STRASMORE/EXPLORE 3,214 QUERIES

A naive open-to-close yardstick, netted against a ladder of slippage assumptions

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 How Much Slippage to Assume in a Backtest.

as of ranking 6×4read in context →
A naive open-to-close yardstick, netted against a ladder of slippage assumptions — 6 rows by 4 columns, computed from US exchange, SIP and OPRA data.
assumed_slippage_bpsnames_testednames_still_positiveavg_net_edge_bps
01072.04
0.51061.04
11060.04
2105-1.96
3103-3.96
5102-7.96
Rows × columns
6 × 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 A naive open-to-close yardstick, netted against a ladder of slippage assumptions, derived from the stored result.
ColumnTypeRangeNotes
assumed_slippage_bps number 0 to 5
names_tested number every row is 10
names_still_positive number 2 to 7
avg_net_edge_bps number -7.96 to 2.04

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
    naive_rule AS
    (
        SELECT
            ticker,
            round(avg((toFloat64(close) / toFloat64(open) - 1) * 10000), 3) AS gross_edge_bps
        FROM global_markets.stocks_daily_aggs
        WHERE ticker IN ('SPY', 'AAPL', 'MSFT', 'NVDA', 'KO', 'JNJ', 'XOM', 'PG', 'WMT', 'JPM')
          AND date >= '2026-01-02'
          AND date <  '2026-07-01'
          AND open > 0
          AND volume > 0
        GROUP BY ticker
    ),
    ladder AS
    (
        SELECT arrayJoin([0., 0.5, 1., 2., 3., 5.]) AS slippage_bps
    )
SELECT
    l.slippage_bps                                        AS assumed_slippage_bps,
    count()                                               AS names_tested,
    countIf(r.gross_edge_bps - 2 * l.slippage_bps > 0)    AS names_still_positive,
    round(avg(r.gross_edge_bps - 2 * l.slippage_bps), 2)  AS avg_net_edge_bps
FROM naive_rule AS r
CROSS JOIN ladder AS l
GROUP BY l.slippage_bps
ORDER BY assumed_slippage_bps
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