Trade size, high-frequency trading, and colocation around the world
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We examine the impact of changes in market microstructure, particularly algorithmic trading (AT) and high-frequency trading (HFT), on trade size across 24 stock exchanges around the world. Using colocation services as a proxy for AT and HFT, we find mixed results on the impact of AT and HFT on the average trade size. Furthermore, we test whether the presence of HFT leads to the introduction of colocation services. The data are consistent with the view that HFT pre-dates colocation by at least eight months on most exchanges, and has strong power in explaining the introduction of colocation services. In effect, our results show that colocation services do not properly measure effective AT and HFT; rather, colocation services are the result of HFT. Exchanges choose to offer colocation services due to the fact HFT requires higher speed transactions. Finally, we show there have been substantial changes in trade size in other countries such as China where there is no HFT and offer explanations for these changes and suggest avenues for future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it