IDEAS home Printed from https://ideas.repec.org/a/prs/recofi/ecofi_0987-3368_2004_num_74_1_5039.html
   My bibliography  Save this article

Dow Jones, CAC 40, SBF 120 : comment expliquer que le CAC 40 est le plus volatil ?

Author

Listed:
  • Esther Jeffers
  • Damien Moyé

Abstract

[eng] Dow Jones, CAC 40 and SBF 120 : why the CAC 40 is more volatile ? . The notion that the financial markets are inherently efficient is a theory widely accepted by many researchers and professionals. It puts into question methods that seek to predict the ups and downs of financial assets. The recent volatility of the financial markets has raised this question again and raised doubts as whether the markets are able to « correctly » value the stocks they list. We therefore analyse the Dow Jones, the CAC 40 and the SBF 120 from 1993 to 2003. Four interesting conclusions may be drawn from this analysis. First, all three indexes have become more volatile since 1996. Secondly, the Dow Jones industrial average is less volatile than the French indexes used in our study. Also the indexes are closely correlated, but there is a delayed reaction. Finally, we compare the two French indexes to each other and attempt to understand why the CAC 40 is more volatile. . JEL classifications : D84, G1, G12, G14 [fre] L'hypothèse d'efficience des marchés financiers est une théorie généralement acceptée par un grand nombre d'universitaires et de praticiens. Elle met en doute la valeur des méthodes visant à prévoir le comportement des cours des actifs financiers. La volatilité constatée sur les marchés financiers a redonné une actualité certaine à ce thème et a remis en doute leur capacité à évaluer « correctement » . les actifs qui y sont cotés. Nous analysons la volatilité bimestrielle du Dow Jones, du CAC 40 et du SBF 120 entre 1993 et 2003. Quatre éléments intéressants se dégagent de cette analyse : 1 - la volatilité des . trois indices s'est amplifiée à partir de l'année 1996 ; 2 - la volatilité du Dow Jones américain est moins importante que celle des indices français retenus ici pour notre étude ; 3 - nous constatons un décalage temporel. Enfin nous nous attachons à comparer les deux marchés français et essayons de comprendre pourquoi le CAC 40 est le plus volatil. . Classification JEL : D84, G1, G12, G14

Suggested Citation

  • Esther Jeffers & Damien Moyé, 2004. "Dow Jones, CAC 40, SBF 120 : comment expliquer que le CAC 40 est le plus volatil ?," Revue d'Économie Financière, Programme National Persée, vol. 74(1), pages 203-218.
  • Handle: RePEc:prs:recofi:ecofi_0987-3368_2004_num_74_1_5039
    DOI: 10.3406/ecofi.2004.5039
    Note: DOI:10.3406/ecofi.2004.5039
    as

    Download full text from publisher

    File URL: https://doi.org/10.3406/ecofi.2004.5039
    Download Restriction: no

    File URL: https://www.persee.fr/doc/ecofi_0987-3368_2004_num_74_1_5039
    Download Restriction: no

    File URL: https://libkey.io/10.3406/ecofi.2004.5039?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. Cochrane, John H., 1991. "Volatility tests and efficient markets : A review essay," Journal of Monetary Economics, Elsevier, vol. 27(3), pages 463-485, June.
    2. 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.
    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. Ariane Szafarz, 2015. "Market Efficiency and Crises:Don’t Throw the Baby out with the Bathwater," Bankers, Markets & Investors, ESKA Publishing, issue 139, pages 20-26, November-.
    2. John H. Cochrane, 1999. "New facts in finance," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 36-58.
    3. John H. Cochrane, 2017. "Macro-Finance," Review of Finance, European Finance Association, vol. 21(3), pages 945-985.
    4. Kin-Boon Tang & Shao-Jye Wong & Shih-Kuei Lin & Szu-Lang Liao, 2020. "Excess volatility and market efficiency in government bond markets: the ASEAN-5 context," Journal of Asset Management, Palgrave Macmillan, vol. 21(2), pages 154-165, March.
    5. Tim Bollerslev & Robert J. Hodrick, 1992. "Financial Market Efficiency Tests," NBER Working Papers 4108, National Bureau of Economic Research, Inc.
    6. Guglielmo Maria Caporale & Luis A. Gil‐Alana, 2004. "Fractional cointegration and tests of present value models," Review of Financial Economics, John Wiley & Sons, vol. 13(3), pages 245-258.
    7. Ariane Szafarz, 2009. "How Did Financial-Crisis-Based Criticisms of Market Efficiency Get It So Wrong?," Working Papers CEB 09-048.RS, ULB -- Universite Libre de Bruxelles.
    8. Berardi, Michele, 2021. "Uncertainty, sentiments and time-varying risk premia," MPRA Paper 106922, University Library of Munich, Germany.
    9. Parthajit Kayal & Sayanti Mondal, 2020. "Speed of Price Adjustment in Indian Stock Market: A Paradox," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(4), pages 453-476, December.
    10. Giovanni Ferri & Doris Neuberger, 2014. "The Banking Regulatory Bubble and How to Get out of It," Rivista di Politica Economica, SIPI Spa, issue 2, pages 39-69, April-Jun.
    11. Leonardo Becchetti & Roberto Rocci & Giovanni Trovato, 2007. "Industry and time specific deviations from fundamental values in a random coefficient model," Annals of Finance, Springer, vol. 3(2), pages 257-276, March.
    12. Taipalus, Katja, 2006. "Bubbles in the Finnish and US equities markets," Scientific Monographs, Bank of Finland, number 35/2006.
    13. Wayne E. Ferson & Andrea Heuson & Tie Su, 2004. "Weak and Semi-Strong Form Stock Return Predictability, Revisited," NBER Working Papers 10689, National Bureau of Economic Research, Inc.
    14. Haberer, Markus, 2004. "Might a Securities Transactions Tax Mitigate Excess Volatility? Some Evidence From the Literature," CoFE Discussion Papers 04/06, University of Konstanz, Center of Finance and Econometrics (CoFE).
    15. repec:zbw:bofism:2012_047 is not listed on IDEAS
    16. Wayne E. Ferson & Andrea Heuson & Tie Su, 2005. "Weak-Form and Semi-Strong-Form Stock Return Predictability Revisited," Management Science, INFORMS, vol. 51(10), pages 1582-1592, October.
    17. Lucy Ackert & William Hunter, 2001. "An Empirical Examination of the Price-Dividend Relation with Dividend Management," Journal of Financial Services Research, Springer;Western Finance Association, vol. 19(2), pages 115-129, April.
    18. Wyart, Matthieu & Bouchaud, Jean-Philippe, 2007. "Self-referential behaviour, overreaction and conventions in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 63(1), pages 1-24, May.
    19. Bruce N. Lehmann, 1991. "Asset Pricing and Intrinsic Values: A Review Essay," NBER Working Papers 3873, National Bureau of Economic Research, Inc.
    20. Tro Kortian, 1995. "Modern Approaches to Asset Price Formation: A Survey of Recent Theoretical Literature," RBA Research Discussion Papers rdp9501, Reserve Bank of Australia.
    21. Coleman, Les, 2014. "Why finance theory fails to survive contact with the real world: A fund manager perspective," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 25(3), pages 226-236.

    More about this item

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:prs:recofi:ecofi_0987-3368_2004_num_74_1_5039. 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: Equipe PERSEE (email available below). General contact details of provider: https://www.persee.fr/collection/ecofi .

    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.