Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk
Why this work is in the frame
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Bibliographic record
Abstract
We study the temporal behavior of the cross‐sectional distribution of assets' market exposure, or betas, using a large panel of high‐frequency returns. The asymptotic setup has the sampling frequency of returns increasing to infinity, while the time span of the data remains fixed, and the cross‐sectional dimension of the panel is either fixed or increasing. We derive functional limit results for the cross‐sectional distribution of betas evolving over time. We demonstrate, for constituents of the S&P 500 market index, that the dispersion in betas is elevated at the market open and gradually declines over the trading day. This intraday pattern varies significantly over time and reacts to information shocks such as clustered earning announcements and releases of macroeconomic news. We find that earnings news increase beta dispersion while FOMC announcements have the opposite effect on market betas.
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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 | 0.001 | 0.001 |
| 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