Return‐Implied Volatility Dynamics of High and Low Yielding Currencies
Bibliographic record
Abstract
This study investigates the return‐implied volatility dynamics of six most actively traded currencies before and during the financial crisis using quantile regression analysis. In particular, we examine how the size and sign of high and low yielding currency futures returns influence implied volatilities in the currency market. It is found that, especially during a volatile period, the behavior of the return‐implied volatility relationship of high yielding currencies, such as the Australian dollar, Canadian dollar, and British pound, has some similarities with that in the stock markets, while low yielding currencies behave the opposite way. Investment currencies generally exhibit a negative asymmetry, while funding currencies, the Japanese yen in particular, exhibit a positive asymmetry. The results of the study appear consistent with the recent carry trade literature implying that carry trades, investors' behavior, risk exposure, and global risk explain return‐implied volatility dynamics in the currency markets. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 35:1026–1041, 2015
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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 | 0.005 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".