Data snooping in equity premium prediction

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

International Journal of Forecasting, 2021, vol. 37, issue 1, 72-94

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.

Keywords: Equity premium; Prediction; Data snooping; Multiple testing; Return predictability (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:37:y:2021:i:1:p:72-94

DOI: 10.1016/j.ijforecast.2020.03.002

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