IDEAS home Printed from
   My bibliography  Save this article

The impact of stock spams on volatility


  • Taoufik Bouraoui


This article is dedicated to study the impact of stock spams through the analysis of the variations of volatility. Our sample contains 110 firms quoted on emerging market, namely the penny stock market. The results, based on event study methodology and Generalized Autoregressive Conditional Heteroscedastic (GARCH) modelling, show positive and significant changes in volatility; a widening of the variation (lowest price-highest price) was noticed following the consignment of messages by the spammers. The sending of stock spams affected the behaviour of investors, thus indicating that the spamming activity is a lucrative business.

Suggested Citation

  • Taoufik Bouraoui, 2011. "The impact of stock spams on volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 21(13), pages 969-977.
  • Handle: RePEc:taf:apfiec:v:21:y:2011:i:13:p:969-977 DOI: 10.1080/09603107.2011.562159

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

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

    Other versions of this item:

    References listed on IDEAS

    1. Koski, Jennifer Lynch, 1998. "Measurement Effects and the Variance of Returns after Stock Splits and Stock Dividends," Review of Financial Studies, Society for Financial Studies, vol. 11(1), pages 143-162.
    2. Pindyck, Robert S, 1984. "Risk, Inflation, and the Stock Market," American Economic Review, American Economic Association, vol. 74(3), pages 335-351, June.
    3. Hanke, Michael & Hauser, Florian, 2008. "On the effects of stock spam e-mails," Journal of Financial Markets, Elsevier, vol. 11(1), pages 57-83, February.
    4. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    5. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    6. Sandy Campart & Étienne Pfister, 2008. "Course technologique et valeur boursière. Une étude d'événements basée sur l'industrie pharmaceutique," Revue économique, Presses de Sciences-Po, vol. 59(2), pages 307-329.
    7. A. Craig MacKinlay, 1997. "Event Studies in Economics and Finance," Journal of Economic Literature, American Economic Association, vol. 35(1), pages 13-39, March.
    8. Giaccotto, Carmelo & Sfiridis, James M., 1996. "Hypothesis testing in event studies: The case of variance changes," Journal of Economics and Business, Elsevier, vol. 48(4), pages 349-370, October.
    9. Harris, Lawrence, 1987. "Transaction Data Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(02), pages 127-141, June.
    10. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    11. Jain, Prem C. & Joh, Gun-Ho, 1988. "The Dependence between Hourly Prices and Trading Volume," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(03), pages 269-283, September.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. ap Gwilym, O. & Kita, A. & Wang, Q., 2014. "Speculate against speculative demand," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 212-221.
    2. Taoufik Bouraoui, 2015. "The effect of reducing quantitative easing on emerging markets," Applied Economics, Taylor & Francis Journals, vol. 47(15), pages 1562-1573, March.

    More about this item


    stock spam; event studies; GARCH; volatility;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General


    Access and download statistics


    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:apfiec:v:21:y:2011:i:13:p:969-977. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.