What could your portfolio become?
Explore 50,000 simulated outcomes for speculative technology, established quality companies, and a diversified index. Compare the typical result with the risks along the way.
Research prototype · conditional scenariosSimulated wealth
Compare all three portfolios
| Portfolio | Median value | 5th–95th range | Chance of profit | Chance of beating SPY |
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Assumptions, model limits & how to read this
These results depend on the inputs and are not forecasts. The model uses ARKK, QUAL, and SPY as portfolio proxies. Every arm starts with $500. Weekly deposits are represented by their monthly equivalent (weekly amount × 52 ÷ 12), added at month end. Profit means ending above total contributions.
Baseline annualized return anchors are 13.63%, 14.47%, and 15.22%; volatility inputs are 50%, 12.28%, and 12.74%. Return anchors are transformed into log-return drifts. Correlations are scenario assumptions. The lower-return case subtracts five percentage points from each return anchor. Stress adds 1.5× volatility and tighter correlations.
The same random seed is used in every case. Controls display precomputed 50,000-path runs; they do not fetch live prices or rerun the Python model in your browser. Bands show pointwise percentiles, not a single possible path. The 12 example trajectories are the first 12 paths, not selected winners.
The prototype exponentiates Student-t log returns. This distribution has no finite theoretical mean for gross returns, so this dashboard emphasizes medians and quantiles. Historical input windows differ; source validation, matched histories, and a model with finite return moments remain research tasks. Fees, taxes, inflation, liquidity events, and delistings are not modeled explicitly. Long-horizon 5- and 10-year views are planned.