Financialization and Commodity Markets Serial Dependence
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
Recent financialization in commodity markets makes it easier for institutional investors to trade a portfolio of commodities via various commodity-indexed products. We present several pieces of novel causal evidence that daily exposure to such index trading results in price overshoots and reversals, as reflected in negative daily return autocorrelations, only among commodities in that index. This is because index trading propagates nonfundamental noise to all indexed commodities. We present direct evidence for such noise propagation using commodity news sentiment data. This paper was accepted by Bruno Biais, finance. Funding: Z. Da acknowledges financial support from the Beijing Outstanding Young Scientist Program [Grant BJJWZYJH01201910034034] and the 111 Project [Grant B20094]. K. Tang acknowledges financial support from the National Natural Science Foundation of China [Grants 71973075 and 72192802]. Y. Tao acknowledges financial support from the Start-up Research Grant of University of Macau [Grant SRG2022-00016-FSS]. L. Yang acknowledges the Social Sciences and Humanities Research Council of Canada for financial support [Grants 430-2018-00173 and 435-2021-0040]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4797 .
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 | 0.002 | 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) | 0.000 | 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 it