Realized volatility, jump and beta: evidence from Canadian stock market
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
Inclusion of jump component in the price process has been a long debate in finance literature. In this paper, we identify and characterize jump risks in the Canadian stock market using high-frequency data from the Toronto Stock Exchange. Our results provide a strong evidence of jump clustering - about 90% of jumps occur within first 30 minutes of market opening for trade, and about 55% of jumps are due to the overnight returns. While average intraday jump is negative, jumps induced by overnight returns bring a cancellation effect \nyielding average size of the jumps to zero. We show that the economic significance of jump component in volatility forecasting is very nominal. Our results further demonstrate that market jumps and overnight returns bring significant changes in systematic risk (beta) of stocks. While the average effect of market jumps on beta is not significantly different than zero, the effect of overnight returns on beta is significant. Overall, our results suggest that jump risk is non-systematic in nature.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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