Adaptive Market Hypothesis And Overconfidence Bias

Manel Mahjoubi; Jamel Eddine Henchiri

doi:10.36923/economa.v27i1.237

Open Access Article Economics

Manel Mahjoubi ⁽¹⁾, Jamel Eddine Henchiri ⁽²⁾

(1) RED Laboratory, Higher Institute of Management, University of Gabes, Tunisia,

(2) RED Laboratory, Higher Institute of Management, University of Gabes, Tunisia

https://doi.org/10.36923/economa.v27i1.237

Issue
Vol. 27 No. 1 (2024)

Submitted
October 3, 2023

Published
February 20, 2024

Keywords:

Efficient market hypothesis, behavioural finance, Adaptive Market Hypothesis, Overconfidence Bias

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Abstract

This paper examines the effect of excessive investor confidence on market efficiency. We study this impact for 21 developed markets and 25 emerging markets for a period from January 2006 until June 2020. First, we estimate weak market efficiency using the auto-correlation test (Ljung-Box, 1978). Thus, based on the adaptive approach, we assume that the overconfidence of investors has a negative impact on market efficiency. Concerning the over-confidence variable; we use the transaction volume decomposition method of Chuang and Lee (2006). Finally, we used the logit panel model to study the impact the impact of investor overconfidence on market efficiency. The result shows that during our study period, the trust bias had no impact either on the efficiency of developed markets or on the efficiency of emerging markets. We attribute this result to successive crises during our study period, including the subprime crisis, the eurozone crisis, the stock market crash in China, and the COVID crisis, which likely caused investors to become pessimistic and lose confidence in the stock market.

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References

Abbes, M. (2013). Does Overconfidence Bias Explain Volatility During the Global Financial Crisis? Transition Studies Review, 19, 291-312. https://doi.org/10.1007/s11300-012-0234-6 DOI: https://doi.org/10.1007/s11300-012-0234-6

Abedini, B. (n.d.). Weak-form efficiency: stock market in the Gulf Cooperation Council countries. SCMS Journal of Indian Management, 2009, 15-20.

Almail, A., & Almudhaf, F. (2017). Adaptive Market Hypothesis: Evidence from three centuries of UK data. Economics and Business Letters, 6(2), 48-53. DOI: https://doi.org/10.17811/ebl.6.2.2017.48-53

Aumeboonsuke, V., & Dryver, A. L. (2014). The importance of using a test of weak-form market efficiency that does not require investigating the data first. International Review of Economics & Finance, 33, 350-357. https://doi.org/10.1016/j.iref.2014.02.009 DOI: https://doi.org/10.1016/j.iref.2014.02.009

Barber, B. M., & Odean, T. (2001). Boys will be Boys: Gender, Overconfidence, and Common Stock Investment. The Quarterly Journal of Economics, 116, 261-292. https://doi.org/10.1162/003355301556400 DOI: https://doi.org/10.1162/003355301556400

Boujelbène, M., Boujelbène, Y., & Bouri, A. (2009). Overconfidence bias: Explanation of market anomalies French market case. Journal of Applied Economic Sciences, 4.

Boussaidi, R. (2022). Implications of the overconfidence bias in presence of private information: Evidence from MENA stock markets. International Journal of Finance & Economics, 27(3), 3660-3678. https://doi.org/10.1002/ijfe.2343 DOI: https://doi.org/10.1002/ijfe.2343

Boya, C. M. (2019). From efficient markets to adaptive markets: Evidence from the French stock exchange. Research in International Business and Finance, 49, 156-165. https://doi.org/10.1016/j.ribaf.2019.03.005 DOI: https://doi.org/10.1016/j.ribaf.2019.03.005

Chkioua, D. H. (2021). Excess Volatility in the Tunisian Stock Market: Explanation by Behavioral Finance. South Asian Journal of Social Studies and Economics, 12, 1-11. https://doi.org/10.9734/sajsse/2021/v12i430310 DOI: https://doi.org/10.9734/sajsse/2021/v12i430310

Chuang, W.-I., & Lee, B.-S. (2006). An empirical evaluation of the overconfidence hypothesis. Journal of Banking & Finance, 30, 2489-2515. https://doi.org/10.1016/j.jbankfin.2005.08.007 DOI: https://doi.org/10.1016/j.jbankfin.2005.08.007

Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor Psychology and Security Market Under- and Overreactions. The Journal of Finance, 53, 1839-1885. https://doi.org/10.1111/0022-1082.00077 DOI: https://doi.org/10.1111/0022-1082.00077

Daniel, K. D., Hirshleifer, D., & Subrahmanyam, A. (2001). Overconfidence, Arbitrage, and Equilibrium Asset Pricing. The Journal of Finance, 56, 921-965. https://doi.org/10.1111/0022-1082.00350 DOI: https://doi.org/10.1111/0022-1082.00350

Drury, C. (2008). Management and Cost Accounting. Retrieved from https://www.perlego.com/fr/book/2105539/management-and-cost-accounting-pdf

Ertaş, F., & Özkan, O. (2018). Piyasa Etkinliği Açısından Adaptif Piyasa Hipotezi'nin Test Edilmesi: Türkiye ve ABD Hisse Senedi Piyasaları Örneği-Testing the Adaptive Market Hypothesis in Terms of Market Efficiency: The Case of Turkey and the US Stock Markets, 642, 23-40.

Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25, 383-417. https://doi.org/10.2307/2325486 DOI: https://doi.org/10.1111/j.1540-6261.1970.tb00518.x

Fama, E. F. (1965). The Behavior of Stock-Market Prices. DOI: https://doi.org/10.1086/294743

Farmer, J. D., & Lo, A. W. (1999). Frontiers of finance: evolution and efficient markets. Proc Natl Acad Sci U S A, 96, 9991-9992. https://doi.org/10.1073/pnas.96.18.9991 DOI: https://doi.org/10.1073/pnas.96.18.9991

Frankfurter, G., & Mcgoun, E. (2001). Anomalies in finance: What are they and what are they good for? International Review of Financial Analysis, 10, 407-429. https://doi.org/10.1016/S1057-5219(01)00061-8 DOI: https://doi.org/10.1016/S1057-5219(01)00061-8

Giglio, S., Maggiori, M., Rao, K., Stroebel, J., & Weber, A. (2021). Climate Change and Long-Run Discount Rates: Evidence from Real Estate. The Review of Financial Studies, 34, 3527-3571. https://doi.org/10.1093/rfs/hhab032 DOI: https://doi.org/10.1093/rfs/hhab032

Hiremath, G. S., & Narayan, S. (2016). Testing the adaptive market hypothesis and its determinants for the Indian stock markets. Finance Research Letters, 19, 173-180. https://doi.org/10.1016/j.frl.2016.07.009 DOI: https://doi.org/10.1016/j.frl.2016.07.009

Hirshleifer, D., & Shumway, T. (2003). Good Day Sunshine: Stock Returns and the Weather. The Journal of Finance, 58, 1009-1032. https://doi.org/10.1111/1540-6261.00556 DOI: https://doi.org/10.1111/1540-6261.00556

Jlassi, M., Naoui, K., & Mansour, W. (2014). Overconfidence Behavior and Dynamic Market Volatility: Evidence from International Data. Procedia Economics and Finance, 13, 128-142. https://doi.org/10.1016/S2212-5671(14)00435-3 DOI: https://doi.org/10.1016/S2212-5671(14)00435-3

Kim, J. H., Shamsuddin, A., & Lim, K.-P. (2011). Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data. Journal of Empirical Finance, 18, 868-879. https://doi.org/10.1016/j.jempfin.2011.08.002 DOI: https://doi.org/10.1016/j.jempfin.2011.08.002

Kılıç, Y. (2020). Adaptive Market Hypothesis: Evidence from the Turkey Stock Market.

Kruger, J. W., & Vatiswa, Nthoesane, M. G. (2011). Share Price Reaction to Earnings Announcement on the JSE-ALTX. https://doi.org/10.2139/ssrn.1935198 DOI: https://doi.org/10.2139/ssrn.1935198

Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65, 297-303. https://doi.org/10.1093/biomet/65.2.297 DOI: https://doi.org/10.1093/biomet/65.2.297

Lo, A. W. (2019). Adaptive markets: financial evolution at the speed of thought. Princeton University Press. https://doi.org/10.1515/9780691196800 DOI: https://doi.org/10.1515/9780691196800

Lo, A. W. (2012). Adaptive Markets and the New World Order. MIT web domain. https://doi.org/10.2139/ssrn.1977721 DOI: https://doi.org/10.2139/ssrn.1977721

Lo, A. W. (2005). Reconciling Efficient Markets with Behavioral Finance: The Adaptive Markets Hypothesis (SSRN Scholarly Paper No. ID 1702447). Social Science Research Network, Rochester, NY.

Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective (SSRN Scholarly Paper No. ID 602222). Social Science Research Network, Rochester, NY.

Montier, J. (2002). Darwin's Mind: The Evolutionary Foundations of Heuristics and Biases. https://doi.org/10.2139/ssrn.373321 DOI: https://doi.org/10.2139/ssrn.373321

Mushinada, V. N. C., & Veluri, V. S. S. (2018). Investors overconfidence behaviour at Bombay Stock Exchange. International Journal of Managerial Finance, 14, 613-632. https://doi.org/10.1108/IJMF-05-2017-0093 DOI: https://doi.org/10.1108/IJMF-05-2017-0093

Naseem, S., Mohsin, M., Hui, W., Liyan, G., & Penglai, K. (2021a). The Investor Psychology and Stock Market Behavior During the Initial Era of COVID-19: A Study of China, Japan, and the United States. Front Psychol, 12, 626934. https://doi.org/10.3389/fpsyg.2021.626934

Naseem, S., Mohsin, M., Hui, W., Liyan, G., & Penglai, K. (2021b). The Investor Psychology and Stock Market Behavior During the Initial Era of COVID-19: A Study of China, Japan, and the United States. Front Psychol, 12, 626934. https://doi.org/10.3389/fpsyg.2021.626934 DOI: https://doi.org/10.3389/fpsyg.2021.626934

Neely, C. J., Weller, P. A., & Ulrich, J. M. (2009). The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market. The Journal of Financial and Quantitative Analysis, 44, 467-488. https://doi.org/10.1017/S0022109009090103 DOI: https://doi.org/10.1017/S0022109009090103

Odean, T. (1998). Are Investors Reluctant to Realize Their Losses? The Journal of Finance, 53, 1775-1798. https://doi.org/10.1111/0022-1082.00072 DOI: https://doi.org/10.1111/0022-1082.00072

Phan Tran Trung, D., & Pham Quang, H. (2019). Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market. Journal of Risk and Financial Management, 12, 81. https://doi.org/10.3390/jrfm12020081 DOI: https://doi.org/10.3390/jrfm12020081

Pikulina, E., Renneboog, L., & Tobler, P. N. (2017). Overconfidence and investment: An experimental approach. Journal of Corporate Finance, 43, 175-192. https://doi.org/10.1016/j.jcorpfin.2017.01.002 DOI: https://doi.org/10.1016/j.jcorpfin.2017.01.002

Rossi, M. (2015). The efficient market hypothesis and calendar anomalies: a literature review. International Journal of Managerial and Financial Accounting, 7, 285-296. https://doi.org/10.1504/IJMFA.2015.074905 DOI: https://doi.org/10.1504/IJMFA.2015.074905

Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17, 83-104. https://doi.org/10.1257/089533003321164967 DOI: https://doi.org/10.1257/089533003321164967

Shrotryia, V. K., & Kalra, H. (2021a). COVID-19 and overconfidence bias: the case of developed, emerging and frontier markets. International Journal of Emerging Markets, 18, 633-665. https://doi.org/10.1108/IJOEM-09-2020-1019 DOI: https://doi.org/10.1108/IJOEM-09-2020-1019

Shrotryia, V. K., & Kalra, H. (2021b). Herding in the crypto market: a diagnosis of heavy distribution tails. Review of Behavioral Finance, 14, 566-587. https://doi.org/10.1108/RBF-02-2021-0021 DOI: https://doi.org/10.1108/RBF-02-2021-0021

Simon, H. A. (1955). On a Class of Skew Distribution Functions. Biometrika, 42, 425-440. https://doi.org/10.2307/2333389 DOI: https://doi.org/10.1093/biomet/42.3-4.425

Statman, M., Thorley, S., & Vorkink, K. (2006). Investor Overconfidence and Trading Volume. The Review of Financial Studies, 19, 1531-1565. https://doi.org/10.1093/rfs/hhj032 DOI: https://doi.org/10.1093/rfs/hhj032

Subash, R. (2012). Role of Behavioral Finance in Portfolio Investment Decisions: Evidence from India.

Thaler, R. H. (2005). Advances in Behavioral Finance, Volume II. Princeton University Press. https://doi.org/10.1515/9781400829125 DOI: https://doi.org/10.1515/9781400829125

Thaler, R. H. (1999). Mental accounting matters. Journal of Behavioral Decision Making, 12, 183-206. https://doi.org/10.1002/(SICI)1099-0771(199909)12:3<183::AID-BDM318>3.0.CO;2-F DOI: https://doi.org/10.1002/(SICI)1099-0771(199909)12:3<183::AID-BDM318>3.0.CO;2-F

Zafar, Z., & Siddiqui, D. A. (2020). Behavioral Finance Perspectives on Pakistan Stock Market Efficiency: Assessing the Prospect Theory Empirically Using Adaptive Pattern of Efficiency across Military and Democratic Phases. https://doi.org/10.2139/ssrn.3683106 DOI: https://doi.org/10.2139/ssrn.3683106

Authors

Manel Mahjoubi

RED Laboratory, Higher Institute of Management, University of Gabes

https://orcid.org/0009-0009-6300-2816

mnlmahjoubi@yahoo.com (Primary Contact)

Jamel Eddine Henchiri

RED Laboratory, Higher Institute of Management, University of Gabes

https://orcid.org/0000-0001-7675-056X

Author Biographies

Manel Mahjoubi, RED Laboratory, Higher Institute of Management, University of Gabes

Dr Maneel Mahjoubi is currently an assistant at the Higher Institute of Management, University of Gabes, in Tunisia. He obtained his PhD in finance from Faculty of Economics and Management - University of Sfax, in Tunisia. Member at the Research Unit on Research, Business and Decisions (UR-RED), in Higher Institute of Management of Gabes (University of Gabes, in Tunisia). He also participated in several high-profile conferences.

Jamel Eddine Henchiri, RED Laboratory, Higher Institute of Management, University of Gabes

Pr. Jamel Eddine Henchiri, is currently a Professor at the Higher Institute of Management- University of Gabes, in Tunisia.Also, he is the director of the Research Unit on Research, Business and Decisions (UR-RED), in the University of Gabes, in Tunisia). Since its creation in 2013. In addition, he has been the president of the scientific journal Journal of Academic Finance (JoAF), since 2010. Also, he is the founder and main organizer of the international conference CSIFA: International Scientific Conference on Finance and Insurance, since 2006, and participated in several high-profile conferences. He was also appointed director of the Higher Institute of Management- University of Gabes, in Tunisia, during the years 2013 and 2014. He obtained his PhD in Management Science from Rennes University in France (1 IGR-IAE de Rennes: Rennes, Bretagne, FR).

Mahjoubi, M., & Henchiri, J. E. (2024). Adaptive Market Hypothesis And Overconfidence Bias. Innovation Economics Frontiers, 27(1), 8–16. https://doi.org/10.36923/economa.v27i1.237

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