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Valuation Ratios and Stock Price Predictability in South Africa: Is it there?

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Author Info

  • Rangan Gupta

    ()
    (Department of Economics, University of Pretoria)

  • Mampho P. Modise

    ()
    (Department of Economics, University of Pretoria and South African Treasury, Pretoria, South Africa)

Abstract

Using monthly South African data for 1990:01-2009:10, this paper, to the best of our knowledge, is the first to examine the predictability of real stock prices based on valuation ratios, namely, price-dividend and price-earnings ratios. We cannot detect either short-horizon or long-horizon predictability; that is, the hypothesis that the current value of a valuation ratio is uncorrelated with future stock price changes cannot be rejected at both short- and long- horizons based on bootstrapped critical values constructed from linear representations of the data. We find, via Monte Carlo simulations, that the power to detect predictability in finite samples tends to decrease at long horizons in a linear framework. Though Monte Carlo simulations applied to exponential smooth-transition autoregressive (ESTAR) models of the price-dividend and price-earnings ratios, show increased power, the ability of the non-linear framework in explaining the pattern of stock price predictability in the data does not show any promise both at short- and long-horizons, just as in the linear predictive regressions.

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Bibliographic Info

Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 201016.

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Length: 10 pages
Date of creation: Jul 2010
Date of revision:
Handle: RePEc:pre:wpaper:201016

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Related research

Keywords: Predictive regression; Monte Carlo simulation; Nonlinear mean-reversion;

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Cited by:
  1. Gupta, Rangan & Modise, Mampho P., 2012. "South African stock return predictability in the context data mining: The role of financial variables and international stock returns," Economic Modelling, Elsevier, vol. 29(3), pages 908-916.

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