Early-stage venture returns follow a power law. This simulator runs 5,000 Monte Carlo paths — calibrated to the historical AngelList distribution — so you can see exactly how pool size reshapes your expected return and the probability of losing any value.
There is something very unintuitive about early-stage companies that almost no one outside YC and a small corner of AngelList has figured out: with early-stage companies, the more companies you invest in, the higher your returns — and similarly, the more companies you invest in, the more your likelihood of losing money asymptotically drops toward zero.
As we add more founder shares to the EFLF pool, your chances of making money go up. And your chances of losing value — even if your own startup fails — approach zero. This is why the EFLF can only be built at the earliest stage, with the largest possible pool.
This dashboard simulates 5,000 possible 10-year futures for a fund holding the number of startups you choose, drawing each company's outcome from the historical AngelList seed-stage distribution (Othman, 2019; Koh & Othman, 2020).
Move the sliders, hit Run simulation, and watch how diversification reshapes the range of possible outcomes. The fewer startups in the fund, the more your result depends on luck. The more startups, the more reliably the fund captures the rare home runs that drive almost all the returns.
Each point is the result of 500 simulated 10-year outcomes at that pool size, using the failure rate and maximum upside you set above. Watch how the median and mean climb — and the 5th percentile floor rises — as more startups join the pool. This is the power law at work.
At any given failure rate and maximum upside, how often does a fund of n startups return less than 1× invested capital? Even a handful of companies dramatically cuts the chance of a loss, thanks to the power law's fat tail of winners offsetting losers.
From 10,665 real LP portfolios on AngelList (Koh & Othman, 2020). Left: median annual IRR for investors with fewer vs. more than N holdings — at every threshold, the larger portfolio wins by 7–9% p.a. Right: share of investors "in the money" (portfolio value > cost) rises from ~50% at 3 holdings to ~90% at 90+ holdings.
Source: Koh & Othman (2020), Table 1 and Figure 3. Data reflects AngelList LP portfolios with ≥1 year effective duration as of April 2020. Past performance is not indicative of future results.
Each simulation traces one possible 10-year fund outcome. The dark teal band shows where the middle 50% of outcomes land; the lighter band shows the middle 90%. The faint lines are 30 individual sample paths. Anything below the dashed line is a losing fund.
For a single typical simulation, this shows where the fund's value comes from over time. Watch how a small slice of breakout winners (≥10×) tends to dominate the final value — the power-law dynamic in action.
Complete distribution of the 5,000-path simulation. Percentiles describe where outcomes fall in the distribution; probabilities describe how often the fund clears specific return thresholds.
| Metric | Value |
|---|
Hypothetical and illustrative. The figures shown are simulated, not actual returns of any account, fund, or investor. No representation is made that any investor has achieved or will achieve results similar to those shown. Hypothetical performance has inherent limitations: it is prepared with the benefit of hindsight, does not involve real capital at risk, and may not reflect the impact of material economic and market factors.
Past performance is not indicative of future results. Model parameters are calibrated to historical AngelList early-stage venture data (Othman, 2019). The historical return distribution of the venture asset class is not a guarantee that future returns will follow the same distribution.
Model limitations. The simulation assumes equal-weighted holdings, independent outcomes across companies, no correlation between exits, no fees, no carried interest, no taxes, and no transaction costs. Net returns to an investor would be lower — potentially materially — after fees, expenses, carry, and taxes.
Risk of loss; illiquidity. Investments in early-stage private companies involve a high degree of risk, including the risk of total loss of capital. Private securities are illiquid and may not be readily transferable.
New product; no operating history. The Exceptional Founder Liquidity Fund is a new product with no operating history. Structure and terms remain subject to change, and certain features (collateralized borrowing, secondary purchases, and §351 conversions)† depend on regulatory, tax, and counterparty arrangements still being finalised.
Not an offer; not advice. This dashboard is for informational and illustrative purposes only. It is not an offer to sell, or a solicitation of an offer to buy, any security or interest in any fund, and is not investment, legal, accounting, or tax advice.