Foreign Exchange Forecasting and Leading Ecomonic Indicators: The U.S. -Canadian Experience
Bibliographic record
Abstract
The relationship between the value of currency or foreign exchange between two nations has been explained by Giddy (1976) using four related theories: 1 . The purchasing power parity theory 2. The interest rate parity theory 3. The interest rate theory of exchange rate expectations and 4. The forward rate theory of exchange rate expectations. Four main factors determine a country's international payments and receipts and therefore its demand and supply for currency: real income relative to foreign income number 1 above; the rate of domestic inflation relative to inflation in the foreign country numbers 3 and 4 above; the rate of interest in domestic markets relative to interest rates in foreign country number 2 above; and random factors such as resource discoveries and political decisions. The higher the country's real income, or growth of its real GNP, the greater the volume of imports and the greater the demand for foreign currencies. If the domestic country's rate of inflation rises relative to the rest of the world, its products become less competitive relative to foreign goods and the demand for foreign currency increases. The higher the rate of interest in a country, the more foreign capital will flow into the country's financial markets, the greater demand for its currency. Random events will have either positive or negative effects and should not systematically effect the currency relationship over long periods of time. If these events and the relative changes of these events between two countries are related to leading economic indicators, then we can hypothesize a relationship between the relative movements of a country's leading economic indicators and the movement of the foreign exchange rates both spot and forward. The purpose of this paper is to investigate the relationship between leading economic indicators of two countries and the foreign exchange rates of those countries. Section I contains a review of the literature on foreign exchange forecasting and market efficiency. Section II contains a description of the data and methodology of this study. The results of the analysis are presented in Section III. Implications and conclusions are given in the final section.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.014 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".