The Nonlinear Dynamic Relationship between Stock Prices and Exchange Rates in Asian Countries
Bibliographic record
Abstract
This study explores dynamic relationships between stock prices and exchange rates in Asian countries. These relationships are complex and include both linear and nonlinear relationships. We employ a nonparametric causality test to explore them. The nonparametric causality test is more robust to a nonlinear relationship. The empirical results reveal that most countries have bi-directional causality relationships between stock prices and exchange rates. Some relationships are not captured by the linear model. These results support the theoretical model which shows dynamic interactions between stock and exchange rate markets. This study investigates the main driver to generate the nonlinear causality relatioships. The empirical results present that the main source for the nonlinearity is the volatility effects. In particular, they were substantial during the Asian and global financial crises. After controlling for the volatility effects, only one country shows the bi-directional causality relationship. In contrast to the previous studies, this study shows that the volatility effects are important between different asset markets. These findings suggest that controlling for exchange rate markets may be helpful to mitigate turmoil during a financial crisis.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".