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Record W2981118441

The impact of economic policy uncertainty and commodity prices on CARB country stock market volatility

2019· article· en· W2981118441 on OpenAlexaboutno aff
Syed Abul Basher, Alfred A. Haug, Perry Sadorsky

Bibliographic record

VenueMunich Personal RePEc Archive (Munich University) · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsVolatility (finance)Commodity marketMonetary economicsStock marketStock (firearms)Vector autoregressionStock market volatilityShock (circulatory)Interest rateFinancial economicsFinance
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the impact of economic policy uncertainty shocks and shocks to commodity prices on the realized stock market volatility of the CARB (Canada, Australia, Russia, and Brazil) countries. The CARB countries are important countries to study because they are major commodity exporters. The analysis is conducted using sign restricted impulse response functions (IRFs) and structural vector-autoregressive IRFs. There are some common results across the CARB countries. A positive shock to commodity prices lowers realized stock market volatility while a shock to economic policy uncertainty has a significant positive impact on realized stock market volatility. The magnitudes of the initial impact of these two shocks are similar. Shocks to global economic activity and short-term interest rates lower realized stock market volatility. The impacts of these shocks are more pronounced in models that use sign restrictions. These results have implications for investors and policy makers.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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 designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

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