Investor ROI analysis models what each funding round earns under a set of stated price assumptions, and when it earns it relative to that round's cliff. It is scenario arithmetic run on your own cap table, not a view on where the token will trade. The output is a map of the months where several rounds cross into profit at once, which is where concentrated sell pressure lives.
The analysis is credible precisely because it never picks a price. You hold price as an assumption, vary it deliberately, and read what your vesting schedule does under each one. The moment an assumption becomes a target, it stops being analysis and becomes a forecast.
Scenario modeling and forecasting are not the same exercise
A forecast says the token will be worth X. A scenario says: if the token were worth X, here is what our own unlock schedule produces. The first is a claim about the market, unprovable, and off limits for a firm advising founders. The second is a claim about arithmetic you control, and anyone holding your allocation table can check it.
We publish the second and refuse the first, and we hold clients to the same line in their own materials. If a board wants assurance that conditional scenario work on a digital asset is a recognized method rather than something we improvised, hand them the CFA Institute's November 2023 cryptoasset valuation guide for investment professionals.1
The arithmetic
Five inputs per round: price paid per token, the fraction released at TGE, the cliff length, the vest length after it, and any discount that changes the effective entry. Out of those comes a break even curve, the reference price at which the tokens released by month N cover the whole check.
Illustrative numbers, because the shape matters more than the values. A seed round enters at $0.02 with 5% released at TGE and the rest vesting monthly after a 12 month cliff. A Series A enters at $0.20 with 10% at TGE and a 6 month cliff. Hold a reference price of $0.30 and seed is at 15 times entry on its released portion from day one, while the Series A sits at 1.5 times. One schedule document, two completely different incentives in month one.
Three scenarios, held as assumptions
Run at least three reference prices and state where each comes from rather than inventing it: a downside anchored to the last round's price, a base anchored to comparable launch valuations you can name and date, and an upside. None is a prediction. Each is a lens, and they are not ranked by likelihood, because ranking them is how a scenario set quietly turns into a forecast.
Read three outputs under each. The month each round crosses break even. The total tokens unlocking that month across every round at once. And that unlock expressed both as a share of circulating supply and as a multiple of the market depth that has to absorb it. Teams compute the first two and skip the third, the one deciding whether the unlock is absorbable or an event.
The cliff test
One rule catches most of the damage: no round should reach break even before its own cliff clears. When it does, the cliff is not a lockup. It is a scheduled sale with a date on it that everybody holding that allocation already knows.
The fixes are structural. Extend the cliff so break even lands after it. Cut the TGE release for that round. Or reprice the round. What does not work is lowering the listing reference to close the gap. The market prices the asset wherever it was going to, and you have moved a number in your model rather than an incentive on your cap table.
Presenting it without publishing a forecast
Label every price as an assumption in the chart itself, not in a footnote nobody reads. Write outputs as conditional sentences on this pattern: at this reference price, this round crosses break even in month 14, which carries 3.1% of circulating supply in combined unlocks. Never rank the scenarios, and keep the pitch consistent with the model, because a team that builds three scenarios and then talks about one has published a forecast whether it meant to or not.
There is a limit here worth saying out loud. None of this creates value. The business does that. Investor ROI analysis only tells you whether the schedule you wrote will let the business be heard over its own unlocks, which is a smaller question than founders want it to be and a more answerable one. EY's token due diligence framing points the same way: the investor evaluates what is left against their own risk appetite, so a conditional structure is more useful to them than a single number.2
Common questions
How do you calculate investor ROI on a token round?
Take the price paid per token, the fraction released at TGE, the cliff and the vest schedule, then compute the reference price at which the tokens released by a given month cover the full check. That is the break even curve for that round. Run it at several stated reference prices and plot every round on one chart, because the overlap between rounds is the finding, not any single curve.
Is investor ROI analysis a price prediction?
No, and it stops being useful if it turns into one. Price enters as an assumption that is varied deliberately across a downside, base and upside case, and the output is a conditional statement about your own unlock schedule under each. Nothing in the method estimates what the token will actually trade at, and the scenarios are not ranked by likelihood for that reason.
When should a funding round reach break even?
After its cliff clears, not before. A round that is profitable on the day its cliff releases has a lockup in name only, since the holders can see the date and the multiple in advance. Fix it by extending the cliff, cutting the TGE release, or repricing the round. Lowering the listing reference does not fix it, because the market reprices to wherever it was going anyway.
See Token Allocation and Vesting Design for how this applies in practice.
Sources
- Valuation of Cryptoassets: A Guide for Investment Professionals
CFA Institute Research and Policy Center, 2023
Urav Soni and Rhodri Preece, CFA, November 2023. Cited as the professional standards body reference for conditional scenario methods applied to cryptoassets. - Token due diligence: a structured approach to evaluate digital asset risk
EY, 2024
Frames what remains after mitigants as the thing an investor evaluates against their own risk appetite, which is the case for presenting a conditional structure rather than one number.
Last reviewed 2026-08
Know the terms but not sure how they apply to your project? That is what an engagement is for. We design, document, and stress-test the whole token economy inside the Tokenomics Data Room.
100+ projects advised. Complete tokenomics in 4 to 6 weeks.