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Record W4391353491 · doi:10.1111/ajfs.12459

Does Green Bond Issuance Enhance Market Return of Equity Shares in the Indian Stock Market?*

2024· article· en· W4391353491 on OpenAlex
Snehith Jacob Kodiyatt, Ajithakumari Vijayappan Nair Biju, Manna Sarah Jacob, Krishna Reddy

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 · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSustainable Finance and Green Bonds
Canadian institutionsUniversity of WaterlooEnvironment and Climate Change Canada
FundersIndian Council of Social Science Research
KeywordsEquity (law)BusinessFinancial systemBondStock marketMonetary economicsBond marketFinancial economicsFinanceEconomics

Abstract

fetched live from OpenAlex

Abstract This study examines the announcement effect of a green bond on the issuer's stock returns in the Indian Stock Market. The event study methodology for data analysis and abnormal returns were calculated using the market model for the 16‐day event window that includes the 5 days prior and 10 days after the issuance of the green bonds. The findings of this study show that green bond announcements do not create any significant abnormal returns, thus suggesting investors' irrationality toward environmental factors. This study informs policymakers that investor education relating to the environment is needed in India.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.030
GPT teacher head0.286
Teacher spread0.256 · 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