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Mandated Recognition of Employee Stock Option Expense – The Case of <scp>C</scp>anada

2012· article· en· W2119633108 on OpenAlexaboutno aff
Chandrasekar Subramaniam, Jeffrey J. Tsay

Bibliographic record

VenueJournal of International Financial Management and Accounting · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessFinancial statementStock (firearms)MandateStock marketStock exchangeFinanceMonetary economicsActuarial scienceEconomicsAccounting

Abstract

fetched live from OpenAlex

Abstract On December 18, 2003 the A ccounting S tandards B oard of C anada announced that all firms registered in C anada would be required to expense stock options‐based compensation effective January 1, 2004. While a few firms had voluntarily opted to expense stock options prior to this date, the vast majority of firms had not. This study investigates the market reaction to this announcement by listed firms in the Toronto Stock Exchange that continued to disclose option expense rather than report it in the financial statement. We find no average market reaction by our sample firms affected by this mandate around the announcement date, but a significantly negative market reaction during the 5‐day window around the issuance date of the exposure draft. However, in cross‐sectional tests around the mandated expense announcement date, we find a significant negative relationship between the cumulative abnormal returns and the B lack– S choles value (and number) of options outstanding and of options granted the previous year. These results suggest that the magnitude of the market reaction to the mandated expense announcement is related to the firm's usage of options. Our results provide further evidence that stock prices may not fully impound information disclosed in footnotes.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.570
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.226
Teacher spread0.212 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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