Time Series Properties of four Latin American Equity Markets: Argentina, Brazil, Chile and Mexico
Bibliographic record
Abstract
Variance ratio tests indicate that the equity markets of Argentina, Brazil and Mexico follow random walks, but not those of Chile. The low correlations among the four markets suggest that investments in these countries can contribute to reduce portfolio risk. The research on the random walk hypothesis has been heavily concentrated on the large equity markets of the United States, Canada, Japan and Europe (summers 1986; Fama and French 1986a, 1986b; Lo and MacKinlay 1988, and Poterba and Summers 1988). Even though some studies have been conducted for stock markets of developing countries (Errunza 1983 and Errunza and Losq 1985), little research has been done in Latin American capital markets (Errunza and Losq 1987). This paper employs the variance-ratio test to investigate the random walk hypothesis for the following four Latin American equity markets: Argentina, Brazil, Chile and Mexico. Two versions of the variance-ratio tests are implemented : first, the variance-ratio under the maintained hypothesis of homocedasticity and, second, the heteroscedasticity-robust variance-ratio. The empirical results reported in the paper indicate that the random walk hypothesis is rejected for Chile but it is generally confirmed for Argentina, Brazil and Mexico. Therefore, American investors might not be able to develop investment strategies that can be generate abnormal returns in these three countries. However, the low correlation among these markets suggests that American investors can reduce the risk of their portfolios by diversifying in international stocks of these countries.
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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) | 0.001 | 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) | 0.001 | 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".