Principal Trading Arrangements: When Are Common Contracts Optimal?
Bibliographic record
Abstract
Many financial arrangements reference market prices that are yet to be realized at the time of contracting and consequently susceptible to manipulation. Two of the most common such arrangements are as follows: (i) guaranteed volume-weighted average price (VWAP) contracts, which reference the VWAP prevailing over an execution window, and (ii) market-on-close contracts, which reference the price prevailing at the window’s end. To study such situations, we introduce a stylized model of financial contracting between a client, who wishes to trade a large position, and the client’s dealer. We provide conditions under which guaranteed VWAP contracts are optimal in this principal-agent problem. In contrast, market-on-close contracts generally cannot be optimal. These results explain the use of guaranteed VWAP contracts in practice, question the use of market-on-close contracts, and suggest considerations for the design of financial benchmarks. This paper was accepted by Haoxiang Zhu, finance.
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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 | 0.016 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.007 | 0.020 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".