Does Academic Research Destroy Stock Return Predictability?¶
MCLEAN, R. D., & PONTIFF, J. (2016). Does Academic Research Destroy Stock Return Predictability?. The Journal of Finance, 71(1), 5-32.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Calibrated Rule versus Moving World
- The financial concept of alpha decay — a calibrated edge erodes as the world it exploited changes (competitors arbitrage it, the regime turns) so the strategy must be continually renewed — transfers as a general expectation that any exploited regularity in a moving world is a depreciating asset: an ML model's accuracy, a policy's effectiveness, an evolved trait's fitness all decay against a world that does not hold still, and the practitioner should plan for renewal rather than permanence.
This sourceDocuments alpha decay — predictor returns fall ~26% out-of-sample and ~58% post-publication as the exploited edge is arbitraged away — the canonical evidence that a calibrated market edge is a depreciating asset.
Supported in partVerified against the publisher's abstract
Abstract reports predictor returns fall 26% out-of-sample and 58% post-publication, backing financial alpha decay but not the claim's broader transfer to ML, policy, or evolved traits.
“Portfolio returns are 26% lower out‐of‐sample and 58% lower post‐publication.”
- The financial concept of alpha decay — a calibrated edge erodes as the world it exploited changes (competitors arbitrage it, the regime turns) so the strategy must be continually renewed — transfers as a general expectation that any exploited regularity in a moving world is a depreciating asset: an ML model's accuracy, a policy's effectiveness, an evolved trait's fitness all decay against a world that does not hold still, and the practitioner should plan for renewal rather than permanence.
- Self-Defeating Prediction
- Markets and arbitrage. A published arbitrage signal attracts trades that close the opportunity it describes; the more confidently it is believed, the faster it disappears, a dynamic quant funds manage through alpha-decay analysis and signal cloaking.
Supported in partVerified against the publisher's abstract
Supplies the alpha-decay mechanism only: anomaly returns fall about 58% after publication, which the authors attribute to investors learning from publications and trading on them.
“Portfolio returns are 26% lower out‐of‐sample and 58% lower post‐publication.”
- Markets and arbitrage. A published arbitrage signal attracts trades that close the opportunity it describes; the more confidently it is believed, the faster it disappears, a dynamic quant funds manage through alpha-decay analysis and signal cloaking.
Verification¶
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