IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v10y2022i9p168-d895380.html
   My bibliography  Save this article

Does the Adaptive Market Hypothesis Reconcile the Behavioral Finance and the Efficient Market Hypothesis?

Author

Listed:
  • Umara Noreen

    (College of Business Administration, Prince Sultan University, Riyadh 11586, Saudi Arabia)

  • Attayah Shafique

    (Department of Management Sciences, COMSATS University Islamabad, Islamabad 45550, Pakistan
    Department of Communication and Management Sciences, Pakistan Institute of Engineering and Applied Sciences, Nilore, Islamabad 44000, Pakistan)

  • Usman Ayub

    (Department of Management Sciences, COMSATS University Islamabad, Islamabad 45550, Pakistan)

  • Syed Kashif Saeed

    (Department of Communication and Management Sciences, Pakistan Institute of Engineering and Applied Sciences, Nilore, Islamabad 44000, Pakistan)

Abstract

This study aims to test the adaptive market hypothesis by using the myopic behavior of investors as a new proxy. The data have been taken from New York Stock Exchange from December 1994 to December 2020. Following this collection of data, the companies’ stock prices were distributed into six different portfolios based on size, investment, a book-to-market value, and operating profit. Ordinal logistic regression was used to calculate the probability of recovery of losses after experiencing a decline in the market. As part of the robustness analysis, this study replaces the Sharpe ratio with a Lower Partial Moment ratio. Most of the results for the Sharpe ratio and Lower Partial Moment ratio are similar. During 1995–1999, 2002–2006, and 2010–2020, the investors have not shown myopic behavior towards losses, but from 2000–2001 and 2007–2009 the investors exhibited myopic characteristics. Furthermore, as investors move between myopic and non-myopic loss aversion, the study reports that the US market is both efficient and inefficient at various points in time, following the adaptive market hypothesis. Thus, such a finding could act as a basis for future investment models by adapting traditional models or by building and contributing to the development of new ones.

Suggested Citation

  • Umara Noreen & Attayah Shafique & Usman Ayub & Syed Kashif Saeed, 2022. "Does the Adaptive Market Hypothesis Reconcile the Behavioral Finance and the Efficient Market Hypothesis?," Risks, MDPI, vol. 10(9), pages 1-14, August.
    • Handle: RePEc:gam:jrisks:v:10:y:2022:i:9:p:168-:d:895380
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/10/9/168/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/10/9/168/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bawa, Vijay S., 1975. "Optimal rules for ordering uncertain prospects," Journal of Financial Economics, Elsevier, vol. 2(1), pages 95-121, March.
    2. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    3. Frazzini, Andrea & Lamont, Owen A., 2008. "Dumb money: Mutual fund flows and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 88(2), pages 299-322, May.
    4. 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..
    5. repec:pri:cepsud:91malkiel is not listed on IDEAS
    6. Blavatskyy, Pavlo & Pogrebna, Ganna, 2009. "Myopic loss aversion revisited," Economics Letters, Elsevier, vol. 104(1), pages 43-45, July.
    7. Maria Rosa Borges, 2010. "Efficient market hypothesis in European stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 16(7), pages 711-726.
    8. Kaplanski, Guy & Levy, Haim, 2010. "Sentiment and stock prices: The case of aviation disasters," Journal of Financial Economics, Elsevier, vol. 95(2), pages 174-201, February.
    9. Lee, Boram & Veld-Merkoulova, Yulia, 2016. "Myopic loss aversion and stock investments: An empirical study of private investors," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 235-246.
    10. Ariél Pakes & Zvi Griliches, 1984. "Estimating Distributed Lags in Short Panels with an Application to the Specification of Depreciation Patterns and Capital Stock Constructs," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(2), pages 243-262.
    11. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2015. "Sentiment-prone investors and volatility dynamics between spot and futures markets," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 180-196.
    12. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    13. Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
    14. Aggarwal, Divya & Damodaran, Uday, 2020. "Ambiguity attitudes and myopic loss aversion: Experimental evidence using carnival games," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    15. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Azizah Abu Bakar & Antonios Siganos & Evangelos Vagenas‐Nanos, 2014. "Does Mood Explain the Monday Effect?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 409-418, September.
    16. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    17. Shefrin, Hersh & Statman, Meir, 2000. "Behavioral Portfolio Theory," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(2), pages 127-151, June.
    18. Mlambo, Chipo & Biekpe, Nicholas, 2007. "The efficient market hypothesis: Evidence from ten African stock markets," MPRA Paper 25968, University Library of Munich, Germany, revised 2007.
    19. Xue Dong He & Xun Yu Zhou, 2014. "Myopic loss aversion, reference point, and money illusion," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1541-1554, September.
    20. Lin Liu & Qiguang Chen, 2020. "How to compare market efficiency? The Sharpe ratio based on the ARMA-GARCH forecast," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-21, December.
    21. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    22. Raone Botteon Costa, 2018. "A systematic test for myopic loss aversion theory," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 10(4), pages 320-335, October.
    23. Shafique, Attayah & Ayub, Usman & Zakaria, Muhammad, 2019. "Don’t let the Greed catch you! Pleonexia rule applied to Pakistan stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 157-168.
    24. Fama, Eugene F & French, Kenneth R, 1995. "Size and Book-to-Market Factors in Earnings and Returns," Journal of Finance, American Finance Association, vol. 50(1), pages 131-155, March.
    25. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    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. Indranil Ghosh & Esteban Alfaro-Cortés & Matías Gámez & Noelia García-Rubio, 2023. "COVID-19 Media Chatter and Macroeconomic Reflectors on Black Swan: A Spanish and Indian Stock Markets Comparison," Risks, MDPI, vol. 11(5), pages 1-27, May.

    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. Qianwei Ying & Tahir Yousaf & Qurat ul Ain & Yasmeen Akhtar & Muhammad Shahid Rasheed, 2019. "Stock Investment and Excess Returns: A Critical Review in the Light of the Efficient Market Hypothesis," JRFM, MDPI, vol. 12(2), pages 1-22, June.
    2. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    3. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    4. Thomas Holtfort, 2019. "From standard to evolutionary finance: a literature survey," Management Review Quarterly, Springer, vol. 69(2), pages 207-232, June.
    5. Yin, Libo & Liao, Huiyi, 2021. "Big is brilliant: Understanding the Chinese size effect through profitability shocks," International Review of Financial Analysis, Elsevier, vol. 74(C).
    6. Senarathne Chamil W., 2020. "Are Religious Believers Irrational: A Direct Test from an Efficient Market Hypothesis," Financial Sciences. Nauki o Finansach, Sciendo, vol. 25(1), pages 35-53, March.
    7. Azubuike Samuel Agbam, 2015. "Tests of Random Walk and Efficient Market Hypothesis in Developing Economies: Evidence from Nigerian Capital Market," International Journal of Management Sciences, Research Academy of Social Sciences, vol. 5(1), pages 1-53.
    8. Joep Sonnemans, 2003. "Price Clustering and Natural Resistance Points in the Dutch Stock Market," Tinbergen Institute Discussion Papers 03-043/1, Tinbergen Institute.
    9. Jitka Veselá & Alžběta Zíková, 2022. "Are the Czech, Polish, German and Dutch markets taking a random walk? [Konají český, polský, německý a nizozemský trh náhodnou procházku?]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2022(2), pages 19-38.
    10. Muchnik, Lev & Bunde, Armin & Havlin, Shlomo, 2009. "Long term memory in extreme returns of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4145-4150.
    11. Michele Costola & Massimiliano Caporin, 2016. "Rational Learning For Risk-Averse Investors By Conditioning On Behavioral Choices," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-26, March.
    12. Thibaut Mastrolia & Tianrui Xu, 2024. "Clearing time randomization and transaction fees for auction market design," Papers 2405.09764, arXiv.org, revised Oct 2024.
    13. Abakah, Emmanuel Joel Aikins & Abdullah, Mohammad & Yousaf, Imran & Kumar Tiwari, Aviral & Li, Yanshuang, 2024. "Economic sanctions sentiment and global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    14. Torsten Trimborn, 2018. "A Macroscopic Portfolio Model: From Rational Agents to Bounded Rationality," Papers 1805.11036, arXiv.org, revised Oct 2018.
    15. Romain Bocher, 2022. "The Intersubjective Markets Hypothesis," Journal of Interdisciplinary Economics, , vol. 34(1), pages 35-50, January.
    16. Imran Yousaf & Shoaib Ali & Syed Zulfiqar Ali Shah, 2018. "Herding behavior in Ramadan and financial crises: the case of the Pakistani stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-14, December.
    17. Vicentina Gomes, Liliane & Odálio dos Santos, José & Lana Silva, Cristiane & Ferreira de Souza, Maurício, 2018. "Divulgações de informações e o efeito no retorno de ações da maior empresa de educação listada na B3 (Brasil, Bolsa, Balcão) [Information disclosures and the effect on the return of stocks of the l," MPRA Paper 93123, University Library of Munich, Germany, revised 30 May 2018.
    18. Kostanjcar, Zvonko & Jeren, Branko & Juretic, Zeljan, 2012. "Impact of uncertainty in expected return estimation on stock price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5563-5571.
    19. Yensen Ni, 2024. "Navigating Energy and Financial Markets: A Review of Technical Analysis Used and Further Investigation from Various Perspectives," Energies, MDPI, vol. 17(12), pages 1-22, June.
    20. Fu, Jie & Zhang, Xiaoqi & Zhou, Wenyuan & Lyu, Yang, 2024. "A continuous heterogeneous agent model for multi-asset pricing and portfolio construction under market matching friction," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 267-283.

    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:gam:jrisks:v:10:y:2022:i:9:p:168-:d:895380. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.