Validator
Pre-launch tokenomics validation
Kenomic Validator evaluates token models before launch by measuring structural risk across price behavior, supply and inflation dynamics, and exposure to team and holder selling using scenario-based simulations.
Diagnostics
Token Resilience Diagnostics
Five measurable dimensions used to assess pre-launch token risk
How the token price reacts to buying and selling during the launch phase.
Measured signals
- Volatility distribution
- Maximum drawdowns
- Post-shock recovery speed
Failure modes
- Early launch price collapse
- Excessive volatility
- Slow recovery after adverse events
Primary output
Price behavior profile across scenarios
How the token price reacts to buying and selling during the launch phase.
Measured signals
- • Volatility distribution
- • Maximum drawdowns
- • Post-shock recovery speed
Failure modes
- • Early launch price collapse
- • Excessive volatility
- • Slow recovery after adverse events
Primary output
Price behavior profile across scenarios
Inflationary pressure introduced by token emissions and unlock schedules.
Measured signals
- • Emission rate relative to demand
- • Unlock concentration
- • Dilution over time
Failure modes
- • Persistent sell pressure
- • Excessive holder dilution
Primary output
Emission sustainability range
Capacity of available liquidity to absorb trading activity during launch.
Measured signals
- • Expected slippage
- • Depth degradation under stress
- • Capital efficiency
Failure modes
- • Excessive price impact
- • Liquidity breakdown during volatility
Primary output
Minimum viable liquidity estimate
Resilience of the token model to sustained or coordinated selling by early participants.
Measured signals
- • Selling behavior by cohort
- • Absorption capacity
- • Cascade risk
Failure modes
- • Unlock-driven price breakdowns
- • Sell cascades during low liquidity
Primary output
Sell-pressure tolerance range
Whether the token design incentivizes holding and participation rather than short-term extraction.
Measured signals
- • Participation incentives
- • Free-rider exposure
- • Reward sustainability
Failure modes
- • Incentive-driven extraction
- • Unsustainable reward structures
Primary output
Behavioral alignment score
Why Validator
From spreadsheet assumptions to simulation-backed validation
Most token launches fail when theoretical models encounter real liquidity and real selling.Validator replaces static assumptions with measurable risk signals derived from simulations.These signals quantify launch resilience across liquidity constraints, emission pressure, and exposure to team and holder selling.
Designed for teams preparing fundraising, listings, or internal launch decisions.
For Market Makers
Liquidity provisioning intelligence
Model liquidity strategies before deploying capital
Kenomic enables market makers to model liquidity behavior under asymmetric order flow, volatility, and selling pressure. This allows sizing depth, defining ranges, and assessing risk before inventory or capital is committed.
Min Depth
$2.1M
5% Slippage
$480k
Stress Decay
-34%
Provisioning structure
What is modeled
- Depth requirements
- Spread sustainability
- Capital efficiency
Why it matters
Liquidity strategies can be evaluated without exposing capital to untested market conditions.
Outputs
- → Target liquidity ranges
- → Rebalancing thresholds
- → Exposure limits
Inventory risk
What is modeled
- Directional exposure
- Volatility sensitivity
- Downside scenarios
Why it matters
Inventory risk can be quantified under worst-case selling and volatility assumptions.
Outputs
- → Maximum inventory exposure
- → Risk-adjusted sizing
- → Stress loss estimates
Exit feasibility
What is modeled
- Exit slippage
- Time required to exit
- Liquidity availability
Why it matters
Planned exits can be tested before capital is deployed into illiquid conditions.
Outputs
- → Exit feasibility assessment
- → Time-to-exit ranges
- → Suggested exit pacing
Return distributions
What is modeled
- Return percentiles
- Drawdown exposure
- Scenario sensitivity
Why it matters
Returns can be evaluated across conservative and adverse scenarios, not only base cases.
Outputs
- → Return ranges
- → Downside bounds
- → Scenario breakdowns
Allocation structure
What is modeled
- Position concentration
- Portfolio impact
- Correlation exposure
Why it matters
Investment sizing can be aligned with broader portfolio constraints.
Outputs
- → Suggested allocation ranges
- → Risk concentration flags
- → Rebalancing considerations
For Investors and Funds
Investor outcome modeling
Position sizing and allocation design under conservative exit assumptions
Kenomic allows investors to model how different allocation sizes, vesting structures, and exit strategies perform under adverse market conditions. The focus is on understanding downside, liquidity constraints, and the impact of investor selling on price.
VaR (95%)
-42%
Expected
+127%
CVaR
-58%
Optimal Allocation
2.1% of fund AUM
Deliverables
Validation outputs
Clear, decision-ready outputs generated from simulation-based validation
ARC resilience score
A single quantitative score summarizing pre-launch token risk across price behavior, supply and inflation dynamics, liquidity constraints, and exposure to selling.
Structural risk diagnostics
Identified structural weaknesses ranked by severity, including sensitivity to key tokenomics parameters.
Scenario-based simulations
Token behavior evaluated across multiple market and selling scenarios to expose fragility before launch.
Recommended parameter ranges
Simulation-derived operating ranges for emissions, liquidity assumptions, and selling constraints.
Output formats Founder-readable, investor-ready, exchange-compatible
Pricing
Simple pricing. Start free, scale on demand.
Your first Validator run is free. After that, pricing is usage-based: buy credits only when you need them. No fixed subscriptions, no long commitments.
Start
First validation run: free
Scale
Then use credits based on demand
Repeat
Top up anytime, use only what you need
Validate before capital is at risk
Use simulations to quantify liquidity requirements, selling pressure, emission sustainability, and price impact before launch.