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Record W3206116313 · doi:10.1111/ajfs.12349

How Do Structural Oil Price Shocks Affect China's Investor Sentiment? The Critical Role of OPEC Oil Supply Shocks*

2021· article· en· W3206116313 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAsia-Pacific Journal of Financial Studies · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEconomicsOil supplyStock (firearms)Monetary economicsVariance decomposition of forecast errorsChinaDemand shockOil priceStock marketAggregate demandSupply shockEconometricsAutoregressive modelStructural vector autoregressionMonetary policy

Abstract

fetched live from OpenAlex

Abstract This paper applies a modified structural vector autoregressive (SVAR) model to explore whether explicit structural oil price shocks affect investor sentiment in China's stock market. The results indicate that China's investor sentiment responds significantly positively to OPEC supply shocks, while it responds significantly negatively to oil‐specific demand shocks. However, China's stock investor sentiment does not respond to aggregate demand shocks and non‐OPEC supply shocks. In addition, OPEC supply shocks and oil‐specific demand shocks have greater explanatory power for variations in stock investor sentiment through variance decomposition.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.001
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 head0.017
GPT teacher head0.244
Teacher spread0.227 · 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