Bibliographic record
Abstract
To open our issue, we have Kissell and Malamut's discussion of traditional VWAP strategy and its inconsistency with investment objectives. They demonstrate its likelihood to compromise the stock selection process. Garvey and Wu examine the effect of prior outcomes on order selection decisions. They conclude that the trader's behavior appears sub-optimal because traders who systematically deviate from their normal order submission strategies experience lower profitability. This is followed by Borkovec and Heidle who present a model to improve transaction cost estimates for post-trade analysis. Cheng extends previous research on how overconfidence affects trading performance by examining whether the degree of impact is different between electronic trading markets and open outcry environments. Berkeley discusses the need for invisibility of order for the success of block traders. Chlistalla, Gomber, and Groth discuss MiFID and its impact on the European landscape of execution venues. Selway provides four proposals for the NYSE to turn around the Hybrid platform. We are pleased to have as a special editor for this issue Professor Guo Ying (Rosemary)Luo, Associate Professor of Finance at the DeGroote School of Business of McMaster University. She brings us two articles that were presented at the Annual Conference on Market Structure and Market Integrity for 2005 and 2006 (website: http://www.degroote.mcmaster.ca/faculty/rsconference07.aspx). This conference is sponsored by the DeGroote School of Business at McMaster University and Market Regulation Services Inc. As always, we welcome your submissions. Please encourage those you know who have good papers or have made good presentations on trading related subjects to submit them to us. Submission guidelines are included in this issue. We value your comments and suggestions, so please email us at journals@investmentresearch.org. Brian Bruce Editor-in-Chief I gratefully acknowledge The Journal of Trading for supporting the publication of the aforementioned articles. The first article examines the transaction costs for the two derivatives traded on the Montreal Exchange, namely, the BAX (the interest rate futures contracts) and the SXF (the equity futures contracts). The results show that the trading costs on the BAX are much less than its minimum tick value and are similar to the costs of Eurodollar futures on the Chicago Mercantile Exchange (CME); and the transaction costs on the SXF are much higher than the contract's minimum tick value and exceed those of the CME S&P 500 index futures contracts. Hedging appears to reduce the transaction costs for all participants. There is almost no correlation between transaction costs and trading activity. The second article investigates the frontrunning activities in the Toronto Stock exchange. Frontrunning is referred to as brokers' proprietary trading activities ahead of executing their clients' orders. The results show that only a small number of brokers have engaged in frontrunning trading activities. The paper further identifies positive association between the magnitude and frequency of frontrunning activities with broker activity levels, order size, sell-side orders, and informed client orders. There is no evidence to support investors' common perceptions that anonymous orders are used to conceal frontrunning activities. Guo Ying (Rosemary) Luo Special Editor
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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 | 0.003 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.017 | 0.015 |
| Insufficient payload (model declined to judge) | 0.068 | 0.043 |
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".