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From efficient markets to adaptive markets: Evidence from the French stock exchange

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  • Boya, Christophe M.

Abstract

This paper examines the degree of market efficiency of the French Stock Market and tries to check both the efficient market hypothesis (EMH) and the adaptative market hypothesis (AMH). We use a rolling variance ratio test approach in order to provide an overview of the efficiency behavior from 1988 to 2018. We find that our results are consistent with the AMH. Indeed, it seems that the French stock market presents successive periods of efficiency and inefficiency. Moreover, inefficiency periods coincide with major macroeconomics events.

Suggested Citation

  • Boya, Christophe M., 2019. "From efficient markets to adaptive markets: Evidence from the French stock exchange," Research in International Business and Finance, Elsevier, vol. 49(C), pages 156-165.
  • Handle: RePEc:eee:riibaf:v:49:y:2019:i:c:p:156-165
    DOI: 10.1016/j.ribaf.2019.03.005
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    1. Alexandru Todea & Maria Ulici & Simona Silaghi, 2009. "Adaptive Markets Hypothesis - Evidence from Asia-Pacific Financial Markets," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 1(1), pages 007-013, December.
    2. Jean Matouk & Jean-Louis Monino, 2005. "Le marché de Paris a la mémoire courte !," Revue d'Économie Financière, Programme National Persée, vol. 81(4), pages 133-155.
    3. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, Oxford University Press, vol. 69(1), pages 99-118.
    4. Kim, Jae H. & Shamsuddin, Abul, 2008. "Are Asian stock markets efficient? Evidence from new multiple variance ratio tests," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 518-532, June.
    5. Christine Stachowiak, 2004. "Prévisibilité des rentabilités boursières. Une étude empirique du marché boursier français sur données intraquotidiennes," Économie et Prévision, Programme National Persée, vol. 166(5), pages 71-85.
    6. Chow, K. Victor & Denning, Karen C., 1993. "A simple multiple variance ratio test," Journal of Econometrics, Elsevier, vol. 58(3), pages 385-401, August.
    7. Larry G. Epstein & Martin Schneider, 2008. "Ambiguity, Information Quality, and Asset Pricing," Journal of Finance, American Finance Association, vol. 63(1), pages 197-228, February.
    8. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.
    9. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    10. Valérie Mignon, 1998. "Méthodes d'estimation de l'exposant de Hurst. Application aux rentabilités boursières," Économie et Prévision, Programme National Persée, vol. 132(1), pages 193-214.
    11. Neely, Christopher J. & Weller, Paul A. & Ulrich, Joshua M., 2009. "The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(2), pages 467-488, April.
    12. Christine Stachowiak, 2004. "Prévisibilité des rentabilités boursières. Une étude empirique du marché boursier français sur données intraquotidiennes," Economie & Prévision, La Documentation Française, vol. 166(5), pages 71-85.
    13. Liu, Christina Y & He, Jia, 1991. "A Variance-Ratio Test of Random Walks in Foreign Exchange Rates," Journal of Finance, American Finance Association, vol. 46(2), pages 773-785, June.
    14. Shan, Liwei & Gong, Stephen X., 2012. "Investor sentiment and stock returns: Wenchuan Earthquake," Finance Research Letters, Elsevier, vol. 9(1), pages 36-47.
    15. Ito, Mikio & Sugiyama, Shunsuke, 2009. "Measuring the degree of time varying market inefficiency," Economics Letters, Elsevier, vol. 103(1), pages 62-64, April.
    16. Ser‐Huang Poon, 1996. "Persistence and mean reversion in UK stock returns," European Financial Management, European Financial Management Association, vol. 2(2), pages 169-196, July.
    17. Christophe Boya & Jean-Louis Monino, 2010. "The impact of exogenous information on stock value through the coloration concept: a test model," Journal of Innovation Economics, De Boeck Université, vol. 0(2), pages 163-180.
    18. 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.
    19. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2012. "Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1607-1626.
    20. Wright, Jonathan H, 2000. "Alternative Variance-Ratio Tests Using Ranks and Signs," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 1-9, January.
    21. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    22. Choi, In, 1999. "Testing the Random Walk Hypothesis for Real Exchange Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 293-308, May-June.
    23. Urquhart, Andrew & McGroarty, Frank, 2016. "Are stock markets really efficient? Evidence of the adaptive market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 39-49.
    24. Mobarek, Asma & Fiorante, Angelo, 2014. "The prospects of BRIC countries: Testing weak-form market efficiency," Research in International Business and Finance, Elsevier, vol. 30(C), pages 217-232.
    25. Hoque, Hafiz A.A.B. & Kim, Jae H. & Pyun, Chong Soo, 2007. "A comparison of variance ratio tests of random walk: A case of Asian emerging stock markets," International Review of Economics & Finance, Elsevier, vol. 16(4), pages 488-502.
    26. 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.
    27. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
    28. Benjamin Miranda Tabak, 2003. "The random walk hypothesis and the behaviour of foreign capital portfolio flows: the Brazilian stock market case," Applied Financial Economics, Taylor & Francis Journals, vol. 13(5), pages 369-378.
    29. Kim, Jae H., 2006. "Wild bootstrapping variance ratio tests," Economics Letters, Elsevier, vol. 92(1), pages 38-43, July.
    30. Hiremath, Gourishankar S & Kumari, Jyoti, 2014. "Stock returns predictability and the adaptive market hypothesis in emerging markets: evidence from India," MPRA Paper 58378, University Library of Munich, Germany.
    31. Christophe Boya, 2017. "Testing capital market efficiency," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 19(2), pages 194-224.
    32. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    33. Kim, Jae H., 2009. "Automatic variance ratio test under conditional heteroskedasticity," Finance Research Letters, Elsevier, vol. 6(3), pages 179-185, September.
    34. Kian-Ping Lim & Weiwei Luo & Jae H. Kim, 2013. "Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests," Applied Economics, Taylor & Francis Journals, vol. 45(8), pages 953-962, March.
    35. Kwong-C. Cheung & J. Andrew Coutts, 2001. "A note on weak form market efficiency in security prices: evidence from the Hong Kong stock exchange," Applied Economics Letters, Taylor & Francis Journals, vol. 8(6), pages 407-410.
    36. Khuntia, Sashikanta & Pattanayak, J.K., 2018. "Adaptive market hypothesis and evolving predictability of bitcoin," Economics Letters, Elsevier, vol. 167(C), pages 26-28.
    37. Hiremath, Gourishankar S. & Narayan, Seema, 2016. "Testing the adaptive market hypothesis and its determinants for the Indian stock markets," Finance Research Letters, Elsevier, vol. 19(C), pages 173-180.
    38. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    39. Ahmad, Rubi & Rhee, S. Ghon & Wong, Yuen Meng, 2012. "Foreign exchange market efficiency under recent crises: Asia-Pacific focus," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1574-1592.
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    Cited by:

    1. Thiago Christiano Silva & Benjamin Miranda Tabak & Idamar Magalhães Ferreira, 2019. "Modeling Investor Behavior Using Machine Learning: Mean-Reversion and Momentum Trading Strategies," Complexity, Hindawi, vol. 2019, pages 1-14, December.

    More about this item

    Keywords

    Adaptive markets; Efficient markets; Rolling variance ratio;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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