The Influence of Corporate Risk Exposures
Bibliographic record
Abstract
We examine how corporations' exposures to interest rates, exchange rates, and commodity prices are related to investors' and analysts' expectations about firms' earnings. The results indicate that investors and analysts encounter difficulties estimating the earnings effects of the risk exposures that companies face. Stock returns around earnings announcements are associated with the magnitude of both recent quarter and lagged shocks to interest rates, exchange rates and commodity prices, especially for firms with large ex-ante exposures to these risks. Although intra-quarter revisions to analysts' forecasts do incorporate information about the earnings effects of the risk shocks, analysts' earnings forecasts do not fully resolve the uncertainty created by either recent quarter and lagged shocks. Overall, the results suggest that analysts resolve between 25%-60% of the total uncertainty created by interest rate, exchange rate, and commodity price shocks. The results are consistent with arguments that corporate financial risk exposures are not transparent to investors or analysts, and support recent research arguing that firms' hedging strategies consider this source of earnings uncertainty.
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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 | 0.001 | 0.001 |
| 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".