Commodities as an Asset Class Throughout the Financial Crisis
Bibliographic record
Abstract
This project investigates the performance of commodities as an asset class from September 24, 2003 to June 30, 2011, in the context of its inclusion within a broader portfolio of equities and bonds. Specifically, we examined whether the Goldman Sachs Commodity Index (GSCI), a fully-collateralized index of commodity futures, performed better or worse than the equity and bond marketplaces leading up to, during, and following the financial crisis of the late-2000s, and whether or not it provided any diversification benefits to a traditional portfolio. Our findings were that the GSCI outperformed U.S. bonds but generally not U.S. stocks during the study period, that it was more volatile than both traditional asset classes, offered modest diversification benefits, especially after the crisis began, and that it fared worse than equities in a review of higher moments. Canadian equity investors would have found the GSCI more appealing in a portfolio context than U.S. equity investors would have during the study period, due to a more favourable return weak performance of the U.S. Dollar. These results are in marked contrast to studies of commodity futures prior to the financial crisis, and provide a cautionary note for investors with respect to incorporating a basket of commodities that is heavily weighted in a particular commodity type, such as the GSCI, into their traditional portfolios. Nevertheless commodities clearly have maintained certain diversification benefits, especially during the worst of crisis where they have tended to outperform equities. On the other hand, an extension of the study period to include the Dotcom crisis revealed that commodities offered substantial diversification benefits to a traditional portfolio during that time. In addition, adding commodity futures to a portfolio of stocks and bonds significantly reduces downside risk, as measured by Value-at-Risk (VaR). On balance, we recommend that a basket of commodity futures be considered for inclusion into a traditional portfolio with a long-term investment horizon.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".