Portfolio Simulator

Finding the right size for an early-stage venture capital portfolio is more of an art than a science, with as many answers as there are firms.

There's no one-size-fits-all solution because it depends on your goals. Do you prioritise avoiding losses? Achieving 2x? 10x?

After conducting extensive research and running billions of portfolio simulations, we determined that portfolio performance is impacted by several key factors.

We created this VC Portfolio Simulator so you can explore our findings, design your own early-stage strategy and understand how these factors affect performance.

Complete the following six steps to get a customised analysis, or go directly to the simulator and play around with the variables.

Decision quality

How do you expect to perform with respect to other funds?

Average: based on historical data, the average early-stage fund has a power law distribution of investment returns, with 67.1% of the total investments yielding 0-1x, 26.9% yielding 1-5x, 3.1% yielding 5-10x, 1.5% yielding 10-20x, 0.83% yielding 20-50x and 0.57% yielding over 50x.
Above average: we assume an above average fund to perform slightly better, with 59.1% of the total investments yielding 0-1x, 30.4% yielding 1-5x, 4.65% yielding 5-10x, 2.6% yielding 10-20x, 1.75% yielding 20-50x and 1.5% yielding over 50x.

Upper bound on ROI

Ticket size

Follow-on reserve

Follow-on policy

What's your goal?

How do you expect to perform with respect to other funds?

Average: based on historical data, the average early-stage fund has a power law distribution of investment returns, with 67.1% of the total investments yielding 0-1x, 26.9% yielding 1-5x, 3.1% yielding 5-10x, 1.5% yielding 10-20x, 0.83% yielding 20-50x and 0.57% yielding over 50x.
Above average: we assume an above average fund to perform slightly better, with 59.1% of the total investments yielding 0-1x, 30.4% yielding 1-5x, 4.65% yielding 5-10x, 2.6% yielding 10-20x, 1.75% yielding 20-50x and 1.5% yielding over 50x.

What is the maximum ROI you expect from a single investment?

The power law distribution used in simulating portfolios permits the possibility of extremely large returns with a finite probability. By setting a limit on the maximum return on investment (ROI) expected from a single investment over the lifespan of your fund, the simulation results become more accurate.

What's your ticket sizing policy?

Uniform: allocate the same amount of capital to every investment.
Passive (variable): allocate a different amount of capital to each investment. The amount of capital allocated to each investment is determined by the dynamics of the round. We assume a max-to-min ratio of 10, meaning that the larger investment will be at most 10 times larger than the smallest one.
Active (variable): allocate a different amount of capital to each investment proportional to the expected return of the deal. We assume a max-to-min ratio of 10.

What fraction of the fund capital do you want to allocate to follow-on investments?

We assume a 3x increase in the round size for a follow-on investment. The amount of a follow-on investment is computed by splitting the follow-on capital across all follow-ons in proportion to the size of the initial investment.

What's your follow-on policy?

All: you will follow-on on all your initial investments.
Selected: you will follow-on on a subset of your initial investments, prioritising those that have a higher likelihood of yielding a return of more than 1x. We assume that you won't deploy additional capital for 30% of your initial investments that will yield less than 1x, and for 10% of those that will yield more than 1x.

What returns are you aiming for?

Tune the relative importance you give to each fund return.

Enable fine tuning

10x

Settings

Optimal portfolio size

0