Advanced Search
MyIDEAS: Login to save this article or follow this journal

Patterns in stock market movements tested as random number generators

Contents:

Author Info

  • Doyle, John R.
  • Chen, Catherine H.
Registered author(s):

    Abstract

    This paper shows that tests of Random Number Generators (RNGs) may be used to test the Efficient Market Hypothesis (EMH). It uses the Overlapping Serial Test (OST), a standard test in RNG research, to detect anomalous patterns in the distribution of sequences of stock market movements up and down. Our results show that most stock markets exhibit idiosyncratic recurrent patterns, contrary to the efficient market hypothesis; also that OST detects a different kind of non-randomness to standard econometric long- and short-memory tests. Exposure of these anomalies should contribute to making markets more efficient.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.sciencedirect.com/science/article/pii/S0377221712009101
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 227 (2013)
    Issue (Month): 1 ()
    Pages: 122-132

    as in new window
    Handle: RePEc:eee:ejores:v:227:y:2013:i:1:p:122-132

    Contact details of provider:
    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Stock market time series; Financial data mining; Forecasting; Finance; Overlapping serial test;

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Andrew W. Lo & A. Craig MacKinlay, 1988. "The Size and Power of the Variance Ratio Test in Finite Samples: A Monte Carlo Investigation," NBER Technical Working Papers 0066, National Bureau of Economic Research, Inc.
    2. David Hirshleifer & Tyler Shumway, 2003. "Good Day Sunshine: Stock Returns and the Weather," Journal of Finance, American Finance Association, vol. 58(3), pages 1009-1032, 06.
    3. Wang, Ju-Jie & Wang, Jian-Zhou & Zhang, Zhe-George & Guo, Shu-Po, 2012. "Stock index forecasting based on a hybrid model," Omega, Elsevier, vol. 40(6), pages 758-766.
    4. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    5. Canal, Luisa, 2005. "A normal approximation for the chi-square distribution," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 803-808, April.
    6. Nicolau, Juan L., 2012. "The effect of winning the 2010 FIFA World Cup on the tourism market value: The Spanish case," Omega, Elsevier, vol. 40(5), pages 503-510.
    7. Loughin, Thomas M., 2004. "A systematic comparison of methods for combining p-values from independent tests," Computational Statistics & Data Analysis, Elsevier, vol. 47(3), pages 467-485, October.
    8. Doyle, John R. & Chen, Catherine Huirong, 2009. "The wandering weekday effect in major stock markets," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1388-1399, August.
    9. Lo, Andrew W. (Andrew Wen-Chuan), 1989. "Long-term memory in stock market prices," Working papers 3014-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    10. Sun, Edward W. & Meinl, Thomas, 2012. "A new wavelet-based denoising algorithm for high-frequency financial data mining," European Journal of Operational Research, Elsevier, vol. 217(3), pages 589-599.
    11. Tabak, Benjamin M. & Lima, Eduardo J.A., 2009. "Market efficiency of Brazilian exchange rate: Evidence from variance ratio statistics and technical trading rules," European Journal of Operational Research, Elsevier, vol. 194(3), pages 814-820, May.
    12. Hui, Tak-Kee, 2005. "Day-of-the-week effects in US and Asia-Pacific stock markets during the Asian financial crisis: a non-parametric approach," Omega, Elsevier, vol. 33(3), pages 277-282, June.
    13. George Marsaglia & Wai Wan Tsang, . "Some Difficult-to-pass Tests of Randomness," Journal of Statistical Software, American Statistical Association, vol. 7(i03).
    14. Burton G. Malkiel, 2005. "Reflections on the Efficient Market Hypothesis: 30 Years Later," The Financial Review, Eastern Finance Association, vol. 40(1), pages 1-9, 02.
    15. Bellini, Fabio & Figa-Talamanca, Gianna, 2005. "Runs tests for assessing volatility forecastability in financial time series," European Journal of Operational Research, Elsevier, vol. 163(1), pages 102-114, May.
    16. G. William Schwert, 2002. "Anomalies and Market Efficiency," NBER Working Papers 9277, National Bureau of Economic Research, Inc.
    17. Hui, T-K & Kwan, EK, 1994. "International portfolio diversification: A factor analysis approach," Omega, Elsevier, vol. 22(3), pages 263-267, May.
    18. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    19. Lim, Kian-Ping, 2007. "Ranking market efficiency for stock markets: A nonlinear perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 445-454.
    20. Ziemba, William T., 1994. "World wide security market regularities," European Journal of Operational Research, Elsevier, vol. 74(2), pages 198-229, April.
    21. Rozeff, Michael S. & Kinney, William Jr., 1976. "Capital market seasonality: The case of stock returns," Journal of Financial Economics, Elsevier, vol. 3(4), pages 379-402, October.
    22. Kim, Jae H. & Shamsuddin, Abul, 2008. "Are Asian stock markets efficient? Evidence from new multiple variance ratio tests," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 518-532, June.
    23. Alex Edmans & Diego García & Øyvind Norli, 2007. "Sports Sentiment and Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1967-1998, 08.
    24. Doyle, John R. & Chen, Catherine Huirong, 2012. "A multidimensional classification of market anomalies: Evidence from 76 price indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1237-1257.
    25. Donald W.K. Andrews, 1988. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Cowles Foundation Discussion Papers 877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
    26. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-73, April.
    27. Sermpinis, Georgios & Theofilatos, Konstantinos & Karathanasopoulos, Andreas & Georgopoulos, Efstratios F. & Dunis, Christian, 2013. "Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization," European Journal of Operational Research, Elsevier, vol. 225(3), pages 528-540.
    28. Yang, Jian & Cabrera, Juan & Wang, Tao, 2010. "Nonlinearity, data-snooping, and stock index ETF return predictability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 498-507, January.
    29. George Marsaglia, . "Monkeying with the Goodness-of-Fit Test," Journal of Statistical Software, American Statistical Association, vol. 14(i13).
    30. Christopher T. Ball, 2012. "Not all streaks are the same: Individual differences in risk preferences during runs of gains and losses," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(4), pages 452-461, July.
    31. Giraitis, Liudas & Kokoszka, Piotr & Leipus, Remigijus & Teyssiere, Gilles, 2003. "Rescaled variance and related tests for long memory in volatility and levels," Journal of Econometrics, Elsevier, vol. 112(2), pages 265-294, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:227:y:2013:i:1:p:122-132. 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: (Zhang, Lei).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.