IDEAS home Printed from https://ideas.repec.org/a/vrs/foeste/v15y2015i2p27-41n2.html
   My bibliography  Save this article

Behavioural Present Value Defined as Fuzzy Number – a New Approach

Author

Listed:
  • Piasecki Krzysztof

    (Poznań University of Economics and Business, Department of Operations Research, Al. Niepodległości 10, 61-875 Poznań, Poland)

  • Siwek Joanna

    (Poznań University of Economics and Business, Department of Operations Research, Al. Niepodległości 10, 61-875 Poznań, Poland)

Abstract

The behavioural present value is defined as a fuzzy number assessed under the impact of chosen behavioural factors. The first formal model turned out to be burdened with some formal defects which are finally corrected in the presented article. In this way a new modified formal model of a behavioural present value is obtained. New model of the behavioural present value is used to explain the phenomenon of market equilibrium on the efficient financial market remaining in the state of financial imbalance. These considerations are illustrated by means of extensive numerical case study.

Suggested Citation

  • Piasecki Krzysztof & Siwek Joanna, 2015. "Behavioural Present Value Defined as Fuzzy Number – a New Approach," Folia Oeconomica Stetinensia, Sciendo, vol. 15(2), pages 27-41, December.
    • Handle: RePEc:vrs:foeste:v:15:y:2015:i:2:p:27-41:n:2
    DOI: 10.1515/foli-2015-0033
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/foli-2015-0033
    Download Restriction: no
    File URL: https://libkey.io/10.1515/foli-2015-0033?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. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    2. Yong Fang & Kin Keung Lai & Shouyang Wang, 2008. "Fuzzy Portfolio Optimization," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-77926-1, December.
    3. A. H. Boussabaine & Taha Elhag, 1999. "Applying fuzzy techniques to cash flow analysis," Construction Management and Economics, Taylor & Francis Journals, vol. 17(6), pages 745-755.
    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. Krzysztof Piasecki & Anna Łyczkowska-Hanćkowiak, 2019. "Representation of Japanese Candlesticks by Oriented Fuzzy Numbers," Econometrics, MDPI, vol. 8(1), pages 1-24, December.
    2. 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.
    3. Joanna Siwek & Patryk Żywica, 2025. "Application of Fuzzy Discount Factors in Behavioural Decision-Making for Financial Market Modelling," Econometrics, MDPI, vol. 13(1), pages 1-12, January.
    4. 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.

    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. Piasecki, Krzysztof, 2011. "Rozmyte zbiory probabilistyczne jako narzędzie finansów behawioralnych [Fuzzy Probabilistic Sets as a Tool for Behavioural Finance]," MPRA Paper 46218, University Library of Munich, Germany.
    2. Krzysztof Piasecki, 2013. "Behavioural present value," Papers 1302.0539, arXiv.org.
    3. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    4. Liu, Hong & Qi, Lina & Li, Zaili, 2019. "Insider trading, representativeness heuristic insider, and market regulation," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 48-64.
    5. Seungwook Bahng, 2003. "Do Psychological Barriers Exist in the Stock Price Indices? Evidence from Asia's Emerging Markets," International Area Studies Review, Center for International Area Studies, Hankuk University of Foreign Studies, vol. 6(1), pages 35-52, March.
    6. Hou, Yang & Meng, Jiayin, 2018. "The momentum effect in the Chinese market and its relationship with the simultaneous and the lagged investor sentiment," MPRA Paper 94838, University Library of Munich, Germany.
    7. Keval Amin & Erica Harris, 2022. "The Effect of Investor Sentiment on Nonprofit Donations," Journal of Business Ethics, Springer, vol. 175(2), pages 427-450, January.
    8. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    9. Abdul Hamid Habbe, 2017. "Estimation Error of Earnings Information: A Test of Representativeness and Anchoring-adjustment Heuristic," International Journal of Economics and Financial Issues, Econjournals, vol. 7(1), pages 224-233.
    10. Nicholas Apergis & Vasilios Plakandaras & Ioannis Pragidis, 2022. "Industry momentum and reversals in stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3093-3138, July.
    11. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2011. "New evidence on oil price and firm returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3253-3262.
    12. Qingbin Cui & Makarand Hastak & Daniel Halpin, 2010. "Systems analysis of project cash flow management strategies," Construction Management and Economics, Taylor & Francis Journals, vol. 28(4), pages 361-376.
    13. Gric, Zuzana & Ehrenbergerova, Dominika & Hodula, Martin, 2022. "The power of sentiment: Irrational beliefs of households and consumer loan dynamics," Journal of Financial Stability, Elsevier, vol. 59(C).
    14. Wu, Chen-Hui & Wu, Chin-Shun & Liu, Victor W., 2009. "The conservatism bias in an emerging stock market: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 17(4), pages 494-505, September.
    15. Brav, Alon & Geczy, Christopher & Gompers, Paul A., 2000. "Is the abnormal return following equity issuances anomalous?," Journal of Financial Economics, Elsevier, vol. 56(2), pages 209-249, May.
    16. Mark Grinblatt & Tobias J. Moskowitz, 2002. "What Do We Really Know About the Cross-Sectional Relation Between Past and Expected Returns?," NBER Working Papers 8744, National Bureau of Economic Research, Inc.
    17. L. Lin & M. Schatz & D. Sornette, 2019. "A simple mechanism for financial bubbles: time-varying momentum horizon," Quantitative Finance, Taylor & Francis Journals, vol. 19(6), pages 937-959, June.
    18. Li, Jinfang, 2014. "Multi-period sentiment asset pricing model with information," International Review of Economics & Finance, Elsevier, vol. 34(C), pages 118-130.
    19. Jorgensen, Bjorn & Li, Jing & Sadka, Gil, 2012. "Earnings dispersion and aggregate stock returns," Journal of Accounting and Economics, Elsevier, vol. 53(1), pages 1-20.
    20. Blackburn, Douglas W. & Cakici, Nusret, 2017. "Overreaction and the cross-section of returns: International evidence," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 1-14.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    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:vrs:foeste:v:15:y:2015:i:2:p:27-41:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.