The Dynamic Relationship Between Stock, Bond and Foreign Exchange Markets
Bibliographic record
Abstract
In this paper, we investigate whether deviation of a currency from its fundamentally determined rate of return affects its interaction with interest rates and stock market yields. A time varying transition probability Markov-Switching Vector Autoregressive (MS-VAR) model is utilized for this purpose. Wald and Likelihood ratio tests are used as model adequacy measures. In order to analyse the link among the variables, impulse-response functions are employed. States are defined as overvalued state and undervalued state depending on the position of the observed exchange rate to its fundamentally determined rate which is computed by sticky price exchange rate model. The model is implemented to four major currencies: Australian dollar, the Canadian dollar, the Japanese yen, and the British pound. Transition between the states are linked to risk adjusted excess return (the Sharpe ratio) of debt market and equity market returns of respected currencies in order to understand whether overvaluation and undervaluation is connected to the returns in these markets. The results provide evidence that the relationship between economic fundamentals and the nominal exchange rates are subject to change depending on the overvaluation or undervaluation of the currencies relative to their fundamentally determined rate of return. As an extension of the model, we found that the Sharpe ratios of debt and equity investments in the currencies influence the evolution of transitional dynamics of the exchange rates� deviation from their fundamental values.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".