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Record W2143639306

The Spurious Relation between Inflation Uncertainty and Stock Returns: Evidence from the U.S.

2013· article· en· W2143639306 on OpenAlexvenueno aff
Samih Antoine Azar

Bibliographic record

VenueReview of Economics and Finance · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsStock (firearms)EconometricsSpurious relationshipInflation (cosmology)Real interest rateEquity (law)EarningsExplanatory powerFinancial economicsMonetary economicsInterest rateMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this paper is to reconsider the empirical evidence on the relation between inflation, inflation uncertainty, and stock returns. Two unprecedented proxies for inflation uncertainty are used. First, the power of inflation and inflation uncertainty to explain stock returns is compared. Both variables are separately negatively related to stock returns. However, when both are included together in the regressions, the inflation variable becomes redundant, meaning that its coefficient becomes statistically insignificantly different from zero. This means that inflation uncertainty dominates and supplants the effect of inflation. Second, this paper provides strong evidence that inflation uncertainty itself becomes redundant, and fails to explain stock returns, when two fundamental variables are included in the regressions. The two fundamental variables are the change in the cost of equity, and the growth rate of earnings. The first variable is roughly measured by the change in the baa and in the aaa corporate bond yields, while the second one is taken to be the rate of change of industrial production. The main conclusion of the paper is that both inflation and inflation uncertainty are not significantly related to stock returns when the two aforementioned fundamental variables are accounted for.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.619
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.039
GPT teacher head0.228
Teacher spread0.189 · 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
GenreEmpirical

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

Citations11
Published2013
Admission routes1
Has abstractyes

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