Determinants of Financial Derivative Usage: Empirical Evidence from the Perspective of Governance Structure
Bibliographic record
Abstract
By examining the use of derivatives in a sample of US firms, this paper studies the relationship between the structure of corporate governance, including both bondholder rights and shareholder rights, and managerial hedging decision. We detect a significant association between the hedging decision and governance structure after controlling for well-documented rationales in the prior literature. As one of the first papers, we recognize the impact of bondholder rights on risk management. Our results document both strong bondholder rights and strong shareholder rights encourage hedging strategy, which supports our hypothesis that the main role of corporate hedging is to overcome inefficient markets and maximize firm value, and therefore strong bondholder (or shareholder) rights are positively related to the hedging policy. Our main results keep robust after adopting multiple alternative measures of bondholder rights and shareholder rights and using simultaneous equations model (SEM) to control for potential endogeneity. Moreover, we find weakly significant results echoing earnings management hypothesis but no evidence of risk-shifting hypothesis is observed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".