IDEAS home Printed from https://ideas.repec.org/a/aif/journl/v44y2025i1p17-27.html
   My bibliography  Save this article

A Study of Confusion in Investment Behavior of Mongolian People

Author

Listed:
  • Banzragch Mijiddorj

    (Graduate School of Business, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia.)

  • Bolormaa Ayurzana

    (School of Foreign Languages, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia.)

  • Uyanga Davaasuren

    (Graduate School of Business, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia.)

  • Zaya Mashlai

    (School of Business Administration and Humanities, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia.)

Abstract

Behavioral finance has gained significant attention as researchers explore how cognitive biases and emotional factors influence individual decision-making and financial markets. Unlike traditional finance, which assumes rational behavior, behavioral finance emphasizes the psychological elements that often lead to irrational investment decisions. This study applied a structured questionnaire to analyze the investment behavior of Mongolian individuals, examining twenty distinct behavioral biases. Using a scoring system and behavioral type identification tests, the study identified five key biases that affect investor decision-making: loss aversion, regret aversion, overconfidence, optimism, and illusory control. The results indicated that loss aversion and regret aversion were the most prominent biases, followed by optimism and illusory control. Overconfidence was found to have a relatively smaller effect on decision-making. These findings suggest that psychological factors play a significant role in shaping investment choices among Mongolian investors.

Suggested Citation

  • Banzragch Mijiddorj & Bolormaa Ayurzana & Uyanga Davaasuren & Zaya Mashlai, 2025. "A Study of Confusion in Investment Behavior of Mongolian People," International Journal of Science and Business, IJSAB International, vol. 44(1), pages 17-27.
    • Handle: RePEc:aif:journl:v:44:y:2025:i:1:p:17-27
    as

    Download full text from publisher

    File URL: https://ijsab.com/wp-content/uploads/2552.pdf
    Download Restriction: no
    File URL: https://www.ijsab.com/volume-44-issue-1/7734
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Singh, Bharati, 2021. "A Bibliometric Analysis of Behavioral Finance and Behavioral Accounting," American Business Review, Pompea College of Business, University of New Haven, vol. 24(2), pages 198-230, November.
    2. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. Kim, Kenneth A. & Nofsinger, John R., 2008. "Behavioral finance in Asia," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 1-7, January.
    5. Robert A. Olsen, 1998. "Behavioral Finance and Its Implications for Stock-Price Volatility," Financial Analysts Journal, Taylor & Francis Journals, vol. 54(2), pages 10-18, March.
    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. Roberto Arturo Agudelo Aguirre & Alberto Antonio Agudelo Aguirre, 2024. "Behavioral finance: Evolution from the classical theory and remarks," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 452-475, April.
    2. Zamri Ahmad & Haslindar Ibrahim & Jasman Tuyon, 2017. "Institutional investor behavioral biases: syntheses of theory and evidence," Management Research Review, Emerald Group Publishing Limited, vol. 40(5), pages 578-603, May.
    3. van den Bergh, J.C.J.M. & Botzen, W.J.W., 2015. "Monetary valuation of the social cost of CO2 emissions: A critical survey," Ecological Economics, Elsevier, vol. 114(C), pages 33-46.
    4. Shoji, Isao & Kanehiro, Sumei, 2016. "Disposition effect as a behavioral trading activity elicited by investors' different risk preferences," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 104-112.
    5. Jonathan Meng & Feng Fu, 2020. "Understanding Gambling Behavior and Risk Attitudes Using Cryptocurrency-based Casino Blockchain Data," Papers 2008.05653, arXiv.org, revised Aug 2020.
    6. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    7. Boone, Jan & Sadrieh, Abdolkarim & van Ours, Jan C., 2009. "Experiments on unemployment benefit sanctions and job search behavior," European Economic Review, Elsevier, vol. 53(8), pages 937-951, November.
    8. Castro, Luciano de & Galvao, Antonio F. & Kim, Jeong Yeol & Montes-Rojas, Gabriel & Olmo, Jose, 2022. "Experiments on portfolio selection: A comparison between quantile preferences and expected utility decision models," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    9. Jos'e Cl'audio do Nascimento, 2019. "Behavioral Biases and Nonadditive Dynamics in Risk Taking: An Experimental Investigation," Papers 1908.01709, arXiv.org, revised Apr 2023.
    10. Dash, Saumya Ranjan & Maitra, Debasish, 2018. "Does sentiment matter for stock returns? Evidence from Indian stock market using wavelet approach," Finance Research Letters, Elsevier, vol. 26(C), pages 32-39.
    11. Francesco GUALA, 2017. "Preferences: Neither Behavioural nor Mental," Departmental Working Papers 2017-05, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    12. Bin Zou, 2017. "Optimal Investment In Hedge Funds Under Loss Aversion," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-32, May.
    13. Itzhak Gilboa & Andrew Postlewaite & Larry Samuelson & David Schmeidler, 2019. "What are axiomatizations good for?," Theory and Decision, Springer, vol. 86(3), pages 339-359, May.
    14. Wiafe, Osei K. & Basu, Anup K. & Chen, En Te, 2020. "Portfolio choice after retirement: Should self-annuitisation strategies hold more equities?," Economic Analysis and Policy, Elsevier, vol. 65(C), pages 241-255.
    15. Nicholas Barberis, 2012. "A Model of Casino Gambling," Management Science, INFORMS, vol. 58(1), pages 35-51, January.
    16. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    17. Goytom Abraha Kahsay & Daniel Osberghaus, 2018. "Storm Damage and Risk Preferences: Panel Evidence from Germany," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 301-318, September.
    18. Carolin Bock & Maximilian Schmidt, 2015. "Should I stay, or should I go? – How fund dynamics influence venture capital exit decisions," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 68-82, November.
    19. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2013. "Risk-averse and Risk-seeking Investor Preferences for Oil Spot and Futures," Documentos de Trabajo del ICAE 2013-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Aug 2013.
    20. Paredes-Frigolett, Harold, 2016. "Modeling the effect of responsible research and innovation in quadruple helix innovation systems," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 126-133.

    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:aif:journl:v:44:y:2025:i:1:p:17-27. 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: Farjana Rahman (email available below). General contact details of provider: .

    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.