AEC’ Exchange Rates Risk on Interbank Money Market: Evidence from Thailand
Bibliographic record
Abstract
Exchange rate risk is one part of systematic risk that able to be transfer between countries and markets. Therefore, many researchers are seeking the suitable way to reduce the exchange rate risk. This study aims to analyze the AEC’s exchange rates risk on interbank money market thereby we perform our test with econometric test by using the linear regression to be our model. This study has found some evidence from the variance decomposition test and impulse response test that suggested the exchange rates of AEC member countries such the Indonesian Rupiah (IDR), and Philippine Peso (PHP) can be explained the interrelationship between exchange rate and BIBOR better than other currencies. Moreover, we also found the degree of relation of the exchange rates vary direction with the tenor of BIBOR as well. And, almost every currency of the AEC’s exchange rates had positive relation on BIBOR except the PHP. The results from this study will be extending knowledge and understanding of exchange rate risk on BIBOR to the central bank, financial institution, and everyone who interesting in exchange rate risk moreover this result can apply for risk management as well.
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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 | 0.004 |
| 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 | 0.001 |
| 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".