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Record W1520879115

Essays on the use of convertible bonds and the security issuance decision

2003· preprint· en· W1520879115 on OpenAlexaboutno aff
Igor Lončarski

Bibliographic record

VenueRePEc: Research Papers in Economics · 2003
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsConvertible bondCapital structureDebtLeverage (statistics)ConvertibleConvertible arbitrageEquity (law)BusinessAgency costBondFinanceHybrid securityFinancial economicsEconomicsFinancial marketRisk arbitrageCorporate governanceShareholderCapital asset pricing modelBroker-dealer
DOInot available

Abstract

fetched live from OpenAlex

This dissertation examines two topics, the use of convertible bonds by Canadian companies and the security issuance choice in the Canadian market. The first part of the dissertation is devoted to the use of convertible debt by Canadian companies. Practitioners most often view convertibles as delayed equity and claim to issue them because of the lower coupon rate and to “sweeten” the debt issue, which would be otherwise more difficult to place. On the other hand, academics have proposed theories that in general suggest that companies that face high debt- and/or equity-related agency costs could benefit from issuing convertible debt as opposed to other “straight” means of financing. Chapter 2 provides the literature overview of the motives for the issuance of convertible debt. Chapter 3 investigates motives for the use of convertible debt in the Canadian market. Chapter 6 analyzes a convertible arbitrage in the Canadian market, a strategy mainly used by hedge funds to exploit underpricing of convertible bonds. The second part of the dissertation analyzes the security issuance decision in the Canadian market. The security issuance decision is essentially a capital structure decision. Different explanations have been put forward in the past as to how and when managers decide to increase or decrease the leverage of the firm, such are the pecking-order model, the market timing model and the agreement between insiders and outsiders. Chapter 4 examines the determinants of security issuance choice in the Canadian market, while Chapter 5 investigates the relationship between short interest and some of the capital structure theories.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.470
Threshold uncertainty score0.934

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.003
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.061
GPT teacher head0.294
Teacher spread0.233 · 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 designTheoretical or conceptual
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
Published2003
Admission routes1
Has abstractyes

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