IDEAS home Printed from https://ideas.repec.org/p/hhs/hastef/0191.html
   My bibliography  Save this paper

Trading Volume and Autocorrelation: Empirical Evidence from the Stockholm Stock Exchange

Author

Listed:
  • Säfvenblad, Patrik

    (Dept. of Finance, Stockholm School of Economics)

Abstract

This paper provides an extensive empirical investigation into the sources of index return autocorrelation, focusing on the relation between autocorrelation in individual stock returns and autocorrelation in index returns. The study uses daily data from the Stockholm Stock Exchange over the period 1980-1995 and reports three main empirical findings. Daily Swedish stock index returns exhibit strong, and consistently positive, first order autocorrelation throughout the sample period. Positive autocorrelation is observed for return frequencies between 1 day and 3 months. The most liquid stocks exhibit strong positive return autocorrelation. Less liquid stocks exhibit weak or negative return autocorrelation. Autocorrelation is asymmetric, high after days of above average performance of the stock market, low after days of below average performance. When compared to the other days of the week, both index returns and individual stock returns exhibit the strongest autocorrelation following on Friday returns. The transaction cost hypothesis was tested using the Swedish stock market transaction tax. Results indicate lower precision of stock prices during the transaction tax period, but no direct effect on return autocorrelation. The paper concludes that at least three sources contribute to observed return autocorrelation. For daily and short-term returns, profit taking and nonsynchronous trading are the probable causes of observed autocorrelation. For monthly and longer term returns, time-varying expected returns best describe the empirical results.

Suggested Citation

  • Säfvenblad, Patrik, 1997. "Trading Volume and Autocorrelation: Empirical Evidence from the Stockholm Stock Exchange," SSE/EFI Working Paper Series in Economics and Finance 191, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0191
    as

    Download full text from publisher

    File URL: http://swopec.hhs.se/hastef/papers/hastef0191.pdf.zip
    File Function: Complete Rendering
    Download Restriction: no

    File URL: http://swopec.hhs.se/hastef/papers/hastef0191.pdf
    File Function: Complete Rendering
    Download Restriction: no

    File URL: http://swopec.hhs.se/hastef/papers/hastef0191.ps.zip
    File Function: Complete Rendering
    Download Restriction: no

    File URL: http://swopec.hhs.se/hastef/papers/hastef0191.ps
    File Function: Complete Rendering
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    2. Boudoukh, Jacob & Richardson, Matthew P & Whitelaw, Robert F, 1994. "A Tale of Three Schools: Insights on Autocorrelations of Short-Horizon Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 7(3), pages 539-573.
    3. Atchison, Michael D & Butler, Kirt C & Simonds, Richard R, 1987. "Nonsynchronous Security Trading and Market Index Autocorrelation," Journal of Finance, American Finance Association, vol. 42(1), pages 111-118, March.
    4. Berglund, Tom & Liljeblom, Eva, 1988. " Market Serial Correlation on a Small Security Market: A Note," Journal of Finance, American Finance Association, vol. 43(5), pages 1265-1274, December.
    5. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    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. Shah Saeed Hassan Chowdhury & M. Arifur Rahman & M. Shibley Sadique, 2017. "Stock return autocorrelation, day of the week and volatility," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 16(2), pages 218-238, May.

    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. Säfvenblad, Patrik, 1997. "Learning the True Index Level: Index Return Autocorrelation in an REE Auction Market," SSE/EFI Working Paper Series in Economics and Finance 190, Stockholm School of Economics.
    2. Safvenblad, Patrik, 2000. "Trading volume and autocorrelation: Empirical evidence from the Stockholm Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 24(8), pages 1275-1287, August.
    3. Anderson, Robert M. & Eom, Kyong Shik & Hahn, Sang Buhm & Park, Jong-Ho, 2007. "Stock Return Autocorrelation is Not Spurious," Department of Economics, Working Paper Series qt2k7414sv, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    4. Baltussen, Guido & van Bekkum, Sjoerd & Da, Zhi, 2019. "Indexing and stock market serial dependence around the world," Journal of Financial Economics, Elsevier, vol. 132(1), pages 26-48.
    5. Sias, Richard W. & Starks, Laura T., 1997. "Return autocorrelation and institutional investors," Journal of Financial Economics, Elsevier, vol. 46(1), pages 103-131, October.
    6. Shah Saeed Hassan Chowdhury & M. Arifur Rahman & M. Shibley Sadique, 2017. "Stock return autocorrelation, day of the week and volatility," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 16(2), pages 218-238, May.
    7. Chang, Sanders S. & Wang, F. Albert, 2015. "Adverse selection and the presence of informed trading," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 19-33.
    8. Rodrigo Aranda & Patricio Jaramillo, 2008. "Nonlinear Dynamic in the Chilean Stock Market: Evidence from Returns and Trading Volume," Working Papers Central Bank of Chile 463, Central Bank of Chile.
    9. Elaut, Gert & Frömmel, Michael & Lampaert, Kevin, 2018. "Intraday momentum in FX markets: Disentangling informed trading from liquidity provision," Journal of Financial Markets, Elsevier, vol. 37(C), pages 35-51.
    10. Menkhoff, Lukas & Schmeling, Maik, 2010. "Trader see, trader do: How do (small) FX traders react to large counterparties' trades?," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1283-1302, November.
    11. Nicholas Taylor, 2011. "Time-varying price discovery in fragmented markets," Applied Financial Economics, Taylor & Francis Journals, vol. 21(10), pages 717-734.
    12. G.S Morgan & Peter N. Smith & S.H. Thomas, "undated". "Portfolio return autocorrelation and non-synchronous trading in UK equities," Discussion Papers 00/46, Department of Economics, University of York.
    13. Koutmos, Gregory, 1998. "Asymmetries in the Conditional Mean and the Conditional Variance: Evidence From Nine Stock Markets," Journal of Economics and Business, Elsevier, vol. 50(3), pages 277-290, May.
    14. Vinay Patel, 2015. "Price Discovery in US and Australian Stock and Options Markets," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 27, July-Dece.
    15. Robert A. Weigand, 1996. "Trading volume and firm size: A test of the information spillover hypothesis," Review of Financial Economics, John Wiley & Sons, vol. 5(1), pages 47-58, December.
    16. John M.R. Chalmers & Roger M. Edelen & Gregory B. Kadlec, "undated". "The wildcard option in transaction mutual-fund shares," Rodney L. White Center for Financial Research Working Papers 25-99, Wharton School Rodney L. White Center for Financial Research.
    17. Peress, Joel & Schmidt, Daniel, 2021. "Noise traders incarnate: Describing a realistic noise trading process," Journal of Financial Markets, Elsevier, vol. 54(C).
    18. He, Hua & Wang, Jiang, 1995. "Differential Information and Dynamic Behavior of Stock Trading Volume," Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 919-972.
    19. Masahiro Watanabe, 2003. "A Model of Stochastic Liquidity," Yale School of Management Working Papers ysm385, Yale School of Management.
    20. Lim, Kian-Ping & Kim, Jae H., 2011. "Trade openness and the informational efficiency of emerging stock markets," Economic Modelling, Elsevier, vol. 28(5), pages 2228-2238, September.

    More about this item

    Keywords

    Return autocorrelation; Stockholm Stock Exchange; trading volume; non-synchronous trading; feedback trading; time-varying risk premia;
    All these keywords.

    JEL classification:

    • 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:hhs:hastef:0191. 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: Helena Lundin (email available below). General contact details of provider: https://edirc.repec.org/data/erhhsse.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.