Does academic research destroy stock return predictability?
- Autores: R. David McLean, Jeffrey Pontiff
- Localización: The Journal of finance, ISSN 0022-1082, Vol. 71, Nº 1, 2016, págs. 5-32
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
- Dialnet Métricas: 3 Citas
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Resumen
We study the out-of-sample and post-publication return predictability of 97 variables shown to predict cross-sectional stock returns. Portfolio returns are 26% lower out-of-sample and 58% lower post-publication. The out-of-sample decline is an upper bound estimate of data mining effects. We estimate a 32% (58%–26%) lower return from publication-informed trading. Post-publication declines are greater for predictors with higher in-sample returns, and returns are higher for portfolios concentrated in stocks with high idiosyncratic risk and low liquidity. Predictor portfolios exhibit post-publication increases in correlations with other published-predictor portfolios. Our findings suggest that investors learn about mispricing from academic publications.
