How Publication Can Reduce Stock Return Predictability

Summary

The document raises a question about why stock return predictors may weaken after academic publication. It cites McLean and Pontiff’s reported evidence that portfolio returns were lower out of sample and declined further after papers describing predictors were published. One interpretation is that publication informs investors about mispricing, draws attention to the signal, and leads trading to reduce the opportunity.

The author asks whether this pattern could instead be self-reinforcing when predictor discovery involves data snooping. A variable selected partly by chance might pass robustness checks; publication could then prompt trading that changes returns, even if the original relationship did not reflect a durable economic mechanism. The thread presents this as a concern rather than resolving it. It does not give enough detail to assess the cited study’s design, alternative explanations, or the magnitude of publication effects beyond the stated figures, so the proposed feedback mechanism remains a hypothesis.

Key ideas

• The cited study reports weaker portfolio returns out of sample and a further decline after predictor papers are published.
• Publication may spread information about mispricing and attract trading that erodes a return predictor.
• Data snooping could create apparent predictors that survive some robustness checks without a durable economic basis.
• The author proposes that post-publication trading might create or amplify return changes, but the discussion does not resolve this possibility.

Tags

# Does Academic Research Destroy Stock Return Predictability?


# Does Academic Research Destroy Stock Return Predictability?












McLean/Pontiff (2016) give evidence that portfolio returns are 26% lower out-of-sample and 58% lower after publishing an academic paper on variables, which are likely to predict cross-sectional returns:

> Our findings suggest that investors learn about mispricing from academic publications. [...] This result is also consistent with the idea that academic research draws trading attention to the predictors.

Isn't this a self-fulfilling prophecy, having regard to the data-snooping bias?

Assume data-snooping leads us to a variable which explains the cross-section of stock returns and luckily passes some robustness tests. After publishing our paper, the market adopts our findings and diminishes strategies based on our variable - although there is no economic reason to do so! In fact, anyone thinks of a previous mispricing but only after our publication real mispricing arises.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.