SMCI: Is the day's volatility set by the first 30 minutes? Opening-range vs rest-of-day range
The opening 30 minutes of SMCI carry a clear signal: across 750 NY-session days the initial high–low captures about 62% of the day's final range and correlates positively with the remaining session (Pearson r ≈ 0.55). An OLS fit implies the open explains roughly 30% of the variation in the rest-of-day range — big opens tend to be followed by bigger remaining sessions, but a large share of volatility still comes later.
This study measured 09:30–10:00 and 10:00–16:00 minute-bar ranges normalized to the prior close, then ran Pearson/Spearman correlations, a rolling 60-day correlation, tercile buckets, and an OLS regression. The detailed statistics, charts, and tercile breakdown below show how useful the opening width is as a real-time volatility gauge — and where its limits lie.
For SMCI over the past ~3 years, does the size of the opening 30-minute high-low range (9:30–10:00) predict how wide the rest of the session (10:00–16:00) trades — is the day's turbulence essentially locked in by the first half hour? Thesis: the opening-range width is strongly positively correlated with the remaining-day range, so a violent open reliably begets a violent day and you can gauge a session's volatility from its first thirty minutes rather than sitting through it.
How this was measured
Filtered SMCI minute bars to NY-regular session (Mon–Fri, 09:30–16:00 ET) over the last ~3 years. For each session, computed the opening 30-minute range as max(high)−min(low) from 09:30–10:00 and the remaining-day range as max(high)−min(low) from 10:00–16:00. Both ranges were normalized by the prior session close to make them comparable across price levels. Measured Pearson/Spearman correlations and an OLS fit of rest-range on open-range; also reported a 60-session rolling correlation and a tercile bucket view of rest-range by opening-range size.
The key numbers
Reading the numbers
The opening 30-minute range is meaningfully linked to the rest of the session: Pearson r = 0.547 (p=0.0000) and the OLS slope is ~0.776 (r^2 = 0.300). On average the first 30 minutes already capture about 62.03% of the day's final high‑low range.
The charts
The scatter shows an upward-sloping cloud: larger opening 30‑min ranges (x runs from 0.0113 to 0.1601, mean 0.0396) tend to occur with larger rest‑of‑day ranges (y runs 0.0117–0.25, mean 0.0547). Look at the general upward tilt of the points rather than any single dot — that tilt is the 0.547 Pearson relationship reported above. In plain terms, a violent open usually accompanies a more turbulent remainder of the day, but the spread of points (overlapping x and y values) also shows it is not a perfect one‑to‑one lock.
The 60‑session rolling Pearson r moves a lot over time (60‑session series: mean 0.4077, range 0.0314–0.7584), starting near 0.3891 and ending around 0.3315. The takeaway is that the open-vs-rest association has been intermittently much stronger or weaker — sometimes very predictive (peaks near 0.76) and sometimes nearly absent (lows near 0.03). So the historical average positive link exists, but its predictive strength is time-varying rather than constant.
The box/tercile view summarizes the practical effect: mean rest‑of‑day range rises across terciles from 0.0414 (low open) to 0.0510 (mid) to 0.0719 (high open). Note the overlap in minima and maxima (low min 0.0117 max 0.1555; high min 0.0223 max 0.25), which means high opening-range days typically lead to bigger remaining ranges on average but you will still see large rest‑of‑day moves following smaller opens and vice versa. In short, opening width is a useful, not infallible, signal of how wide the rest of the session will trade.
Rest-of-day range summary by opening-range tercile
| bucket | N | mean_rest_range | std_rest_range |
|---|---|---|---|
| Low opening-range | 250 | 0.0414 | 0.0186 |
| Mid opening-range | 250 | 0.051 | 0.026 |
| High opening-range | 250 | 0.0719 | 0.0373 |
The takeaway
Yes — a wider opening 30-minute high–low is meaningfully associated with a wider remainder of the session, but it is not destiny. Over 750 sessions the Pearson r is 0.547 (p≈0), so this is very unlikely to be random, and the OLS slope of 0.776 with r²=0.30 means opening-range explains about 30% of the variation in the rest-of-day range. On average the open is 3.96% of prior close versus 5.47% for the rest of the day, and the first 30 minutes capture about 62.0% of the final high–low on a typical day. The terciles line up cleanly: mean rest-range rises from 4.14% (low open) to 5.10% (mid) to 7.19% (high), so big opens tend to be followed by bigger remaining sessions. Practical takeaway: use the opening 30-minute width as a real-time volatility gauge — it gives a reasonably strong read, but expect substantial unexplained noise (roughly 70% of variance remains).
The fine print
- Ranges are normalized to the prior close to reflect what’s knowable at 09:30.
- Half-days and irregular sessions remain in-sample and can mechanically reduce the 10:00–16:00 range.
- Tercile buckets and correlations are in-sample; out-of-sample regime shifts may change performance.
- High–low range measures dispersion only; identical ranges can hide very different intraday paths.