The Impact of Inflation Hedge Assets on Portfolio Optimizations for US and Canadian Investors
Bibliographic record
Abstract
The research is based on “Gold: Inflation Hedge and Long-Term Strategic Asset.” paper by Dempster and Artigas (2010). Authors used basic portfolio for the US investor, which includes Corporate Bonds, US Treasuries, Equity US and Equity Ex-US. By adding, alternatively, the four potential inflation-hedges, researchers showed Gold as the most appropriate Long-Term Strategic Asset. In our research, we constructed basic investment portfolio for US and Canadian investors. For each case, alternatively, four potential Inflation Hedges, which are Gold, S&P GSCI Index, REITs and TIPS, were added to the basic portfolio. The optimization results are based on the post-crisis period from 2009 to 2016. The final results for the US suggest that Gold should be considered as a strong long-term strategic asset. For the Canadian case, Gold, and S&P GSCI tend to be appropriate long-term strategic assets, which should be added to the basic portfolio. Canadian REITs get allocation under base case assumptions but sensitivity analysis indicates that the results are not robust.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 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".