A Simultaneous Equations Model of Returns, Volatility, And Volume With Intraday Trading Dynamics
Bibliographic record
Abstract
This paperextends the finance literature by modeling stock returns, volatility, andvolume in a simultaneous equations model while incorporating the effects oftrading dynamics on these three variables. Evidence shows that returns, volatility, and volume are interrelated. However, research typically examined them asthree separate relationships between each pair of the three variables. Priorliterature has also failed to examine the impact of intraday trading dynamicson returns, volatility, and volume. Thisstudy overcomes both limitations. Usinga simultaneous equations model that incorporates feedbacks among these threevariables, this study documents that intraday skewness hassignificant impacts on daily returns, volatility, and volume. In addition, the two-way relationshipsbetween the variables change significantly when they are estimatedsimultaneously. The findings in thisstudy deepen our understanding of the relationships between returns,volatility, and volume and have important implications for traders, portfoliomanagers, and other market participants.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".