Was there a peso problem in cattle options?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – Pricing densities implied from options on live cattle futures show a persistent and negative skew. The purpose is to examine whether the skew can be explained, in part, by peso-type problems. Design/methodology/approach – Two announcements of bovine spongiform encephalopathy (BSE) provide a natural setting within which to examine the validity of the peso-problem explanation. These announcements represent the first documented cases of BSE in North America. Prior to the announcements, the potential for BSE would have been known by market participants as the disease had been found among cattle in the British Isles, Europe and Asia. The paper uses options market data to compute implied moments of the pricing distribution for live cattle futures. The paper then analyzes these moments around BSE announcements. Findings – The first Canadian BSE announcement impacted the mean and volatility but not the implied skew. Later in the year, BSE was found in a US cow and the paper finds a statistically significant change in the implied skew. The distribution showed a pronounced leftward skew prior to the US announcement but was nearly symmetric during the days afterwards. This finding is consistent with the market having priced the possibility of a BSE discovery into deep out-of-the-money put options. Originality/value – Peso problems have been documented in other financial markets. The results are important because they suggest that they may also be important to agricultural markets and that agricultural options markets do account for low probability but highly important events.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it