Consumption hedging and home‐country bias in a model of international capital market equilibrium
Bibliographic record
Abstract
Purpose The purpose of this paper is to develop a model of international capital market equilibrium where investors exhibit home‐country bias due to their desire to hedge real consumption. Design/methodology/approach This paper posits a two‐stage process of portfolio choice for the representative investor of a country. In the first step, the investor's benchmark portfolio is determined, whereas in the second step, his optimal portfolio is chosen. The latter portfolio maximizes the expected portfolio rate of return minus the risk tolerance weighted variance of tracking error. The market equilibrium implications of the portfolio optimality conditions are determine via aggregation across all investors and countries. Findings A revised security market line is derived that differs from the traditional security market line in terms of vertical intercept, slope, and beta coefficient. It is demonstrated that the derived model may be interpreted as a multi‐country generalization of the Chen‐Boness extension of the capital asset pricing model under uncertain inflation. Originality/value This paper presents an innovative application of Roll's tracking portfolio paradigm. Another novel feature is the derivation of the international capital market equilibrium implications of such portfolio choice behaviour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".