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Maximal predictability under long-term mean reversion

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  • Hjalmarsson, Erik

Abstract

I analyse the relationship between two stylized empirical facts for stock returns: Unconditional long-term mean reversion and predictability by variables such as the dividend-price ratio or the short-term interest rate. In particular, I show that if one imposes that returns satisfy long-term mean reversion, this implies an upper bound on the predictive regression R-square. If a predictive regression is intended as a motivational building block for theoretical modelling, and the R-square bound is violated, one should recognize that the implied returns process violate long-term mean reversion. Empirical results show that the proposed bound is binding for several leading predictors.

Suggested Citation

  • Hjalmarsson, Erik, 2018. "Maximal predictability under long-term mean reversion," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 269-282.
  • Handle: RePEc:eee:empfin:v:45:y:2018:i:c:p:269-282
    DOI: 10.1016/j.jempfin.2017.11.006
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    More about this item

    Keywords

    Return predictability; Variance ratios;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G1 - Financial Economics - - General Financial Markets

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