How holding periods change S&P 500 outcomes
Does a longer holding period eliminate losses? We test every available 1-, 3-, 5-, and 10-year S&P 500 window in the simulator snapshot, rather than choosing one attractive start date. The question concerns endpoint price changes; it does not measure what an investor experienced between the endpoints.
| Horizon | Windows | Loss windows | Worst annualized | Median annualized | Best annualized |
|---|---|---|---|---|---|
| 1 years | 180 | 25 | -20.27% | 13.21% | 62.71% |
| 3 years | 156 | 0 | 1.55% | 10.81% | 24.09% |
| 5 years | 132 | 0 | 3.70% | 11.79% | 17.92% |
| 10 years | 72 | 0 | 7.69% | 11.10% | 14.77% |
What changes when you move the start date?
the 1-year windows range from -20.27% to 62.71% annualized; the 3-year windows range from 1.55% to 24.09% annualized; the 5-year windows range from 3.70% to 17.92% annualized; the 10-year windows range from 7.69% to 14.77% annualized.
The weakest one-year interval began 2022-01-03 and ended 2023-01-03. That is a useful counterexample to judging this dataset only by its full-period rise. Longer windows combine more market regimes, but they also leave fewer observations available for comparison.
Method
For each starting observation i and horizon h months, we use P[i+h]/P[i] − 1. Annualized growth is (P[i+h]/P[i])^(12/h) − 1. A 12-month interval requires 13 observations, not 12. We count a loss only when the endpoint is below the start. Medians use all eligible windows, including those ending in a decline. For a spreadsheet replay, sort the CSV's sp500 rows by date and divide each close by the close h rows earlier.
What the result cannot establish
These are overlapping windows: adjacent ten-year observations share almost all their history. They are not independent trials, and their loss frequency is not the probability of a future loss. This sample begins after the 2008 financial crisis and omits many earlier market regimes. Even if a column has zero losses, it is not a guarantee. Inflation could turn a positive nominal outcome into a real loss, and a severe interim drawdown can occur inside a positive endpoint window.
Replay one interval
In Single mode, choose S&P 500, set initial investment to $10,000 and monthly contribution to $0, and select the months in any CSV row. Divide ending value by $10,000 and subtract one to recover the unannualized return. Repeat with a neighboring start month while keeping the horizon constant. Use the downloaded snapshot for an exact replay if live prices have changed.
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.