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Record W4387162402 · doi:10.1093/rof/rfad033

Why momentum concentrates among overvalued stocks?

2023· article· en· W4387162402 on OpenAlexaff
Jack Favilukis, Terry Zhang

Bibliographic record

VenueEuropean Finance Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMomentum (technical analysis)EconomicsTrading strategyFinancial economicsAnomaly (physics)EconometricsProfit (economics)Monetary economicsPhysicsMicroeconomics

Abstract

fetched live from OpenAlex

Abstract We uncover a link between momentum and overvaluation: assets that generate strong momentum profits have lower risk-adjusted unconditional returns; conversely, trading momentum within overvalued assets doubles the profit of the standard momentum strategy. We compute the profits of a momentum strategy within various portfolios; portfolios within which momentum is profitable are defined as momentum trading opportunity (MTO). High-MTO assets have negative unconditional alphas and concentrate in the short legs of most anomalies; controlling for MTO reduces anomaly alphas by up to half. These results imply that the existence of other anomalies is closely linked to the existence of momentum and they should be studied jointly.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.546
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.232
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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