Median spread each half hour, as a multiple of each name's tightest bucket (regular hours, ET)
Answered against 22 years of US equities and 12 years of US options data and published with the query that produced it. This result is stored as of 2026-10-04, from Why Are Spreads Wider at the Open? Real Data.
| et_time | spy_x | aapl_x | etsy_x |
|---|---|---|---|
| 09:30 | 1.01 | 3.01 | 5.25 |
| 10:00 | 1.01 | 2.45 | 3.27 |
| 10:30 | 1.01 | 1.99 | 2.41 |
| 11:00 | 1.01 | 1.99 | 1.87 |
| 11:30 | 1.01 | 1.52 | 2.02 |
| 12:00 | 1.01 | 1.5 | 2.11 |
| 12:30 | 1.01 | 1.5 | 1.76 |
| 13:00 | 1.01 | 1.49 | 1.74 |
| 13:30 | 1.01 | 1.49 | 1.6 |
| 14:00 | 1.01 | 1.48 | 1.58 |
| 14:30 | 1.01 | 1.48 | 1.5 |
| 15:00 | 1 | 1 | 1.26 |
| 15:30 | 1 | 1 | 1 |
- Rows × columns
- 13 × 4
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
et_time |
text | 13 distinct values (09:30, 10:00, 10:30…) | |
spy_x |
number | 1 to 1.01 | |
aapl_x |
number | 1 to 3.01 | |
etsy_x |
number | 1 to 5.25 |
Computed from Strasmore's warehouse of US exchange, SIP and OPRA market data. Equity prices are delayed; options greeks and implied volatility are end-of-day. This result is stored, not recomputed on load — it is exactly the numbers that were returned on , and the query below is what returned them.
Run it yourself
This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.
SELECT et_time,
round(anyIf(rel, ticker = 'SPY'), 2) AS spy_x,
round(anyIf(rel, ticker = 'AAPL'), 2) AS aapl_x,
round(anyIf(rel, ticker = 'ETSY'), 2) AS etsy_x
FROM (
SELECT ticker,
et_time,
median_bps / min(median_bps) OVER (PARTITION BY ticker) AS rel
FROM (
SELECT ticker,
formatDateTime(toStartOfInterval(toTimeZone(sip_timestamp, 'America/New_York'), INTERVAL 30 MINUTE), '%H:%i') AS et_time,
quantileExact(0.5)(toFloat64(ask_price - bid_price) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000) AS median_bps
FROM global_markets.cache_stocks_quotes
WHERE ticker IN ('SPY', 'AAPL', 'ETSY')
AND sip_timestamp >= toDateTime(today() - 14)
AND sip_timestamp < toDateTime(today() - 3)
AND (toHour(sip_timestamp) * 60 + toMinute(sip_timestamp)) BETWEEN 810 AND 1199
AND bid_price > 0
AND ask_price > bid_price
GROUP BY ticker, et_time
)
)
GROUP BY et_time
ORDER BY et_time
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