Bibliographic record
Abstract
The hedging property of gold against single asset has been greatly demonstrated in literature. Gold-stock hedge suggests gold as ‘safe haven’ for stock market. Unlike gold-stock hedge which requires zero or negative correlation between their returns, gold-inflation hedge refers to the positive co-movement or ’peg’ between gold return and inflation. Thus, this is the first paper to address whether gold can hedge stock market and inflation simultaneously since stock market boom often comes with moderate inflation which creates puzzle in gold price dynamics and its hedging property. In this paper, we assume that an investor creates optimal portfolios from stock and gold. The weights assigned to gold are interpreted as hedge coefficient towards the stock market. We ask if the hedge coefficient also moves in tandem with inflation or other functions of inflation. When regressing the hedge coefficient on inflation or functions of inflation, the slope will be positive if the gold first used to hedge the stock market can also hedge inflation. We find that is not the case: the coefficient is not positive in statistics. This result implies that gold fails to hedge both stock market and inflation simultaneously over time.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".