Invest now or spread twelve purchases?
If $12,000 is already available, how did investing it immediately compare with twelve $1,000 purchases in this snapshot? We run both schedules from every eligible starting month. Each comparison commits the same $12,000 and ends on the same observation. This is a test of delayed deployment of existing cash, not a test of saving from future paychecks.
Lump sum finished ahead in 141 of 181 windows (77.90%); staged purchases finished ahead in 40. The median lump-sum advantage was $712.43. These are sample counts, not forecast odds.
| Scenario | Start | End | Lump sum | Twelve purchases | Lump minus staged |
|---|---|---|---|---|---|
| Largest lump advantage | 2020-04-01 | 2021-03-01 | $18,952.37 | $14,264.02 | $4,688.35 |
| Largest staged advantage | 2022-01-03 | 2022-12-01 | $10,198.73 | $11,813.51 | $-1,614.78 |
Why the cash schedule matters
When the index rises after entry, investing earlier exposes more of the capital to that rise. When prices fall early, the staged schedule can buy more units later. The same mechanism can help or hurt; a lower average purchase price is not guaranteed and is not itself a measure of profit. The worst ending wealth across this sample was $9,567.47 for lump sum and $10,022.42 for staged purchases. Those minima may come from different windows.
Method and fair comparison
At the first observation, lump sum buys $12,000/P[0] units. The staged schedule buys $1,000/P[t] at each of twelve observations t=0 through 11, including the final valuation date. Ending values are units multiplied by P[11]. There are eleven monthly intervals between the twelve purchases: this is not a twelve-month holding-period return. Idle cash earns zero and remains part of the investor's wealth until spent; all of it is invested by the final observation.
We use every consecutive twelve-observation block, including overlapping blocks, and report the full CSV rather than only the winning scenarios. No CAGR is calculated on staged contributions: cash enters at different times. A spreadsheet can sum 1000/close across a block and multiply by its last close.
Replay in the simulator
Choose S&P 500 and one start/end month pair above. Run Single mode first with $12,000 initial and $0 monthly, then with $0 initial and $1,000 monthly. The tool makes a contribution on the first and final observations, so confirm that twelve contributions total $12,000. Compare ending dollars, not the two displayed percentages as if capital had identical time in the market.
Limits and external context
This result excludes dividends, interest on waiting cash, tax, inflation, and fund costs. Paying interest on idle cash would improve the staged result. A different staging duration or market history may change both the win count and size of the gap. Adjacent windows are dependent. Payroll contributions are a different decision because money not yet earned cannot be invested upfront.
Investor.gov defines dollar-cost averaging as regular equal-dollar investing. Vanguard's February 2023 research reports a 68% lump-sum win rate for its global-market comparison with three-month staging and a one-year evaluation. Its assets, period, and schedule differ from ours; it is context, not validation of our numerical result.
Data, assumptions, and reproducibility
This is an original descriptive calculation by Sun Insight Lab using a frozen response from the public API that powers our Simulator. Retrieved 2026-09-07T18:29:28+00:00; coverage is January 2010 through December 2025. The last observation is December 1, 2025, not the last trading day of that year. The endpoint selects the first available trading-day observation in each month; the IPO month can start later. No interpolation, missing-month fill, or future data is used.
The S&P 500 series is the Yahoo Finance ^GSPC price index: it omits dividend reinvestment and cannot itself be purchased. Stock series come from the pipeline's adjusted-close field and can incorporate dividend and split adjustments. We do not describe the mixed series as a uniform total-return comparison. No separate dividend payments are added. Taxes, fees, trading spreads, inflation, and cash interest are excluded. Fractional units and frictionless transactions are assumed.
Frozen API data (JSON) · Prices (CSV) · All observations for this study (CSV) · Summary results (JSON) · Provenance and SHA-256 checksum · Calculation and page-generation script
Download prices.json and manifest.json into research/2026-09/, and save reproduce.py as scripts/build_studies.py beside that directory. Run python scripts/build_studies.py with Python 3.10 or newer. No packages, API keys, or network access are needed. The script checks the snapshot hash and complete monthly coverage, then regenerates the CSVs, summaries, and all three articles. Rounded displayed figures come from the unrounded calculations.
The snapshot preserves what the simulator served on retrieval; it is not an independent audit of every vendor price. Later corrections to the live feed may change an interactive replay. Dates and symbol selection are part of the result, not evidence of predictive power. See data methodology and editorial policy.
Sources
- Simulator public price API (the frozen response above is the numerical source).
- S&P Dow Jones Indices: price and dividend return distinction.
- yfinance adjustment implementation (upstream methodology context, not a certification of this snapshot).
Educational analysis, not a forecast or a recommendation. Browse all three studies · Report a correction.