To provide liquidity for airdrop points, users must first connect their wallet to the Curve Finance application. Then, they select a desired pool and deposit an equivalent value of the pool's constituent assets (e.g., USDC and USDT for a stablecoin pool). This action grants them LP (Liquidity Provider) tokens. Holding these tokens in their wallet represents their stake in the pool. For airdrop eligibility, consistent and long-term provision is key. Many projects track this activity via on-chain snapshots, rewarding users based on the depth and duration of their liquidity commitment.
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Risk-loading techniques from insurance and credit risk provide sophisticated frameworks for moving beyond simple expected value calculations. A key technique is risk-adjusted capital allocation, where the required capital (or reward) is determined by the Value at Risk (VaR) or Conditional Value at Risk (CVaR) of the slashing distribution. This means a fat-tailed risk with low probability but high severity demands a much higher multiplier than its expected value suggests. Furthermore, finance teaches us to load for parameter uncertainty—since the estimated slashing probability itself is uncertain, the multiplier must include a "parameter risk premium." Finally, techniques for pricing illiquid and non-diversifiable risks directly apply, as an operator's slashing risk is difficult to hedge, justifying a higher risk premium in the reward multiplier.
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How do risk-loading techniques from finance inform slashing multiplier design? Risk-loading techniques from finance, particularly from insurance and credit risk, provide a sophisticated framework for moving beyond simple expected value calculations. The core idea is to price risk based on its statistical properties, not just its mean. A key technique is risk-adjusted capital allocation, akin to Solvency II in insurance. Here, the required capital (or in our case, the reward) is determined by the Value at Risk (VaR) or Conditional Value at Risk (CVaR) of the slashing distribution. A fat-tailed risk with a low probability but high severity demands a much higher multiplier than its expected value suggests. Furthermore, finance teaches us to load for parameter uncertainty—since the estimated slashing probability is itself uncertain, the multiplier must include a "parameter risk premium." Finally, techniques for pricing illiquid and non-diversifiable risks directly apply
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