Strong growth can coexist with deep drawdowns
A large ending multiple says little about the hardest part of holding an investment. We compare growth with the largest observed peak-to-trough decline for S&P 500, NVIDIA, Tesla, and Palantir over the same January 2021–December 2025 monthly sample. The start was chosen to give all four series complete calendar-year coverage after Palantir's listing; it is not an optimized entry date.
| Series | Ending multiple | Annualized growth | Maximum sampled drawdown | Peak | Trough | Recovery |
|---|---|---|---|---|---|---|
| SP500 | 1.84× | 13.22% | -23.31% | 2022-01-03 | 2022-10-03 | 2024-02-01 |
| NVDA | 13.76× | 70.44% | -60.17% | 2021-12-01 | 2022-10-03 | 2023-06-01 |
| TSLA | 1.77× | 12.29% | -73.17% | 2021-11-01 | 2023-01-03 | 2025-10-01 |
| PLTR | 7.17× | 49.27% | -81.18% | 2021-02-01 | 2023-01-03 | 2024-10-01 |
Growth and the path to it are different questions
The deepest sampled decline among these four series was -81.18% for PLTR, from 2021-02-01 to 2023-01-03. A hypothetical $10,000 position bought at that sampled peak would have been worth $1,881.63 at the trough before costs. This peak-entry illustration is separate from buying at the beginning of the study.
Recovery means reaching the previous sampled peak again, not recovering every investor's purchase price or compensating for inflation. A row can finish above its study starting price while still being below a later peak. Read the growth and drawdown columns together rather than sorting only by the winner.
Method
Each series has 60 observations and 59 monthly intervals. Ending multiple is last close / first close; annualized growth is multiple^(12/59) − 1. At each observation we maintain the highest close seen so far, calculate close / running peak − 1, and retain the most negative value. Recovery is the first later observation at or above that peak; a missing recovery means none was observed before the sample ended. There are no contributions or rebalancing in these calculations.
Monthly sampling hides risk
These are first-trading-day samples, not daily closes. A crash and recovery between two samples will be missed. The worst daily or intraday drawdown can therefore be deeper than this table. Nor does a historical recovery show that a future decline must recover. The S&P series excludes dividends while adjusted stock prices may include them, so relative growth here is not a comparison of identically defined total returns.
Selection bias
These are four familiar choices already offered in the simulator, not a random portfolio or the historical investable universe. Three are individual technology-related companies. Selecting recognizable survivors after observing their success can make stock selection look easier than it was. This study describes their paths and does not estimate the performance of a strategy that could have selected them in advance.
Replay and extend
Use Single mode with $10,000 initial, $0 monthly, January 2021 through December 2025. Divide the ending value by $10,000 to reproduce the multiple. For drawdown, download the prices CSV and calculate a running maximum in a spreadsheet; deposits would otherwise obscure losses in an account-value chart. Then move the start month and repeat. The code provides the exact peak, trough, and recovery rule rather than relying on visual estimates from a chart.
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.