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Tests of the Random Walk Hypothesis Against a Price-Trend Hypothesis

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  • Taylor, Stephen J.

Abstract

Forecasts of financial prices, calculated from the present and past values, are never substantially more accurate than the prediction that future prices will equal the most recently observed price. This conclusion has been summarized by two hypotheses. First, the random walk hypothesis, states that daily returns are uncorrelated. Few people believe that this is exactly correct; indeed, the hypothesis has been refuted both for small stock markets [13] and for American commodity futures markets [3]. Second, the weak-form efficient market hypothesis, as defined by Jensen [15], states that investors cannot make profits from any correlation between returns, after deducting all the costs of trading and adjusting for risk. Strict efficiency, is a special case that occurs when prices fully reflect all information available in the past prices [7], [8].

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  • Taylor, Stephen J., 1982. "Tests of the Random Walk Hypothesis Against a Price-Trend Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 17(1), pages 37-61, March.
  • Handle: RePEc:cup:jfinqa:v:17:y:1982:i:01:p:37-61_01
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    Citations

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    Cited by:

    1. L. Ingber, 1996. "Canonical momenta indicators of financial markets and neocortical EEG," Lester Ingber Papers 96cm, Lester Ingber.
    2. Ingber, Lester, 2000. "High-resolution path-integral development of financial options," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 529-558.
    3. L. Ingber & J.K. Wilson, 2000. "Statistical mechanics of financial markets: Exponential modifications to Black-Scholes," Lester Ingber Papers 00fm, Lester Ingber.
    4. Chun, Young Hak, 1997. "Rank-based selection strategies for the random walk process," European Journal of Operational Research, Elsevier, vol. 96(2), pages 417-427, January.
    5. Markku Lanne & Mika Meitz & Pentti Saikkonen, 2012. "Testing for Predictability in a Noninvertible ARMA Model," Koç University-TUSIAD Economic Research Forum Working Papers 1225, Koc University-TUSIAD Economic Research Forum.
    6. L. Ingber & M.F. Wehner & G.M. Jabbour & T.M. Barnhill, 1991. "Application of statistical mechanics methodology to term-structure bond-pricing models," Lester Ingber Papers 91as, Lester Ingber.
    7. Lester Ingber & Radu Paul Mondescu, 2000. "Optimization of Trading Physics Models of Markets," Papers physics/0007075, arXiv.org.
    8. Wilson, Christine A. & Featherstone, Allen M. & Kastens, Terry L., 2001. "Threshold Effects In Food And Agribusiness Stock Price Markets," 2001 Annual meeting, August 5-8, Chicago, IL 20591, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Nyholm, Juho, 2017. "Residual-based diagnostic tests for noninvertible ARMA models," MPRA Paper 81033, University Library of Munich, Germany.
    10. Ivan Contreras & J. Ignacio Hidalgo & Laura Nuñez, 2018. "Exploring the influence of industries and randomness in stock prices," Empirical Economics, Springer, vol. 55(2), pages 713-729, September.
    11. L. Ingber & R.P. Mondescu, 2003. "Automated internet trading based on optimized physics models of markets," Lester Ingber Papers 03ai, Lester Ingber.

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