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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".