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Momentum of return predictability

Author

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  • Wang, Yudong
  • Liu, Li
  • Ma, Feng
  • Diao, Xundi

Abstract

We find the momentum of predictability (MoP) that the forecasting performance of some univariate regressions is persistent. A univariate model which outperforms the benchmark during recent past period can also beat the benchmark in the near future out-of-sample. Accordingly, we propose a forecasting strategy that involves switching between a model of interest and the benchmark model, based on observations of their recent past performance. We obtain significant stock return predictability both in statistical and economic terms. Predictability is found to be stronger for longer forecasting horizons. Success of the MoP strategy is also seen in forecasting exchange rates.

Suggested Citation

  • Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
  • Handle: RePEc:eee:empfin:v:45:y:2018:i:c:p:141-156
    DOI: 10.1016/j.jempfin.2017.11.003
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    More about this item

    Keywords

    Return forecasting; Predictive regression; Model switching; Portfolio exercise; Certainty equivalent return;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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