Average quoted spread across six household names, one mid-morning hour
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 2026-10-08, from Stock Order Types Explained: The Core Four.
| symbol | spread_cents | spread_bps |
|---|---|---|
| SPY | 1.71 | 0.22 |
| NVDA | 1.57 | 0.73 |
| AAPL | 4.54 | 1.36 |
| KO | 1.22 | 1.38 |
| PG | 2.92 | 1.98 |
| MSFT | 12.82 | 2.6 |
- Rows × columns
- 6 × 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 |
|---|---|---|---|
symbol |
text | 6 distinct values (AAPL, KO, MSFT…) | |
spread_cents |
number | 1.22 to 12.82 | |
spread_bps |
number | 0.22 to 2.6 |
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
ticker AS symbol,
round(avg(toFloat64(ask_price - bid_price)) * 100, 2) AS spread_cents,
round(avg(toFloat64(ask_price - bid_price)
/ toFloat64((ask_price + bid_price) / 2)) * 10000, 2) AS spread_bps
FROM global_markets.cache_stocks_quotes
WHERE ticker IN ('SPY', 'AAPL', 'MSFT', 'NVDA', 'KO', 'PG')
AND sip_timestamp >= toDateTime('2026-09-16 14:00:00')
AND sip_timestamp < toDateTime('2026-09-16 15:00:00')
AND bid_price > 0
AND ask_price > bid_price
GROUP BY ticker
ORDER BY spread_bps
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.