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Predicting Stock Returns Using a Variable Order Markov Tree Model

Author

Listed:
  • Shmilovici Armin

    (Ben-Gurion University of the Negev)

  • Ben-Gal Irad

    (Tel-Aviv University)

Abstract

The weak form of the Efficient Market Hypothesis (EMH) states that the current market price fully reflects the information of past prices and rules out predictions based on price data alone. In an efficient market, consistent prediction of the next outcome of a financial time series is problematic because there are no reoccurring patterns that can be used for a reliable prediction. This research offers an alternative test of the weak form of the EMH. It uses a universal prediction algorithm based on the Variable Order Markov tree model to identify re-occurring patterns in the data, constructs explanatory models, and predicts the next time-series outcome. Based on these predictions, it rejects the EMH for certain stock markets while accepting it for other markets. The weak form of the EMH is tested for four international stock exchanges: the German DAX index; the American Dow-Jones30 index; the Austrian ATX index and the Danish KFX index. The universal prediction algorithm is used with sliding windows of 50, 75, and 100 consecutive daily returns for periods of up to 12 trading years. Statistically significant predictions are detected for 17% to 81% of the ATX, KFX and DJ30 stock series for about 3% to 30% of the trading days. A summary prediction analysis indicates that for a confidence level of 99% the more volatile German (DAX) and American (DJ30) markets are indeed efficient. The algorithm detects periods of potential market inefficiency in the ATX and KFX markets that may be exploited for obtaining excess returns.

Suggested Citation

  • Shmilovici Armin & Ben-Gal Irad, 2012. "Predicting Stock Returns Using a Variable Order Markov Tree Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(5), pages 1-33, December.
  • Handle: RePEc:bpj:sndecm:v:16:y:2012:i:5:p:1-33:n:1
    DOI: 10.1515/1558-3708.1648
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    References listed on IDEAS

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    1. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    2. Armin Shmilovici & Yoav Kahiri & Irad Ben-Gal & Shmuel Hauser, 2009. "Measuring the Efficiency of the Intraday Forex Market with a Universal Data Compression Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 33(2), pages 131-154, March.
    3. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    4. Ching-Wei Tan, 1999. "Estimating the Complexity Function of Financial Time Series: An Estimation Based on Predictive Stochastic Complexity," Computing in Economics and Finance 1999 1143, Society for Computational Economics.
    5. Neal Maroney & Aris Protopapadakis, 2002. "The Book-to-Market and Size Effects in a General Asset Pricing Model: Evidence from Seven National Markets," Review of Finance, European Finance Association, vol. 6(2), pages 189-221.
    6. repec:pri:cepsud:91malkiel is not listed on IDEAS
    7. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    8. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    9. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    10. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    11. Henryk Gurgul & Paweł Majdosz & Roland Mestel, 2007. "Price–volume relations of DAX companies," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 21(3), pages 353-379, September.
    12. Manuel Dominguez & Ignacio Lobato, 2003. "Testing the Martingale Difference Hypothesis," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 351-377.
    13. Thomas M. Cover, 1991. "Universal Portfolios," Mathematical Finance, Wiley Blackwell, vol. 1(1), pages 1-29, January.
    14. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    15. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
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