When Bonds Matter: Home Bias in Goods and Assets
Bibliographic record
Abstract
Recent models of international equity portfolios exhibit two potential weaknesses: (1) the structure of equilibrium equity portfolios is determined by the correlation of equity returns with real exchange rates, yet empirically equities don't appear to be a good hedge against real exchange rate risk; (2) Equity portfolios are highly sensitive to preference parameters. This paper solves both problems. It first shows that, in more general and realistic environments, the hedging of real exchange rate risks occurs through international bond holdings since relative bond returns are strongly correlated with real exchange rate fluctuations. Equilibrium equity positions are then optimally determined by the correlation of equity returns with the return on nonfinancial wealth, conditional on the bond returns. The model delivers equilibrium portfolios that are well-behaved as a function of the underlying preference parameters. We find reasonable empirical support for the theory for G-7 countries. We are able to explain short positions in domestic currency bonds for all G-7 countries, as well as significant levels of home equity bias for the U.S., Japan, and Canada.
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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 | 0.002 | 0.011 |
| 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 | 0.001 |
| 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".