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Record W3087316049 · doi:10.1002/cjas.64

Why do companies issue convertible bond loans? An empirical analysis for the Canadian market

2008· preprint· en· W3087316049 on OpenAlexaffvenueabout
Igor Lončarski, Jenke ter Horst, Chris Veld

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2008
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsConvertible bondEquity (law)Event studyDebtMonetary economicsBusinessConvertibleAgency costEconomicsFinancial economicsFinancial systemFinanceCorporate governanceShareholder

Abstract

fetched live from OpenAlex

Abstract To identify issuer motives, we study the determinants of announcement effects of convertible debt issues in the Canadian market. Classified into equity‐ and debt‐like, wealth effects are significantly more negative for equity‐like convertible bond issuers. Equity‐like convertibles are significantly negatively affected by agency costs of equity. However, agency costs of debt have no significant effect on debt‐like convertibles. Consistent with Stein (1992), this suggests convertibles in particular represent a substitute for equity. Moreover, convertible debt offers announced by income trusts experience significantly less negative wealth effects than offers by nontrusts—a finding explained by a more debt‐like convertible design, very low agency costs of equity in case of income trusts, or both. Copyright © 2008 ASAC. Published by John Wiley & Sons, Ltd.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.025
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0040.002
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.169
GPT teacher head0.325
Teacher spread0.156 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2008
Admission routes3
Has abstractyes

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