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Are Stock Returns Predictable? A Test Using Markov Chains

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  • McQueen, Grant
  • Thorley, Steven
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    Abstract

    This paper uses a Markov chain model to test the random walk hypothesis of stock prices. Given a time series of returns, a Markov chain is defined by letting one state represent high returns and the other represent low returns. The random walk hypothesis restricts the transition probabilities of the Markov change to be equal irrespective of the prior years. Annual real returns are shown to exhibit significant nonrandom walk behavior in the sense that low (high) returns tend to follow runs of high (low) returns in the postwar period. Copyright 1991 by American Finance Association.

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    Bibliographic Info

    Article provided by American Finance Association in its journal Journal of Finance.

    Volume (Year): 46 (1991)
    Issue (Month): 1 (March)
    Pages: 239-63

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    Handle: RePEc:bla:jfinan:v:46:y:1991:i:1:p:239-63

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    Cited by:
    1. Chiang, Raymond & Liu, Peter & Okunev, John, 1995. "Modelling mean reversion of asset prices towards their fundamental value," Journal of Banking & Finance, Elsevier, vol. 19(8), pages 1327-1340, November.
    2. N. Vijayamohanan Pillai, 2004. "Causality and error correction in Markov chain: Inflation in India revisited," Centre for Development Studies, Trivendrum Working Papers 366, Centre for Development Studies, Trivendrum, India.
    3. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Miranda, José G.V. & García-Rubio, Raquel, 2013. "How fast do stock prices adjust to market efficiency? Evidence from a detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1631-1637.
    4. Tan, Baris & Yilmaz, Kamil, 2002. "Markov chain test for time dependence and homogeneity: An analytical and empirical evaluation," European Journal of Operational Research, Elsevier, vol. 137(3), pages 524-543, March.
    5. R. Chiang & Ian Davidson & John Okunev, 1996. "Some Further Theoretical and Empirical Implications Regarding the Relationship between Earnings, Dividends and Returns," Working Paper Series 60, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    6. Chen, Son-Nan & Jeon, Kisuk, 1998. "Mean reversion behavior of the returns on currency assets," International Review of Economics & Finance, Elsevier, vol. 7(2), pages 185-200.
    7. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
    8. Paul Zimmerman & John Yun & Christopher Taylor, 2013. "Edgeworth Price Cycles in Gasoline: Evidence from the United States," Review of Industrial Organization, Springer, vol. 42(3), pages 297-320, May.
    9. Emekter, Riza & Jirasakuldech, Benjamas & Snaith, Sean M., 2009. "Nonlinear dynamics in foreign exchange excess returns: Tests of asymmetry," Journal of Multinational Financial Management, Elsevier, vol. 19(3), pages 179-192, July.
    10. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Society for Computational Economics, vol. 40(3), pages 245-264, October.

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