IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v108y2010i1p101-103.html
   My bibliography  Save this article

Stock return predictability despite low autocorrelation

Author

Listed:
  • Amini, Shima
  • Hudson, Robert
  • Keasey, Kevin

Abstract

This paper shows that short horizon stock returns can be predicted to a much greater degree by past price movements than would be anticipated given their low autocorrelation. This raises doubts over the reliability of the autocorrelation statistic as a measure of stock market predictability.

Suggested Citation

  • Amini, Shima & Hudson, Robert & Keasey, Kevin, 2010. "Stock return predictability despite low autocorrelation," Economics Letters, Elsevier, vol. 108(1), pages 101-103, July.
  • Handle: RePEc:eee:ecolet:v:108:y:2010:i:1:p:101-103
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165-1765(10)00157-6
    Download Restriction: Full text for ScienceDirect subscribers only

    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. 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.
    2. Mazouz, Khelifa & Joseph, Nathan L. & Joulmer, Joulmer, 2009. "Stock price reaction following large one-day price changes: UK evidence," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1481-1493, August.
    3. Brown, Keith C. & Harlow, W. V. & Tinic, Seha M., 1988. "Risk aversion, uncertain information, and market efficiency," Journal of Financial Economics, Elsevier, vol. 22(2), pages 355-385, December.
    4. Park, Jinwoo, 1995. "A Market Microstructure Explanation for Predictable Variations in Stock Returns following Large Price Changes," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(02), pages 241-256, June.
    5. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    6. Atkins, Allen B. & Dyl, Edward A., 1990. "Price Reversals, Bid-Ask Spreads, and Market Efficiency," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(04), pages 535-547, December.
    7. Lasfer, M. Ameziane & Melnik, Arie & Thomas, Dylan C., 2003. "Short-term reaction of stock markets in stressful circumstances," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 1959-1977, October.
    8. Brown, Keith C. & Harlow, W. V. & Tinic, Seha M., 1993. "The Risk and Required Return of Common Stock following Major Price Innovations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(01), pages 101-116, March.
    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. repec:ebl:ecbull:eb-17-00217 is not listed on IDEAS
    2. Amini, Shima & Gebka, Bartosz & Hudson, Robert & Keasey, Kevin, 2013. "A review of the international literature on the short term predictability of stock prices conditional on large prior price changes: Microstructure, behavioral and risk related explanations," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 1-17.
    3. Xue, Wen-Jun & Zhang, Li-Wen, 2017. "Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models," Economic Modelling, Elsevier, vol. 60(C), pages 391-401.
    4. 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.
    5. Wen-Jun Xue & Li-Wen Zhang, 2016. "Stock Return Autocorrelations and Predictability in the Chinese Stock Market: Evidence from Threshold Quantile Autoregressive Models," Working Papers 1605, Florida International University, Department of Economics.

    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:eee:ecolet:v:108:y:2010:i:1:p:101-103. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.