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Record W3012115342 · doi:10.1093/rapstu/raaa002

Stock Price Movements: Business-Cycle and Low-Frequency Perspectives

2020· article· en· W3012115342 on OpenAlexaff
Chunhua Lan

Bibliographic record

VenueThe Review of Asset Pricing Studies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPredictabilityEconomicsDividendBusiness cycleDividend yieldEconometricsCash flowFinancial economicsStock (firearms)Yield (engineering)HorizonYield curveMonetary economicsDividend policyMathematicsStatisticsFinanceKeynesian economicsInterest rateEngineering

Abstract

fetched live from OpenAlex

Abstract We find that a business-cycle component of the aggregate dividend yield strongly predicts short-term aggregate dividend growth and consumption growth, whereas its low-frequency counterpart significantly forecasts long-horizon market returns. The dividend yield—the sum of these two components—has difficulty revealing variations in expected cash flow growth, because its low-frequency component tends to disguise such variations. Yet the low-frequency component has significant forecasting power for multiperiod returns at horizons of several years to as long as around 20 years, which is longer than the horizons typically exploited in prior studies that provide weak statistical evidence to challenge multiperiod return predictability. (JEL G12, G17) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.698
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.275
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations14
Published2020
Admission routes1
Has abstractyes

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