The same curve, split by print size: small fills against blocks
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 2026-08-15, from Trade Markouts Explained: Execution Quality.
| horizon | small_fill_bps | block_fill_bps | block_fill_count |
|---|---|---|---|
| 1 sec | 3.073 | 2.651 | 11604 |
| 5 sec | 2.86 | 2.518 | 11592 |
| 15 sec | 2.779 | 2.686 | 11596 |
| 1 min | 3.81 | 3.445 | 11594 |
| 5 min | 2.983 | 2.495 | 11588 |
- Rows × columns
- 5 × 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 |
|---|---|---|---|
horizon |
text | 5 distinct values (1 min, 1 sec, 15 sec…) | |
small_fill_bps |
number | 2.779 to 3.81 | |
block_fill_bps |
number | 2.495 to 3.445 | |
block_fill_count |
number | 11,588 to 11,604 | 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
mid_by_second AS
(
SELECT
dateDiff('second', toDateTime('2026-06-10 13:30:00', 'UTC'), sip_timestamp) AS sec,
argMax((toFloat64(bid_price) + toFloat64(ask_price)) / 2, sip_timestamp) AS mid
FROM global_markets.cache_stocks_quotes
WHERE ticker = 'INTC'
AND sip_timestamp >= toDateTime('2026-06-10 13:30:00', 'UTC')
AND sip_timestamp < toDateTime('2026-06-10 20:00:00', 'UTC')
AND bid_price > 0
AND ask_price > bid_price
GROUP BY sec
),
signed_fills AS
(
SELECT
t.sec AS sec,
t.fill_size AS fill_size,
q.mid AS ref_mid,
if(t.fill_price > q.mid, 1, -1) AS side
FROM
(
SELECT
dateDiff('second', toDateTime('2026-06-10 13:30:00', 'UTC'), sip_timestamp) AS sec,
sec - 1 AS ref_sec,
toFloat64(price) AS fill_price,
size AS fill_size
FROM global_markets.stocks_trades
WHERE ticker = 'INTC'
AND sip_timestamp >= toDateTime('2026-06-10 13:30:01', 'UTC')
AND sip_timestamp < toDateTime('2026-06-10 19:55:00', 'UTC')
AND price > 0
AND size > 0
) AS t
INNER JOIN mid_by_second AS q ON q.sec = t.ref_sec
WHERE t.fill_price != q.mid
)
SELECT
multiIf(f.horizon_s < 60,
concat(toString(f.horizon_s), ' sec'),
concat(toString(intDiv(f.horizon_s, 60)), ' min')) AS horizon,
round(avgIf(f.side * (fut.mid - f.ref_mid) / f.ref_mid, f.fill_size < 1000) * 10000, 3) AS small_fill_bps,
round(avgIf(f.side * (fut.mid - f.ref_mid) / f.ref_mid, f.fill_size >= 1000) * 10000, 3) AS block_fill_bps,
countIf(f.fill_size >= 1000) AS block_fill_count
FROM
(
SELECT
sec,
fill_size,
ref_mid,
side,
horizon_s,
sec + horizon_s AS future_sec
FROM signed_fills
ARRAY JOIN [1, 5, 15, 60, 300] AS horizon_s
) AS f
INNER JOIN mid_by_second AS fut ON fut.sec = f.future_sec
GROUP BY f.horizon_s
HAVING countIf(f.fill_size < 1000) > 0
AND countIf(f.fill_size >= 1000) > 0
ORDER BY f.horizon_s
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.