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The same company can be a good investment at one price and a bad one at another

An investment decision weighs the range of outcomes against the price paid. Scenario-based expected value shows how quickly a higher price erodes the return from the same company.

11 min read · Level 4

The point

I find writing down a probability for the best outcome the most humbling part of any investment decision. It is almost always lower than the enthusiasm in the room implied, and the moment it is written it becomes something that can be argued with, which is exactly what a good decision needs.

What is it?

Instead of asking 'is this a good company?', ask 'what are the possible outcomes, how likely are they, and what does each return at this price?'.

For an early-stage investment at a 10,000,000 post-money:

Scenario Probability Multiple Contribution Company fails 60% 0x 0.00 Modest outcome 30% 2x 0.60 Large outcome 10% 25x 2.50 Expected multiple 3.10x

0.6 x 0 + 0.3 x 2 + 0.1 x 25 = 3.10x.

Now the same company at a 20,000,000 post-money. The outcomes for the company are unchanged, but each multiple halves:

Company fails 60% 0x 0.00 Modest outcome 30% 1x 0.30 Large outcome 10% 12.5x 1.25 Expected multiple 1.55x

Doubling the price halves the expected multiple, even though nothing about the company changed. And in both cases, the most likely single outcome is losing the investment.

Why does an investor care?

Because the price is the one variable an investor can negotiate or walk away from. A great company at an extreme price can be a worse investment than a decent company at a fair one.

The exercise also makes probabilities explicit, which exposes overconfidence: most investors, asked to write down probabilities, discover they were implicitly assuming success.

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Example

Testing the probabilities.

The investor's estimate of a 10% chance of a 25x outcome is the load-bearing assumption. If it is really 5%:

At 10,000,000 post-money: 0.3 x 2 + 0.05 x 25 = 0.60 + 1.25 = 1.85x (failure share becomes 65%) At 20,000,000 post-money: 0.3 x 1 + 0.05 x 12.5 = 0.30 + 0.625 = 0.925x

At the higher price and a slightly less optimistic view of the upside, the expected multiple is below 1x. The decision depends almost entirely on the probability of the large outcome and the price paid.

The common mistake

Deciding on the quality of the company without writing down outcome probabilities and multiples at the actual price.

How it works

Step 1: Define three to four scenarios

Include failure, modest and large outcomes with plausible exit values.

Step 2: Assign probabilities

Use base rates for the stage, then adjust with evidence.

Step 3: Calculate multiples at this price

Convert each exit value into a multiple of the proposed entry price.

Step 4: Test the load-bearing probability

Recalculate with a lower chance of the best outcome.

When to use this

Before committing to any investment with a wide range of possible outcomes.

When not to use it

Do not present expected value as a prediction; it is a way to compare decisions, and single early-stage investments usually end far from their expected value.

How investors actually did it

A recurring pattern: power-law returns in venture portfolios

Analyses of venture capital returns, including studies of angel and fund portfolios, have repeatedly found that a small minority of investments generate most of the returns while a large share return less than the capital invested.

The probability and size of the best outcome drive almost all of the expected value.

Do this now

  • Write three outcome scenarios with probabilities for one deal
  • Recalculate the expected multiple at a price 50% higher

Create a free account to read the rest and apply it to your own investing.

Related lessons

  • Work backwards: what would have to be true to justify this price? — Rather than producing your own valuation and comparing it with the price, take the price as given and solve for the growth or margins it assumes. Then judge whether those assumptions are plausible. (11 min)
  • Probability, not certainty — Every investment is a bet on a distribution of outcomes, not a prediction of one. Once you think in probabilities, a loss stops being proof you were wrong. (10 min)
  • Several methods give a range; the gaps show what you believe — No single method values an early company reliably. Running several and comparing the results shows the range of defensible prices and exposes which assumptions drive the difference. (10 min)

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