IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v227y2013i1p122-132.html
   My bibliography  Save this article

Patterns in stock market movements tested as random number generators

Author

Listed:
  • Doyle, John R.
  • Chen, Catherine H.

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.

Suggested Citation

  • Doyle, John R. & Chen, Catherine H., 2013. "Patterns in stock market movements tested as random number generators," European Journal of Operational Research, Elsevier, vol. 227(1), pages 122-132.
  • Handle: RePEc:eee:ejores:v:227:y:2013:i:1:p:122-132
    DOI: 10.1016/j.ejor.2012.11.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221712009101
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2012.11.057?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Ziemba, William T., 1994. "World wide security market regularities," European Journal of Operational Research, Elsevier, vol. 74(2), pages 198-229, April.
    2. 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.
    3. 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.
    4. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    5. 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, June.
    6. 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.
    7. Lo, Andrew W. & MacKinlay, A. Craig, 1989. "The size and power of the variance ratio test in finite samples : A Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 40(2), pages 203-238, February.
    8. 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.
    9. 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.
    10. 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 246-273, April.
    11. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    12. Schwert, G. William, 2003. "Anomalies and market efficiency," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 15, pages 939-974, Elsevier.
    13. 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.
    14. Marsaglia, George & Tsang, Wai Wan, 2002. "Some Difficult-to-pass Tests of Randomness," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i03).
    15. 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.
    16. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    17. John Board & Charles Sutcliffe & William T. Ziemba, 2003. "Applying Operations Research Techniques to Financial Markets," Interfaces, INFORMS, vol. 33(2), pages 12-24, April.
    18. 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.
    19. Lim, Kian-Ping & Brooks, Robert D., 2009. "Price limits and stock market efficiency: Evidence from rolling bicorrelation test statistic," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1271-1276.
    20. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2003. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, edition 1, volume 1, number 1.
    21. 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, February.
    22. John M. Mulvey, 1994. "Introduction to the Special Issue on Finance," Interfaces, INFORMS, vol. 24(3), pages 1-2, June.
    23. 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.
    24. GIRAITIS, Liudas & KOKOSZKA, Piotr & LEIPUS, Remigijus & TEYSSIÈRE, Gilles, 2003. "Rescaled variance and related tests for long memory in volatility and levels," LIDAM Reprints CORE 1594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Alex Edmans & Diego García & Øyvind Norli, 2007. "Sports Sentiment and Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1967-1998, August.
    26. repec:cup:judgdm:v:7:y:2012:i:4:p:452-461 is not listed on IDEAS
    27. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    28. 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.
    29. 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.
    30. 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.
    31. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2003. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, edition 1, volume 1, number 2.
    32. 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.
    33. Marsaglia, George, 2005. "Monkeying with the Goodness-of-Fit Test," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i13).
    34. Hui, T-K & Kwan, EK, 1994. "International portfolio diversification: A factor analysis approach," Omega, Elsevier, vol. 22(3), pages 263-267, May.
    35. Moreno, David & Olmeda, Ignacio, 2007. "Is the predictability of emerging and developed stock markets really exploitable?," European Journal of Operational Research, Elsevier, vol. 182(1), pages 436-454, October.
    36. Canal, Luisa, 2005. "A normal approximation for the chi-square distribution," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 803-808, April.
    37. 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.
    38. 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.
    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. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    2. Ma, T. & Fraser-Mackenzie, P.A.F. & Sung, M. & Kansara, A.P. & Johnson, J.E.V., 2022. "Are the least successful traders those most likely to exit the market? A survival analysis contribution to the efficient market debate," European Journal of Operational Research, Elsevier, vol. 299(1), pages 330-345.
    3. Green, Lawrence & Sung, Ming-Chien & Ma, Tiejun & Johnson, Johnnie E. V., 2019. "To what extent can new web-based technology improve forecasts? Assessing the economic value of information derived from Virtual Globes and its rate of diffusion in a financial market," European Journal of Operational Research, Elsevier, vol. 278(1), pages 226-239.
    4. Michael A. Noakes & Kanshukan Rajaratnam, 2016. "Testing market efficiency on the Johannesburg Stock Exchange using the overlapping serial test," Annals of Operations Research, Springer, vol. 243(1), pages 273-300, August.
    5. Ben Moews, 2023. "On random number generators and practical market efficiency," Papers 2305.17419, arXiv.org, revised Jul 2023.
    6. Li-Chen Cheng & Yu-Hsiang Huang & Ming-Hua Hsieh & Mu-En Wu, 2021. "A Novel Trading Strategy Framework Based on Reinforcement Deep Learning for Financial Market Predictions," Mathematics, MDPI, vol. 9(23), pages 1-16, November.

    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. 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.
    2. Mostafa Saidur Rahim Khan & Naheed Rabbani, 2019. "Market Conditions and Calendar Anomalies in Japanese Stock Returns," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(2), pages 187-209, June.
    3. Cajueiro, Daniel O. & Tabak, Benjamin M., 2006. "Testing for predictability in equity returns for European transition markets," Economic Systems, Elsevier, vol. 30(1), pages 56-78, March.
    4. Assaf, Ata, 2015. "Long memory and level shifts in REITs returns and volatility," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 172-182.
    5. A. Sensoy & Benjamin M. Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.
    6. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    7. Leković Miljan, 2018. "Evidence for and Against the Validity of Efficient Market Hypothesis," Economic Themes, Sciendo, vol. 56(3), pages 369-387, September.
    8. Bwo-Nung Huang & Chin Yang, 1995. "The fractal structure in multinational stock returns," Applied Economics Letters, Taylor & Francis Journals, vol. 2(3), pages 67-71.
    9. Francis Ahking, 2010. "Non-parametric tests of real exchange rates in the post-Bretton Woods era," Empirical Economics, Springer, vol. 39(2), pages 439-456, October.
    10. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    11. Wagner, Moritz & Lee, John Byong-Tek & Margaritis, Dimitris, 2022. "Mutual fund flows and seasonalities in stock returns," Journal of Banking & Finance, Elsevier, vol. 144(C).
    12. Charles, Amélie & Darné, Olivier, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Energy Policy, Elsevier, vol. 37(11), pages 4267-4272, November.
    13. 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.
    14. Guglielmo Caporale & Luis Gil-Alana, 2013. "Long memory in US real output per capita," Empirical Economics, Springer, vol. 44(2), pages 591-611, April.
    15. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability Of Technical Trading Rules In Us Futures Markets: A Data Snooping Free Test," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19011, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    16. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Economic Modelling, Elsevier, vol. 28(1-2), pages 27-35, January.
    17. Feng, Zhen-Hua & Zou, Le-Le & Wei, Yi-Ming, 2011. "Carbon price volatility: Evidence from EU ETS," Applied Energy, Elsevier, vol. 88(3), pages 590-598, March.
    18. Assaf, Ata, 2016. "MENA stock market volatility persistence: Evidence before and after the financial crisis of 2008," Research in International Business and Finance, Elsevier, vol. 36(C), pages 222-240.
    19. Chaker Aloui & Duc Khuong Nguyen, 2014. "On the detection of extreme movements and persistent behaviour in Mediterranean stock markets: a wavelet-based approach," Applied Economics, Taylor & Francis Journals, vol. 46(22), pages 2611-2622, August.
    20. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "Adaptive Markets Hypothesis for Islamic Stock Portfolios: Evidence from Dow Jones Size and Sector-Indices," Post-Print hal-01526483, HAL.

    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:ejores:v:227:y:2013:i:1:p:122-132. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.