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Same $500-a-month plan vs a lump sum across five stocks, 2016 to 2026 ($ thousands)

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 2026-07-16, from Does Dollar-Cost Averaging Work?.

as of ranking 5×3read in context →
Same $500-a-month plan vs a lump sum across five stocks, 2016 to 2026 ($ thousands) — 5 rows by 3 columns, computed from US exchange, SIP and OPRA data.
tickerdca_finallumpsum_final
MSFT199.4529.5
QQQ203.3427
SPY139.3237.7
JNJ95.8140.1
KO92.6116.8
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 Same $500-a-month plan vs a lump sum across five stocks, 2016 to 2026 ($ thousands), derived from the stored result.
ColumnTypeRangeNotes
ticker text 5 distinct values (JNJ, KO, MSFT…)
dca_final number 92.6 to 203.3
lumpsum_final number 116.8 to 529.5

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
monthly AS (
    SELECT ticker, toStartOfMonth(dt) AS mo, argMin(c, dt) AS px
    FROM (
        SELECT ticker, toDate(toTimeZone(window_start, 'America/New_York')) AS dt,
               argMax(toFloat64(close), window_start) AS c
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker IN ('SPY', 'QQQ', 'MSFT', 'JNJ', 'KO')
          AND window_start >= '2016-01-01 00:00:00' AND window_start < '2026-07-01 00:00:00'
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
               + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
        GROUP BY ticker, dt
    )
    GROUP BY ticker, mo
)
SELECT ticker,
       round(sum(500.0 / px) * argMax(px, mo) / 1000, 1) AS dca_final,
       round(sum(500.0) / argMin(px, mo) * argMax(px, mo) / 1000, 1) AS lumpsum_final
FROM monthly
GROUP BY ticker
HAVING count() = 126
ORDER BY lumpsum_final DESC

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