Commodity futures price volatility, convenience yield and economic fundamentals
Bibliographic record
Abstract
Commodity price volatility increased during 2006 to 2011 first with the commodity bull cycle of 2006 to 2008 and then with the credit freeze crisis and Great Recession. This letter uses both high- and low-frequency data over 1990 to 2011 to examine the link between economic fundamentals and measures of realized volatility and convenience yield computed from estimated futures price forward curves. The possible influence of institutional investors (index traders) is also examined. Affine term structure models are estimated using Intercontinental Exchange (ICE) futures prices on cotton, a commodity for which economic fundamentals can be readily identified and measured. The results, robust across specifications, suggest that the determinants of volatility, but not convenience yield, changed during the period 2006 to 2011. There is no evidence that index traders are responsible for increased volatility or changes in convenience yield.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.001 |
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".