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Record W1970012844 · doi:10.1080/13504851.2014.943880

Dynamics between crude oil and equity markets under the risk-neutral measure

2014· article· en· W1970012844 on OpenAlexaff
Marie‐Hélène Gagnon, Gabriel J. Power, Dominique Toupin

Bibliographic record

VenueApplied Economics Letters · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSkewnessEconomicsKurtosisEconometricsFutures contractVector autoregressionVolatility (finance)Equity (law)Financial economicsMonetary economicsStatisticsMathematics

Abstract

fetched live from OpenAlex

This article investigates the time series relationship between equity and crude oil markets using option-implied risk-neutral moments. We recover daily time series of constant-maturity risk-neutral volatility (RNV), skewness and kurtosis using options data for the S&P 500 and WTI oil futures over the period January 1996 to October 2011. The transmission of shocks is analysed for each risk-neutral moment using a vector autoregression model where each market is represented by one equation. Impulse response functions and variance decompositions are recovered and analysed. Our contribution is to document the transmission of shocks measured through investor anticipations in both markets. Our results suggest the transmission of shocks measured through investor anticipations is different under the risk-neutral measure than under the physical measure previously studied in the literature. Shocks to equity market RNV and skewness are transmitted to oil RNVand skewness while the reverse is not observed. However, shocks to risk-neutral kurtosis in one market do not affect the other market. The crystallized changes in investor anticipations in equity markets are eventually passed on to oil markets.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.019
GPT teacher head0.203
Teacher spread0.185 · 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 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

Citations3
Published2014
Admission routes1
Has abstractyes

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