Bibliographic record
Abstract
We study the intra-day trading profits and losses of retail, institutional, and high frequencytraders from 2006 to 2012, usinggranular trader-level data fromthe Toronto Stock Exchange and analyze the evolution in trading costs for traders who trade with both market and limit orders. Retail investors make persistent intra-day trading losses, institutional investors earn positive profits, and high frequency trading (HFT) profits decline over time. HFT activities are associated with a reduction in retail traders ’ liquidity costs and in the trading losses that are attributed to adverse future price movements. Institutional traders ’ profits are positively related to retail trading activities but unrelated to HFT activities. Retail losses add up to almost half a billion dollars over our six year sample, and only a small portion of these losses can be attributed to direct bid-ask spread costs – the remainder are due to adverse intra-day price movements. Financial supportfrom the SSHRC isgratefullyacknowledged. TheTorontoStock Exchange(TSX) and Alpha Trading kindly provided us with databases. The views expressed here are those of the authors and
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.501 | 0.184 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".