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Data snooping in equity premium prediction

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  • Dichtl, Hubert
  • Drobetz, Wolfgang
  • Neuhierl, Andreas
  • Wendt, Viktoria-Sophie

Abstract

We analyze the performance of a comprehensive set of equity premium forecasting strategies. All strategies were found to outperform the mean in previous academic publications. However, using a multiple testing framework to account for data snooping, our findings support Welch and Goyal (2008) in that almost all equity premium forecasts fail to beat the mean out-of-sample. Only few forecasting strategies that are based on Ferreira and Santa-Clara’s (2011) sum-of-the-parts approach generate robust and statistically significant economic gains relative to the historical mean even after controlling for data snooping and accounting for transaction costs.

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  • Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    • Handle: RePEc:eee:intfor:v:37:y:2021:i:1:p:72-94
    DOI: 10.1016/j.ijforecast.2020.03.002
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