IDEAS home Printed from https://ideas.repec.org/a/taf/eurjfi/v7y2001i1p1-21.html
   My bibliography  Save this article

Empirical distributions of stock returns: European securities markets, 1990-95

Author

Listed:
  • Felipe Aparicio
  • Javier Estrada

Abstract

The assumption that daily stock returns are normally distributed has long been disputed by the data. In this article the normality assumption is tested (and clearly rejected) using time series of daily stock returns for 13 European securities markets. More importantly, four alternative specifications are fitted to the data, overall support is found for the scaled- t distribution (and partial support for a mixture of two Normal distributions), and the magnitude of the error that stems from predicting returns by using the Normal distribution is quantified. Data also show that normality may be a plausible assumption for monthly (but not for daily) stock returns.

Suggested Citation

  • Felipe Aparicio & Javier Estrada, 2001. "Empirical distributions of stock returns: European securities markets, 1990-95," The European Journal of Finance, Taylor & Francis Journals, vol. 7(1), pages 1-21.
    • Handle: RePEc:taf:eurjfi:v:7:y:2001:i:1:p:1-21
    DOI: 10.1080/13518470121786
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/13518470121786
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13518470121786?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kon, Stanley J, 1984. "Models of Stock Returns-A Comparison," Journal of Finance, American Finance Association, vol. 39(1), pages 147-165, March.
    2. S. James Press, 1967. "A Compound Events Model for Security Prices," The Journal of Business, University of Chicago Press, vol. 40, pages 317-317.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Blattberg, Robert C & Gonedes, Nicholas J, 1974. "A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices," The Journal of Business, University of Chicago Press, vol. 47(2), pages 244-280, April.
    5. Praetz, Peter D, 1972. "The Distribution of Share Price Changes," The Journal of Business, University of Chicago Press, vol. 45(1), pages 49-55, January.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Chamberlain, Gary, 1983. "A characterization of the distributions that imply mean--Variance utility functions," Journal of Economic Theory, Elsevier, vol. 29(1), pages 185-201, February.
    8. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    9. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    10. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    11. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    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. Ricardo Pereira, 2007. "The Cost Of Equity Of Portuguese Public Firms: A Downside Risk Approach," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(1), pages 7-25.
    2. Landsman, Zinoviy, 2010. "On the Tail Mean-Variance optimal portfolio selection," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 547-553, June.
    3. Keith Jefferis & Graham Smith, 2004. "Capitalisation And Weak‐Form Efficiency In The Jse Securities Exchange," South African Journal of Economics, Economic Society of South Africa, vol. 72(4), pages 684-707, September.
    4. Graham Smith, 2007. "Random walks in Middle Eastern stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 17(7), pages 587-596.
    5. Mesakh Prihanto Surya Putra & Apriani Dorkas Rambu Atahau & Robiyanto Robiyanto, 2018. "Cross–asset class portfolio between gold and stocks in Indonesia," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 10(1), pages 69-81, April.
    6. Houda Hafsa & Dorra Hmaied, 2012. "Are Downside Higher Order Co-Moments Priced? : Evidence From The French Market," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 6(1), pages 65-81.
    7. Stella Kanellopoulou & Epaminondas Panas, 2008. "Empirical distributions of stock returns: Paris stock market, 1980-2003," Applied Financial Economics, Taylor & Francis Journals, vol. 18(16), pages 1289-1302.
    8. Georges Hübner & Thomas Lejeune, 2015. "Portfolio choice and investor preferences : A semi-parametric approach based on risk horizon," Working Paper Research 289, National Bank of Belgium.
    9. Feng Zhang & Xi Wang & Honggao Cao, 2021. "Turnover-Adjusted Information Ratio," Papers 2105.10306, arXiv.org.
    10. Robert Chirinko & Hisham Foad, 2006. "Noise vs. News in Equity Returns," CESifo Working Paper Series 1812, CESifo.
    11. Hübner, Georges & Lejeune, Thomas, 2021. "Mental accounts with horizon and asymmetry preferences," Economic Modelling, Elsevier, vol. 103(C).
    12. Massing, Till & Ramos, Arturo, 2021. "Student’s t mixture models for stock indices. A comparative study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    13. Yugu Xiao & Emiliano A. Valdez, 2015. "A Black-Litterman asset allocation model under Elliptical distributions," Quantitative Finance, Taylor & Francis Journals, vol. 15(3), pages 509-519, March.
    14. Konstantinos Tolikas & Athanasios Koulakiotis & Richard A. Brown, 2007. "Extreme Risk and Value-at-Risk in the German Stock Market," The European Journal of Finance, Taylor & Francis Journals, vol. 13(4), pages 373-395.

    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. Eom, Cheoljun & Kaizoji, Taisei & Scalas, Enrico, 2019. "Fat tails in financial return distributions revisited: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    2. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    3. Stavros Degiannakis & Alexandra Livada & Epaminondas Panas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," Applied Economics, Taylor & Francis Journals, vol. 40(23), pages 3051-3067.
    4. López Martín, María del Mar & García, Catalina García & García Pérez, José, 2012. "Treatment of kurtosis in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2032-2045.
    5. Wai Mun Fong, 1997. "Robust beta estimation: Some empirical evidence," Review of Financial Economics, John Wiley & Sons, vol. 6(2), pages 167-186.
    6. Bollerslev, Tim & Engle, Robert F. & Nelson, Daniel B., 1986. "Arch models," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 49, pages 2959-3038, Elsevier.
    7. Fong, Wai Mun, 1997. "Robust beta estimation: Some empirical evidence," Review of Financial Economics, Elsevier, vol. 6(2), pages 167-186.
    8. Koundouri, Phoebe & Kourogenis, Nikolaos & Pittis, Nikitas & Samartzis, Panagiotis, 2015. "Factor Models as "Explanatory UniÖers" versus "Explanatory Ideals" of Empirical Regularities of Stock Returns," MPRA Paper 122254, University Library of Munich, Germany.
    9. Sam Howison & David Lamper, 2001. "Trading volume in models of financial derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 8(2), pages 119-135.
    10. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis, 2016. "Statistical Modeling Of Stock Returns: Explanatory Or Descriptive? A Historical Survey With Some Methodological Reflections," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 149-164, February.
    11. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    12. Manuel Vega & José L. Alvarez, "undated". "Tipos de cambio flexibles y volatilidad: Las regularidades empíricas de las observaciones diarias," Studies on the Spanish Economy 116, FEDEA.
    13. Christian Gabriel & Christian Lau, 2014. "On the distribution of government bond returns: evidence from the EMU," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(2), pages 181-203, May.
    14. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis, "undated". "Statistical Modeling of Stock Returns: Explanatory or Descriptive? A Historical Survey with Some Methodological Reflections," DEOS Working Papers 1331, Athens University of Economics and Business.
    16. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    17. Richard Harris & C. Coskun Kucukozmen, 2001. "The empirical distribution of stock returns: evidence from an emerging European market," Applied Economics Letters, Taylor & Francis Journals, vol. 8(6), pages 367-371.
    18. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," PIER Working Paper Archive 05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    19. Adcock, C J & Meade, N, 2017. "Using parametric classification trees for model selection with applications to financial risk management," European Journal of Operational Research, Elsevier, vol. 259(2), pages 746-765.
    20. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.

    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:taf:eurjfi:v:7:y:2001:i:1:p:1-21. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/REJF20 .

    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.