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Record W3158286502 · doi:10.1093/rapstu/raab011

Strategic Trading When Central Bank Intervention Is Predictable

2021· article· en· W3158286502 on OpenAlexaff
Liyan Yang, Haoxiang Zhu

Bibliographic record

VenueThe Review of Asset Pricing Studies · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntervention (counseling)Central bankEconomicsMonetary economicsPsychological interventionFinancial economicsMonetary policyPsychology

Abstract

fetched live from OpenAlex

Abstract Market prices are noisy signals of economic fundamentals. In a two-period model, we show that if the central bank uses market prices as guidance for intervention, large strategic investors who benefit from high prices would depress market prices to induce a market-supportive intervention. Stronger anticipated interventions lead to deeper price depressions preintervention and sharper price reversals post-intervention. The central bank intervention harms strategic investors even though it is the investors who tried to mislead the central bank. The model predicts a V-shaped price pattern around central bank interventions, consistent with recent evidence. (JEL G14, G18)

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: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.456
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.082
GPT teacher head0.289
Teacher spread0.207 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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