STRASMORE/EXPLORE 3,293 QUERIES

SPY: share of sessions that swept the prior day's high or low, by year

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 2026-09-28, from What Is a Liquidity Sweep in Trading?.

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SPY: share of sessions that swept the prior day's high or low, by year — 5 rows by 3 columns, computed from US exchange, SIP and OPRA data.
yearhigh_sweep_pctlow_sweep_pct
202124.616.3
202217.120.3
202319.221.6
202423.417.1
202522.818.8
Rows × columns
5 × 3
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 SPY: share of sessions that swept the prior day's high or low, by year, derived from the stored result.
ColumnTypeRangeNotes
year number 2,021 to 2,025
high_sweep_pct number 17.1 to 24.6 percent
low_sweep_pct number 16.3 to 21.6 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.

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
    toYear(date)                                                          AS year,
    round(100.0 * countIf(hi > prior_hi AND cl < prior_hi) / count(), 1)  AS high_sweep_pct,
    round(100.0 * countIf(lo < prior_lo AND cl > prior_lo) / count(), 1)  AS low_sweep_pct
FROM
(
    SELECT
        date,
        hi,
        lo,
        cl,
        lagInFrame(hi) OVER (ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_hi,
        lagInFrame(lo) OVER (ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_lo
    FROM
    (
        SELECT
            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 = 'SPY'
          AND date >= '2020-12-31'
          AND date <  '2026-01-01'
        GROUP BY date
    )
)
WHERE date >= '2021-01-01'
  AND prior_hi > 0
GROUP BY year
ORDER BY year
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More from this analysisWhat Is a Liquidity Sweep in Trading?
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