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A 20/50 moving-average crossover on SPY, year by year, against holding

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 2026-08-06, from Reproducible Backtest in Python, No API Key.

as of ranking 9×4read in context →
A 20/50 moving-average crossover on SPY, year by year, against holding — 9 rows by 4 columns, computed from US exchange, SIP and OPRA data.
yearrule_pcthold_pctcrossover_count
20171619.44
20186.1-6.33
20197.628.75
202017.416.14
202118.7272
2022-24.7-19.56
20239.424.36
20241323.34
202510.416.44
Rows × columns
9 × 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 20/50 moving-average crossover on SPY, year by year, against holding, derived from the stored result.
ColumnTypeRangeNotes
year number 2,017 to 2,025
rule_pct number -24.7 to 18.7 percent
hold_pct number -19.5 to 28.7 percent
crossover_count number 2 to 6 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.

the exact SQL behind every number
WITH daily AS
(
    SELECT
        toDate(toTimeZone(window_start, 'America/New_York')) AS d,
        toFloat64(argMax(close, window_start))               AS px
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= '2016-01-01 00:00:00'
      AND window_start <  '2026-01-01 05:00:00'
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) >= 570
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) < 960
    GROUP BY d
),
averaged AS
(
    SELECT
        d,
        px,
        avg(px) OVER (ORDER BY d ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS fast_ma,
        avg(px) OVER (ORDER BY d ROWS BETWEEN 49 PRECEDING AND CURRENT ROW) AS slow_ma,
        row_number() OVER (ORDER BY d)                                      AS session_no
    FROM daily
),
positioned AS
(
    SELECT
        d,
        px,
        if(session_no >= 50 AND fast_ma > slow_ma, 1, 0) AS long_today,
        lagInFrame(if(session_no >= 50 AND fast_ma > slow_ma, 1, 0), 1)
            OVER (ORDER BY d ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS long_prior,
        lagInFrame(px, 1)
            OVER (ORDER BY d ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS px_prior
    FROM averaged
)
SELECT
    toYear(d)                                                                   AS year,
    round((exp(sum(log(if(long_prior = 1, px / px_prior, 1.0)))) - 1) * 100, 1) AS rule_pct,
    round((exp(sum(log(px / px_prior))) - 1) * 100, 1)                          AS hold_pct,
    countIf(long_today != long_prior)                                           AS crossover_count
FROM positioned
WHERE px_prior > 0
  AND toYear(d) >= 2017
GROUP BY year
ORDER BY year

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