STRASMORE/EXPLORE 3,171 QUERIES

spread_aapl

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 2026-10-07, from us-premarket-and-after-hours-vietnam-time.

as of series 16×4read in context →
spread_aapl — 16 rows by 4 columns, computed from US exchange, SIP and OPRA data.
ict_timeet_timeavg_spread_bpsquote_count_thousands
15:0004:007.422
16:0005:005.930
17:0006:007.21
18:0007:005.391
19:0008:005.251
20:0009:002.03101
21:0010:001.22135
22:0011:000.98104
23:0012:000.8182
00:0013:000.6966
01:0014:000.6171
02:0015:000.65113
03:0016:004.461
04:0017:003.240
05:0018:003.871
06:0019:003.110
Rows × columns
16 × 4
Computed
Completeness
No missing values
Source
US exchange, SIP and OPRA market data
Licence
Strasmore terms · free, no signup
Formats
JSON · CSV · the SQL below

What each column holds

Column definitions for spread_aapl, derived from the stored result.
ColumnTypeRangeNotes
ict_time text 16 distinct values (00:00, 01:00, 02:00…)
et_time text 16 distinct values (04:00, 05:00, 06:00…)
avg_spread_bps number 0.61 to 7.42
quote_count_thousands number 0 to 135 count

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
        toTimeZone(sip_timestamp, 'America/New_York') AS et,
        toTimeZone(sip_timestamp, 'Asia/Ho_Chi_Minh') AS ict,
        10000 * toFloat64(ask_price - bid_price)
              / toFloat64((ask_price + bid_price) / 2) AS spread_bps
    FROM global_markets.cache_stocks_quotes
    WHERE ticker = 'AAPL'
      AND sip_timestamp >= toDateTime('2026-09-15 08:00:00')
      AND sip_timestamp <  toDateTime('2026-09-16 00:00:00')
      AND bid_price > 0
      AND ask_price > bid_price
      AND toFloat64(ask_price - bid_price) / toFloat64(bid_price) < 0.05
)
SELECT
    formatDateTime(ict, '%H:00')    AS ict_time,
    formatDateTime(et, '%H:00')     AS et_time,
    round(avg(spread_bps), 2)       AS avg_spread_bps,
    round(count() / 1000)           AS quote_count_thousands
FROM quotes
GROUP BY ict_time, et_time
ORDER BY et_time
⌘/Ctrl + Enter

Work with this data in your AI assistant

Opens ready to query, with this page's data. Free, no account.