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Angel Portfolio Simulator

Model a portfolio of angel checks with power-law outcomes. See the expected multiple and IRR, then 2,000 simulated portfolios showing the realistic range and your odds of losing money.

Inputs

Reset

Portfolio

1 to 500

Average holding period

Outcome mix (share of checks)

Total100%

Results

Expected MOIC

2.60x

Expected IRR 12.7% a year over 8 years on $500,000 invested.

P10 (weak case)
1.00x
0.0% IRR
P50 (median)
2.10x
9.7% IRR
P90 (strong case)
4.75x
21.5% IRR
Chance of losing money
9%
Portfolio returns under 1x
Chance of 3x or better
36%
Expected value
$1,300,000
Invested x expected MOIC

The median portfolio returns 2.10x, close to the 2.60x average. In 9% of simulated portfolios you lose money overall.

Portfolio MOIC across 2,000 simulations (share of runs)

For education only. Not tax, legal or investment advice.

Track every angel check in Raziel

Keep each startup, SAFE and SPV with its valuation, documents and returns in one portfolio.

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The math

How the simulator works

The expected multiple is a weighted average: each outcome’s multiple times the share of checks that land there. It tells you what the strategy returns on average, across many investors running it.

Your own portfolio is one draw, not the average. To show the range, the simulator builds 2,000 portfolios. For each one it assigns every check a random outcome using your percentages, then averages the multiples (all checks are the same size).

  1. Percentiles sort the 2,000 results. P10, P50 and P90 are the 10th, 50th and 90th of every hundred.
  2. Chance of losing money is the share of portfolios that returned less than 1x.
  3. The histogram groups the results by multiple so you can see how lopsided they are.

With power-law outcomes, the median portfolio usually sits below the expected value, because a few rare outliers carry the average. More checks raise the chance that you own one of them.

Expected MOIC = sum of  share x multiple
Expected IRR  = Expected MOIC ^ (1 / years) - 1

Each simulation: draw an outcome for every check,
portfolio MOIC = average multiple across checks

Assumptions and simplifications

  • Five fixed outcome buckets. Real outcomes are continuous, and the biggest winners can return far more than 50x.
  • Outcomes are independent between companies, every check is the same size, and there are no follow-on investments, fees or taxes.
  • All checks are written at once and exit together, so IRR is a simplification.
  • The simulation uses a fixed seed: the same inputs always give the same results.

Worked example

20 checks of $25,000 over 8 years

50% at 0x
0.00x
20% at 1x
0.20x
20% at 3x
0.60x
8% at 10x
0.80x
2% at 50x
1.00x
Expected IRR
12.7%
Median simulated portfolio
2.10x
Expected MOIC2.60x

Further reading

Frequently Asked Questions

Common questions about the Angel Portfolio Simulator calculator and the math behind it.

What is the power law in angel investing?

Startup returns are extremely uneven. Most investments return little or nothing, and a small number return many times the money. In a typical angel portfolio, one or two companies can produce most of the total return. That is why the average outcome sits well above the median, and why portfolio size matters so much.

How many angel investments should I make?

Enough that you have a realistic chance of owning one of the rare big winners. Try changing the number of checks here: with only a handful, the chance of losing money is high even when the expected multiple looks good. As the number rises, the spread of outcomes narrows toward the expected value.

Where do the default outcome percentages come from?

They are illustrative assumptions, not data from a study: half of checks lose everything, a fifth return about their money, and a small share produce 10x or 50x outcomes. Replace them with your own view of your deal flow. The shares are scaled to 100% if they add up to something else.

What do P10, P50 and P90 mean?

They are percentiles of the simulated portfolios. P50 is the median: half of the simulations did better and half did worse. P10 is a weak outcome that only 10% of simulations fell below, and P90 is a strong outcome that only 10% beat.

Why does the result not change when I reload?

The simulation uses a fixed random seed, so the same inputs always give the same 2,000 portfolios. That makes results shareable by link and easy to compare as you change one input at a time.

Is the expected IRR realistic?

It assumes every check is written on day one and every company exits at the same time. Real portfolios are built over years, failures tend to show up early and winners take longer, so actual IRRs can differ meaningfully. Use it for comparing scenarios, not as a forecast.

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