IDEAS home Printed from https://ideas.repec.org/p/aue/wpaper/1001.html
   My bibliography  Save this paper

Aggregational Gaussianity And Barely Infinite Variance In Crop Prices

Author

Listed:
  • Antonios Antypas

    (Department of Banking and Financial Management, University of Piraeus)

  • Phoebe Koundouri

    (Dept. of International and European Economic Studies, Athens University of Economics and Business)

  • Nikolaos Kourogenis

    (Department of Banking and Financial Management, University of Piraeus.)

Abstract

This paper aims at reconciling two apparently contradictory empirical regularities of financial returns, namely the fact that the empirical distribution of returns tends to normality as the frequency of observation decreases (aggregational Gaussianity) combined with the fact that the conditional variance of high frequency returns seems to have a unit root, in which case the unconditional variance is infinite. We show that aggregational Gaussianity and infinite variance can coexist, provided that all the moments of the unconditional distribution whose order is less than two exist. The latter characterises the case of Integrated GARCH (IGARCH) processes. Finally, we discuss testing for aggregational Gaussianity under barely infinite varian

Suggested Citation

  • Antonios Antypas & Phoebe Koundouri & Nikolaos Kourogenis, 2010. "Aggregational Gaussianity And Barely Infinite Variance In Crop Prices," DEOS Working Papers 1001, Athens University of Economics and Business.
    • Handle: RePEc:aue:wpaper:1001
    as

    Download full text from publisher

    File URL: http://wpa.deos.aueb.gr/docs/CropsIGARCH2010_01_23.pdf
    File Function: First version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-927, July.
    2. 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.
    3. 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.
    4. Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(1), pages 17-39, February.
    5. Nikolaos Kourogenis & Nikitas Pittis, 2008. "Testing for a unit root under errors with just barely infinite variance," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 1066-1087, November.
    6. Nikolaos Kourogenis & Nikitas Pittis, 2011. "Mixing Conditions, Central Limit Theorems, and Invariance Principles: A Survey of the Literature with Some New Results on Heteroscedastic Sequences," Econometric Reviews, Taylor & Francis Journals, vol. 30(1), pages 88-108.
    7. Mandelbrot, Benoit B, 1972. "Correction of an Error in "The Variation of Certain Speculative Prices" (1963)," The Journal of Business, University of Chicago Press, vol. 45(4), pages 542-543, October.
    8. 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..
    9. Francq, Christian & Zakoïan, Jean-Michel, 2006. "Mixing Properties Of A General Class Of Garch(1,1) Models Without Moment Assumptions On The Observed Process," Econometric Theory, Cambridge University Press, vol. 22(5), pages 815-834, October.
    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. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis, 2012. "Statistical Modeling of Stock Returns: A Historical Survey with Methodological Reflections," DEOS Working Papers 1226, Athens University of Economics and Business.

    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. Antypas, Antonios & Koundouri, Phoebe & Kourogenis, Nikolaos, 2013. "Aggregational Gaussianity and barely infinite variance in financial returns," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 102-108.
    2. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis, 2012. "Statistical Modeling of Stock Returns: A Historical Survey with Methodological Reflections," DEOS Working Papers 1226, Athens University of Economics and Business.
    3. Koundouri, Phoebe & Kourogenis, Nikolaos & Pittis, Nikitas, 2012. "Statistical Modeling of Stock Returns: A Historical Survey with Some Methodological Reflections," MPRA Paper 122422, University Library of Munich, Germany.
    4. Fong, Wai Mun, 1997. "Robust beta estimation: Some empirical evidence," Review of Financial Economics, Elsevier, vol. 6(2), pages 167-186.
    5. 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.
    6. 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.
    7. 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.
    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. P. B. Solibakke, 2005. "Non-linear dependence and conditional heteroscedasticity in stock returns evidence from the norwegian thinly traded equity market," The European Journal of Finance, Taylor & Francis Journals, vol. 11(2), pages 111-136.
    10. McMillan, David G. & Speight, Alan E. H., 2001. "Non-ferrous metals price volatility: a component analysis," Resources Policy, Elsevier, vol. 27(3), pages 199-207, September.
    11. Kevin Fergusson & Eckhard Platen, 2006. "On the Distributional Characterization of Daily Log-Returns of a World Stock Index," Applied Mathematical Finance, Taylor & Francis Journals, vol. 13(1), pages 19-38.
    12. Bucsa, G. & Jovanovic, F. & Schinckus, C., 2011. "A unified model for price return distributions used in econophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3435-3443.
    13. Ole E. Barndorff-Nielsen & Neil Shephard, 2012. "Basics of Levy processes," Economics Papers 2012-W06, Economics Group, Nuffield College, University of Oxford.
    14. 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).
    15. Miguel A Fuentes & Austin Gerig & Javier Vicente, 2009. "Universal Behavior of Extreme Price Movements in Stock Markets," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-4, December.
    16. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034, Decembrie.
    17. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2016. "Factor Models of Stock Returns: GARCH Errors versus Time‐Varying Betas," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(5), pages 445-461, August.
    18. Muneer Shaik & S. Maheswaran, 2019. "Robust Volatility Estimation with and Without the Drift Parameter," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(1), pages 57-91, March.
    19. Henryk Gurgul & Roland Mestel & Tomasz Wojtowicz, 2007. "Distribution of volume on the American stock market," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 1, pages 143-163.
    20. Ghose, Devajyoti & Kroner, Kenneth F., 1995. "The relationship between GARCH and symmetric stable processes: Finding the source of fat tails in financial data," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 225-251, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:aue:wpaper:1001. 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: Ekaterini Glynou (email available below). General contact details of provider: https://edirc.repec.org/data/diauegr.html .

    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.