Frequency Domain Causality Analysis of Interactions between Financial Markets of Turkey
Bibliographic record
Abstract
In this paper, we examined the dynamic linkages between financial markets of Turkey by using frequency domain causality analysis, proposed by Breitung and Candelon (2006), for the weekly Turkish data from 2003 to 2015. The results show that there are volatility spillovers from stock market returns to interest rate and EURO both in the mid and long terms, and short and medium-terms to U.S. Dollar; but, from U.S. Dollar to stock market returns in the short-term. In the long-run, EURO exchange rate Granger cause to interest rate; but, interest rate Granger cause to EURO exchange rate in the short-run. On the other hand, there is no evidence of volatility spillovers from EURO and interest rate to stock market returns. Based on these results, we can conclude that there are certain degree of interdependence and volatility spillovers among the financial markets of Turkey, which have serious policy implications.
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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 | 0.002 | 0.002 |
| 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) | 0.004 | 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".