What modelling covers
A spreadsheet assumes everyone behaves. They do not.
Modelling turns a design on paper into a system you can run. Two streams: a working simulation of the economy, and the stress tests that find where it breaks.
Fixed quote before work begins
Full engagement length
Monte Carlo runs across bull, base and bear conditions, plus the specific failures that kill tokens: unlocks into thin liquidity, growth stalling, incentives ending, holders exiting together.
Model types
Three kinds of model, and the one your economy needs.
Paying for the wrong one is the most common way a modelling budget gets spent without producing a decision.
A six stage process to model and stress-test your token economy.
01
Model scoping
We agree what the model has to answer: the metrics that matter, the decisions riding on them, and the conditions worth testing.
02
Structure mapping
Every source, drain, pool and converter in your economy is mapped, so the model reflects how value actually moves rather than how the deck describes it.
03
Parameter calibration
Inputs are set from your real data where it exists and from comparable protocols where it does not, with every assumption written down and attributed.
04
Monte Carlo simulation
The economy runs thousands of times across bull, base and bear paths, producing distributions rather than a single optimistic line.
05
Stress and failure testing
We deliberately break it: unlocks into thin liquidity, stalled growth, incentives ending, correlated selling. The breaking points are the output that matters.
06
Model handover
You receive the working Machinations model, the scenario results, and a written interpretation of what each output means for your launch decisions.
Outputs and limits
Modelling compares your decisions, it does not predict your price.
The output that matters is the gap between outcome A and outcome B, because everything the model cannot see moves both scenarios the same way.
What the model answers
What happens to TVL, staking participation and sell pressure if the staking APY moves from 6% to 12%. Which unlock schedule does least damage against projected user growth and liquidity depth. When an incentive programme stops paying for itself. What sequence of events undercollateralises the protocol, how likely it is, and what triggers it.
What no model can promise
A price on a date. Price depends on macro conditions, market maker behaviour, exchange listigs, marketing and sentiment, and no model holds all of that; one post from a large enough account erases the most expensive model anyone has built. Anyone quoting you a figure for a given month (a token at $4.36 in month three, or any other invented number) is selling false precision.
Where modelling gets specific: what we simulate, what the outputs tell you, and the limits of what any model can promise.
Client examples
Tokenomics modelling details
We’ve been doing this for years across all narratives, trends, and market conditions. Below are the details of what you can expect working with us.
01
What is tokenomics consulting?
02
How much does tokenomics design cost?
03
How much does tokenomics modelling cost?
04
How much does a tokenomics audit cost?
Frequently asked questions
01
How do you prevent "Death Spirals" in token economic design?
We prevent death spirals by anchoring the token to tangible utility and dynamically aligning emission rates with actual network growth, ensuring that value creation always outpaces token inflation.
02
Do you offer post-TGE (Token Generation Event) monitoring and advisory?
Yes, we can work with clients after TGE. This typically includes adjusting token emissions, and modelling the economy to explore potential changes for a V2 economy.
03
Do you use Machinations.io or Python for token modeling and stress testing?
We generally use Machinations when modelling and stress testing economies, and would only recommend Python to well financed businesses with extremely complex economies.
04
How long does a tokenomics engagement take?
A standard design and modelling engagement runs 3 to 5 weeks. A single-token economy moves faster; a multi-token system with several interacting incentive loops takes longer, because each loop has to be modelled and stress-tested separately.
05
What is the difference between tokenomics design and modelling?
Design defines the economy: supply, distribution, vesting, utility, and value accrual. Modelling tests it; we build the economy in Machinations and stress it under different market and demand conditions to see where it breaks before launch. Design is the blueprint, modelling is the wind tunnel.
06
What does a Machinations model actually show me?
How your token economy behaves over time under different conditions: circulating supply, sell pressure, staking participation, and price-relevant flows month by month. It shows where the economy holds and where it fails before real money is at stake.
07
What scenarios do you stress-test against?
Market drawdowns, demand shocks, unlock cliffs, liquidity crunches, and changes in user growth and retention. We run the economy through bull, bear and sideways conditions in Machinations until something breaks, then fix what broke.
