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?.
| ticker | dca_final | lumpsum_final |
|---|---|---|
| MSFT | 199.4 | 529.5 |
| QQQ | 203.3 | 427 |
| SPY | 139.3 | 237.7 |
| JNJ | 95.8 | 140.1 |
| KO | 92.6 | 116.8 |
- Rows × columns
- 5 × 3
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
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.
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
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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