Bibliographic record
Abstract
This dissertation investigates two important puzzles in international finance: the home bias puzzle and the contagion puzzle. In the first chapter of the dissertation, a rational forward-looking model of portfolio choice is used to study home bias, the tendency to overweight home securities in investment portfolios. The model is applied to monthly returns on equity indices for Canada, France, Germany, Italy, Japan, U.K., U.S. and the world in the 1970--1998 period. Three main findings emerge. First, if a U.S. investor uses a forecasting model and all of the currently available information to form and update the forecasts about the mean and variance of future returns, it is optimal for the investor to hold an internationally diversified portfolio. Second, the conditional approach generates much more stable and sensible portfolio weights than the unconditional approach. Third, taking into account the predictability of the variance can reduce the standard error of optimal allocation weights substantially compared with the traditional method of using the historical sample mean and variance. These findings imply that a well-diversified portfolio is statistically significantly different from the home-biased portfolio. The second chapter of the dissertation focuses on the contagion puzzle: the simultaneous withdrawal of capital from emerging markets apparently without differentiation during crises. The theoretical model of rational contagion generates a co-movement of capital outflow from both crisis and non-crisis countries through the transmission of uncertainty. The model describes the portfolio allocation problem facing an investor from a developed country who invests in the home market and in emerging markets. Returns in emerging markets are assumed to be predictable by local dividend yields to some degree. The model is used to demonstrate that when uncertainty about the forecasting parameters in one emerging market increases (as is likely during periods of crisis), it may be optimal for the investor to withdraw from all other emerging markets, even if fundamentals in those markets are unchanged. Data on U.S. equity holdings show that recent capital outflows from Latin America during the Asian crisis and from Asia during the Mexican crisis are consistent with the theoretical model of rational contagion.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".