The Fair Value of Cash Flow Hedges, Future Profitability, and Stock Returns
Bibliographic record
Abstract
Abstract The SEC and FASB recently expressed concerns that investors do not fully assimilate all of the information provided by complex and incomplete derivatives and other comprehensive income ( OCI ) disclosures. My evidence supports these concerns. Specifically, I examine the information content of unrealized cash flow hedge gains/losses for future profitability and stock returns. An unrealized gain on a cash flow hedge suggests that the price of the underlying hedged item (i.e., commodity price, foreign currency exchange rate, or interest rate) moved in a direction that will impair the firm's profits after the hedge expires. Consequently, I find that unrealized cash flow hedge gains/losses are negatively associated with future gross profit after the firm's existing hedges have expired. This association only holds after the firm has reclassified its hedges into earnings, and is weaker for firms that can pass input price changes on to their customers. Finally, investors do not immediately price the cash flow hedge information. Instead, investors appear surprised by future realizations of gross margin, consistent with the view that complex and incomplete disclosures delay pricing. These results are relevant to policymakers involved in the current FASB and IASB project designed to simplify the accounting and disclosure for derivatives and, in particular, cash flow hedges.
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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 | 0.005 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".