While EigenLayer's airdrop criteria are not fully disclosed, active governance participation is likely a significant factor. For EigenLayer, this could involve voting on key proposals regarding restaking parameters, slashing conditions, or the integration of new Actively Validated Services (AVSs). Engaging in governance demonstrates long-term commitment and aligns with EigenLayer's goal of building a decentralized ecosystem, potentially resulting in a larger token allocation compared to passive restakers.
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Yes, under Poisson-distributed independent slashing events, closed-form formulas exist. The risk-neutral breakeven reward R is R = λL / (1 - λ), where λ is the arrival rate and L is the loss given slash. For small λ, this approximates R ≈ λL. To incorporate risk aversion using CARA utility U(W) = -exp(-γW), the optimal reward solves: (1-λ)U(W+R) + λU(W-L) = U(W). This yields R > λL/(1-λ), explicitly quantifying the risk premium needed based on the risk aversion coefficient γ. These formulas provide a mathematical foundation for multiplier design.
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Are there closed-form formulas for optimal multiplier under Poisson slashing? Yes, under the simplifying assumption of Poisson-distributed, independent slashing events, we can derive closed-form formulas. The core is the expected value calculation: E[Return] = (1 - p) * R - p * S, where p is the slashing probability, R is the reward, and S is the slashed amount. Setting E[Return] = 0 gives the risk-neutral breakeven: R = p * S / (1 - p). For small p, this approximates to R ≈ p * S. To incorporate risk aversion, a utility function like Constant Absolute Risk Aversion (CARA) can be used: U = (1 - p) * (1 - exp(-γ * R)) + p * (1 - exp(-γ * (-S))), where γ is the risk aversion parameter. Solving for R when U > 0 provides a closed-form optimal multiplier that includes a risk premium. This formula shows the multiplier is linear in p and S but increases with the operator's risk aversion γ.
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