PIP Transactions, Price Improvement, Informed Trades and Order Execution Quality
Bibliographic record
Abstract
Abstract This study focuses on innovations in order execution processes within the context of the Boston Option Exchange (BOX). More specifically, it examines the impact of the Price Improvement Process (PIP) on options quoted, effective and realised proportional spreads. We consider the PIP as a mechanism that allows the market maker to ‘internalise’ the transaction. We show that PIP transactions are associated with wider bid/ask proportional quoted spreads than non‐PIP transactions, in spite of the temporary narrowing of the effective proportional spread during PIP. We identify informed traders by focusing on the direction of trade. Using an original data set, we show that PIP transactions follow signals in the form of buy/sell orders by informed traders. We also show that PIP is a mechanism that allows the market maker to internalise a position in the same direction as that of the informed trader. We conclude that PIP does not improve the efficiency of the market but simply allows the market maker to benefit at the expense of uninformed traders.
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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 | 0.006 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".