesage, 2001. "Discounted cash-flows analysis: An interactive fuzzy arithmetic approach," Post-Print hal-00485731, HAL.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Krzysztof Piasecki & Joanna Siwek, 2018. "The portfolio problem with present value modelled by a discrete trapezoidal fuzzy number," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 28(1), pages 57-74.
    3. Piasecki Krzysztof, 2014. "Intuitionistic Assessment Of Behavioural Present Value," Folia Oeconomica Stetinensia, Sciendo, vol. 13(2), pages 49-62.
    4. Anna Łyczkowska-Hanćkowiak, 2019. "Sharpe’s Ratio for Oriented Fuzzy Discount Factor," Mathematics, MDPI, vol. 7(3), pages 1-16, March.
    5. Peng W. He & Andrew Grant & Joel Fabre, 2013. "Economic value of analyst recommendations in Australia: an application of the Black–Litterman asset allocation model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(2), pages 441-470, June.
    6. Medovikov, Ivan, 2014. "Can analysts predict rallies better than crashes?," Finance Research Letters, Elsevier, vol. 11(4), pages 319-325.
    7. Hoechle, Daniel & Schaub, nic & Schmid, Markus, 2012. "Time Stamp Errors and the Stock Price Reaction to Analyst Recommendation and Forecast Revisions," Working Papers on Finance 1215, University of St. Gallen, School of Finance, revised Sep 2015.
    8. Martinez, Jose Vicente, 2011. "Information misweighting and the cross-section of stock recommendations," Journal of Financial Markets, Elsevier, vol. 14(4), pages 515-539, November.
    9. Kliger, Doron & Kudryavtsev, Andrey, 2013. "Volatility expectations and the reaction to analyst recommendations," Journal of Economic Psychology, Elsevier, vol. 37(C), pages 1-6.
    10. R. Bellando & Z. Ben Braham & S. Galanti, 2016. "The profitability of financial analysts’ recommendations: evidence from an emerging market," Applied Economics, Taylor & Francis Journals, vol. 48(46), pages 4410-4418, October.
    11. Thabang Mokoaleli-Mokoteli & Richard J. Taffler & Vineet Agarwal, 2009. "Behavioural Bias and Conflicts of Interest in Analyst Stock Recommendations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(3-4), pages 384-418.
    12. Adam Zaremba & Przemys³aw Konieczka, 2015. "The Profitability Of Following Analyst Recommendations On The Polish Stock Market," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 11(1), pages 22-31, August.
    13. Piasecki, Krzysztof, 2011. "Effectiveness of securities with fuzzy probabilistic return," MPRA Paper 46214, University Library of Munich, Germany.
    14. Brad M. Barber & Reuven Lehavy & Brett Trueman, 2010. "Ratings Changes, Ratings Levels, and the Predictive Value of Analysts’ Recommendations," Financial Management, Financial Management Association International, vol. 39(2), pages 533-553, June.
    15. Andrey Kudryavtsev, 2018. "Holiday effect on stock price reactions to analyst recommendation revisions," Journal of Asset Management, Palgrave Macmillan, vol. 19(7), pages 507-521, December.
    16. Claudia Guagliano & Nadia Linciano & Concetta Magistro Contento, 2013. "The Impact of Financial Analyst Reports on Small Caps Prices in Italy," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 42(3), pages 217-246, November.
    17. Ramnath, Sundaresh & Rock, Steve & Shane, Philip, 2008. "The financial analyst forecasting literature: A taxonomy with suggestions for further research," International Journal of Forecasting, Elsevier, vol. 24(1), pages 34-75.
    18. Mei-Chen Lin, 2020. "When analysts encounter lottery-like stocks: lottery-like stocks and analyst stock recommendations," Review of Quantitative Finance and Accounting, Springer, vol. 55(1), pages 327-353, July.
    19. Oya Altınkılıç & Vadim S. Balashov & Robert S. Hansen, 2013. "Are Analysts' Forecasts Informative to the General Public?," Management Science, INFORMS, vol. 59(11), pages 2550-2565, November.
    20. Altınkılıç, Oya & Hansen, Robert S. & Ye, Liyu, 2016. "Can analysts pick stocks for the long-run?," Journal of Financial Economics, Elsevier, vol. 119(2), pages 371-398.

    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:wut:journl:v:33:y:2023:i:4:p:155-170:id:9. 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: Adam Kasperski (email available below). General contact details of provider: https://edirc.repec.org/data/iopwrpl.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.