Liquidity Efficiency and Distribution in the LVTS: Non-Neutrality of System Changes under Network Asymmetry
Bibliographic record
Abstract
The authors consider the liquidity efficiency of Tranche 2 of the Large Value Transfer System (LVTS T2) by examining, through an empirical analysis, some plausible strategic reactions of individual participants to a systemwide shock to available liquidity in the system. The network structure of the LVTS T2 is found to be asymmetric in terms of the patterns of out-payment flows. It is composed of three subgroups, in which participants within a subgroup are more strongly linked with each other than with participants in other subgroups. Three possible network equilibria are proposed. The equilibria are defined in terms of participant-specific collateral needs and out-payment delays, and result from different relative cost structures involving collateral costs, queuing costs, and payment delay penalties. Each of the conjectural equilibria relate to a dominant strategy for at least those participants most central in the network with respect to liquidity transfer adopted network-wide as a common strategy.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".