Global Portfolio Diversification for Long-Horizon Investors
Bibliographic record
Abstract
This paper conducts a theoretical and empirical investigation of global portfolio diversification for long-horizon investors in the presence of permanent cash flow shocks and transitory discount rate shocks to asset prices and returns.An increase in the cross-country correlations of cash flow shocks raises the risk of a globally diversified portfolio at all horizons.By contrast, an increase in the cross-country correlations of discount rate shocks has a muted effect on portfolio risk at long horizons and does not diminish the benefits of global portfolio diversification to long-term investors.Empirically, we find that increased correlations of discount rate shocks resulting from financial globalization appear to be the main driver of an estimated secular increase in the crosscountry correlations of both stock and bond returns since the late 1990's.Increased correlations of inflation shocks are also an important source of the shift in bond correlations.By contrast, we don't find evidence of an increase in the cross-country correlations of equity cash flow news or stock market volatility shocks.Our findings imply that the benefits of global equity diversification have not declined for long horizon investors despite the secular increase in global stock correlations, while the benefits of global bond diversification have declined.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".