Average quoted spread by ET half hour: AAPL and KO, Friday July 17, 2026
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 2026-08-02, from Learn Quant Trading From an Open Source Book.
| et_time | aapl_spread_bps | ko_spread_bps |
|---|---|---|
| 09:00 | 10.53 | 28.87 |
| 09:30 | 2.38 | 3.32 |
| 10:00 | 1.9 | 2.41 |
| 10:30 | 1.44 | 1.97 |
| 11:00 | 1.27 | 1.78 |
| 11:30 | 1.21 | 1.6 |
| 12:00 | 1.35 | 1.58 |
| 12:30 | 1.42 | 1.49 |
| 13:00 | 1.17 | 1.43 |
| 13:30 | 1.02 | 1.44 |
| 14:00 | 0.94 | 1.33 |
| 14:30 | 1.05 | 1.43 |
| 15:00 | 0.88 | 1.35 |
| 15:30 | 1.01 | 1.34 |
| 16:00 | 4.54 | 8.47 |
| 16:30 | 3.27 | 8.04 |
- Rows × columns
- 16 × 3
- 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 | 16 distinct values (09:00, 09:30, 10:00…) | |
aapl_spread_bps |
number | 0.88 to 10.53 | |
ko_spread_bps |
number | 1.33 to 28.87 |
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.
WITH quotes AS (
SELECT ticker,
toStartOfInterval(toTimeZone(sip_timestamp, 'America/New_York'), INTERVAL 30 MINUTE) AS bucket,
toFloat64(ask_price - bid_price) / toFloat64((ask_price + bid_price) / 2) * 10000 AS spread_bps
FROM global_markets.cache_stocks_quotes
WHERE ticker IN ('AAPL', 'KO')
AND sip_timestamp >= toDateTime('2026-07-17 13:00:00')
AND sip_timestamp < toDateTime('2026-07-17 21:00:00')
AND bid_price > 0
AND ask_price > bid_price
)
SELECT formatDateTime(bucket, '%H:%i') AS et_time,
round(avgIf(spread_bps, ticker = 'AAPL'), 2) AS aapl_spread_bps,
round(avgIf(spread_bps, ticker = 'KO'), 2) AS ko_spread_bps
FROM quotes
WHERE spread_bps > 0 AND spread_bps < 500
GROUP BY et_time
HAVING countIf(ticker = 'AAPL') > 0 AND countIf(ticker = 'KO') > 0
ORDER BY et_time
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.