MétaCan
Menu
Back to cohort
Record W4404803459 · doi:10.1016/j.mulfin.2024.100887

Stock market returns and climate risk in the U.S.

2024· article· en· W4404803459 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Multinational Financial Management · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaEuropean Commission
KeywordsClimate riskStock marketStock (firearms)Financial economicsBusinessClimate changeEconomicsMarket riskFinancial systemMonetary economicsFinanceGeographyOceanography

Abstract

fetched live from OpenAlex

Using a data set for all companies forming the S&P 500 index, we investigate the stock price responses to acute physical risks, chronic physical risks, and transition risks. Our findings reveal that certain sectors are more vulnerable to climate risks, whereas others appear to be relatively unaffected. In addition, our results show that listed firms with poor environmental performance scores are more exposed to climate risk, as indicated by their stock returns being negatively affected, compared to firms with higher environmental performance scores. This suggests that improving environmental performance may help companies to better cope with climate risks and improve their financial performances. Our analysis provides evidence that the short-term systematic risk is more vulnerable to the climate risk events, whereas effects on long-term systematic risk do not appear to be statistically significant. These findings indicate that investors and firms should pay a particular attention to short-term systematic risk when considering the potential impact of climate risk on stock market performances. • We analyse the US stock market’s reaction to physical and transition climate risks. • An event study assesses how acute and transition risks affect stock returns. • Stock return of firms is negatively impacted by their lower environmental scores. • Environmental performance is linked to financial resilience against climate risks.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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