Bibliographic record
Abstract
Purpose This paper aims to develop hedging strategies using both futures and forward contracts and issuing risky debt when financially constrained firms are forced to operate in long horizon. Design/methodology/approach The authors present a model for developing hedging strategies using both futures and forward contracts and issuing risky debt. A theoretical model employing stochastic differential equations for forward hedging is illustrated with a numerical example over parameter values consistent with the literature. Findings A financially constrained firm with limited cash balance must hedge its liquidity with both future and forward contracts and issue risky debt to support its long-term operations. The firm can issue a minimal amount of risky debt by adding forward contracts into hedging and can increase its value higher than that when hedging with only futures contracts. We show numerically that hedging with both futures and forward contracts allows the firm to issue minimal risky debt in increasing its firm value. Practical implications When Metallgesellschaft nearly collapsed in 1993, it offered long-term forward contracts to its customers and attempted to hedge its risk by rolling over series of short-term futures contract. It created the situation of inherent mismatch in maturity structure. A financially constrained firm operating in a long horizon appears to commit its liquidity as long-term forward contracts, which cannot be fully hedged with series of futures contacts. The firm should hedge its liquidity with both futures and forward contracts and avoid liquidation with deadweight costs in its long-term operation. Originality/value This is the first study examining hedging strategies with both futures and forward contracts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".