STRASMORE/EXPLORE 2,401 QUERIES

base_rate

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 2026-09-19, from what-is-a-liquidity-sweep.

as of table 7×6read in context →
base_rate — 7 rows by 6 columns, computed from US exchange, SIP and OPRA data.
tickersession_counthigh_sweep_counthigh_sweep_pctlow_sweep_countlow_sweep_pct
AAPL125527121.625820.6
JPM125528222.525920.6
KO125528822.930224.1
MSFT125526621.226721.3
NVDA12552512025620.4
QQQ125524619.624819.8
SPY125526921.423618.8
Rows × columns
7 × 6
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 base_rate, derived from the stored result.
ColumnTypeRangeNotes
ticker text 7 distinct values (AAPL, JPM, KO…)
session_count number every row is 1,255 count
high_sweep_count number 246 to 288 US dollars
high_sweep_pct number 19.6 to 22.9 percent
low_sweep_count number 236 to 302 US dollars
low_sweep_pct number 18.8 to 24.1 percent

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.

the exact SQL behind every number
SELECT
    ticker,
    count()                                                               AS session_count,
    countIf(hi > prior_hi AND cl < prior_hi)                              AS high_sweep_count,
    round(100.0 * countIf(hi > prior_hi AND cl < prior_hi) / count(), 1)  AS high_sweep_pct,
    countIf(lo < prior_lo AND cl > prior_lo)                              AS low_sweep_count,
    round(100.0 * countIf(lo < prior_lo AND cl > prior_lo) / count(), 1)  AS low_sweep_pct
FROM
(
    SELECT
        ticker,
        date,
        hi,
        lo,
        cl,
        lagInFrame(hi) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_hi,
        lagInFrame(lo) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_lo
    FROM
    (
        SELECT
            ticker,
            date,
            argMax(high,  _ingest_time) AS hi,
            argMax(low,   _ingest_time) AS lo,
            argMax(close, _ingest_time) AS cl
        FROM global_markets.stocks_daily_aggs
        WHERE ticker IN ('SPY', 'QQQ', 'AAPL', 'MSFT', 'NVDA', 'JPM', 'KO')
          AND date >= '2020-12-31'
          AND date <  '2026-01-01'
        GROUP BY ticker, date
    )
)
WHERE date >= '2021-01-01'
  AND prior_hi > 0
GROUP BY ticker
ORDER BY ticker

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