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Record W4313886678 · doi:10.18374/jife-22-4.1

MARKET IMPACT OF COVID-19 TO ANNOUNCEMENTS OF CANADIAN EQUITY OFFERINGS

2022· article· en· W4313886678 on OpenAlexaffabout
Arturo Rubalcava

Bibliographic record

VenueJournal of International Finance and Economics · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicImpact of AI and Big Data on Business and Society
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Equity (law)BusinessVolatility (finance)Stock marketMonetary economicsCapital marketAccountingFinancial systemEconomicsFinancial economicsFinance

Abstract

fetched live from OpenAlex

Did COVID-19 period (March 11, 2020 -Nov.29, 2021) have differential impact on the market reaction of Canadian bought deal seasoned equity offering announcements compared with pre- COVID-19 period (Jan.13,2012-March 10, 2020)?How did expected determinants of equity offers affect the market reaction in COVID-19 period compared with pre-pandemic period?Using univariate and multivariate analysis, this study shows no significant difference on the market reaction between pre-and COVID-19 periods.On the other hand, results show determinants have more significant effect on market reaction in the COVID-19 period than in the pre-pandemic period, which was mostly insignificant.For example, in COVID-19 period, offers with favorable market effect are those from health care companies, and those which intended uses of funds are capital investments, debt decrease, and exploration or development.Similarly, positive effect occurs for offers audited by the Big 4 accounting firms, and those sold by existing shareholders (not capital raising) among others.Surprisingly, stock market volatility had favorable market effect in the COVID-19 period.This is an unexpected finding since investors usually unwelcome market volatility.

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)0.002
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 score0.252
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.142
GPT teacher head0.406
Teacher spread0.264 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes2
Has abstractyes

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