STRASMORE/EXPLORE 2,985 QUERIES

turnover_tiers

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 2026-10-03, from does-ipo-gmp-predict-listing-gains.

as of ranking 4×4read in context →
turnover_tiers — 4 rows by 4 columns, computed from US exchange, SIP and OPRA data.
day1_turnover_tierlistingsmedian_offer_to_open_pctp10_to_p90_spread
under $5M traded17812.161672.8
$5M to $50M6521.21917.8
$50M to $500M8943.864.1
$500M and up15232.8103.9
Rows × columns
4 × 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 turnover_tiers, derived from the stored result.
ColumnTypeRangeNotes
day1_turnover_tier text 4 distinct values ($500M and up, $50M to $500M, $5M to $50M…)
listings number 152 to 894
median_offer_to_open_pct number 1.2 to 32.8 percent
p10_to_p90_spread number 64.1 to 61,672.8

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 day_one AS
(
    SELECT
        i.ticker                                          AS ticker,
        i.list_date                                       AS list_date,
        (toFloat64(d.open_px) / i.offer_price - 1) * 100  AS offer_to_open,
        toFloat64(d.open_px) * toFloat64(d.day_volume)    AS day1_turnover
    FROM
    (
        SELECT
            ticker,
            toDate(argMax(listing_date, last_updated))         AS list_date,
            argMax(toFloat64(final_issue_price), last_updated) AS offer_price
        FROM global_markets.stocks_ipos
        WHERE listing_date >= '2017-01-01'
          AND listing_date <  '2026-09-01'
          AND final_issue_price > 0
          AND currency_code = 'USD'
          AND ticker NOT IN ('SPCX')
        GROUP BY ticker
    ) AS i
    INNER JOIN
    (
        SELECT
            ticker,
            date,
            max(open)   AS open_px,
            max(volume) AS day_volume
        FROM global_markets.stocks_daily_aggs
        WHERE date >= '2017-01-01'
          AND date <  '2026-09-01'
        GROUP BY ticker, date
    ) AS d
        ON d.ticker = i.ticker AND d.date = i.list_date
    WHERE d.day_volume > 0
      AND d.open_px > 0
      AND i.offer_price > 0
)
SELECT
    multiIf(day1_turnover <   5000000, 'under $5M traded',
            day1_turnover <  50000000, '$5M to $50M',
            day1_turnover < 500000000, '$50M to $500M',
                                       '$500M and up') AS day1_turnover_tier,
    count()                                            AS listings,
    round(quantileDeterministic(0.5)(offer_to_open, cityHash64(ticker)), 1) AS median_offer_to_open_pct,
    round(quantileDeterministic(0.9)(offer_to_open, cityHash64(ticker))
        - quantileDeterministic(0.1)(offer_to_open, cityHash64(ticker)), 1) AS p10_to_p90_spread
FROM day_one
GROUP BY day1_turnover_tier
ORDER BY min(day1_turnover)
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