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Record W3195105525 · doi:10.1177/22785337211033509

Does Credit Rating Revisions Affect the Price of Common Stock: A Study of Indian Capital Market

2021· article· en· W3195105525 on OpenAlex
Gaurav Dawar, Shivangi Bhatia, Jai Parkash Bindal

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

VenueBusiness Perspectives and Research · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsCredit ratingEvent studyBusinessStock exchangeAbnormal returnStock marketStock (firearms)Monetary economicsCapital marketEconomicsFinancial systemFinance

Abstract

fetched live from OpenAlex

The current investigation aims to assess the effect of credit assessment changes on the share prices of Indian companies from 2009 to 2019. The data of top 100 companies listed on National Stock Exchange (NSE) across 10 industries stem from CMIE databases. The excess stock return is compared with the market in a 15-day window around credit rating changes. The event effect on share prices is more in the pre-event window compared to the post-event window. Positive abnormal stock returns around upgrades through downgrades are statistically significant compared to upgrades. Credit ratings are not significant across industries, and agency nationality is a critical factor for calculating the intensity of price reaction.

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)0.001
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 score0.196
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.049
GPT teacher head0.328
Teacher spread0.279 · 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