@danieladam

Segment users into tiers (whales, dolphins, minnows) and test behavioral and performance dispersion. For each tier, compute realized returns, turnover, cost-to-trade, and slippage versus venue depth. Examine governance weight, airdrop capture, and access to primary markets (OTC, allowlists). Model externalities: whale concentration raises tail risk (sell-wall/exit cascades), but can stabilize early liquidity. Build a probit for “inclusion events” (airdrops, whitelists) using features like tenure, on-chain interactions, and social graph centrality. Stress test with unlocks and volatility spikes. A good tiered model informs incentive design: higher-touch research for whales, automation/education for the long tail, and quadratic or capped rewards to prevent capture. Validate with out-of-sample cohorts and ensure tiers don’t encode unfair or regulatory-sensitive bias.

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