An Information Approach to International Currencies
Bibliographic record
Abstract
This paper addresses currency competition from an information perspective. Transactions in traditional models do not convey information, so transaction costs -the driver of competition outcomes -are driven by market size. In our model transactions do convey information (consistent with recent empirical findings). Several important departures arise. First, adding the information dimension resolves the traditional indeterminacy of currency trade patterns (by mitigating the concentrating force of market-size economies). Second, whether transactions are executed directly or through a vehicle actually affects prices (because these trading methods do not in general reveal the same information). Third, our model provides a new rationale for why some currency pairs never trade directly (information is not sufficiently symmetric to support trading). Fourth, our model formalizes the arbitrage process and shows that arbitrage transaction quantities and price levels are jointly determined. Empirically, the paper provides a first integrated analysis of transactions in a triangle of markets: /$, $/ , and / . Data for the full triangle permits comparison of direct, indirect and arbitrage transactions, for each pair. The information model predicts that transactions should affect prices across markets (e.g., flow in the /$ market should convey information relevant to $/ and / prices), which is borne out.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".