去中心化借贷平台上的资金分配
Capital allocation on decentralized lending platforms
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中文总结 AI 辅助
本研究聚焦去中心化借贷平台的贷款人资金分配，在三种利率模型下推导闭式解并回测，发现拐点处借贷双方最优分配的不对称性会加剧利率波动。
中文摘要 AI 辅助
本研究是我们之前论文的补充，此前论文研究了去中心化借贷市场中借款人层面的策略，本研究则聚焦于贷款人层面的资金分配。我们考虑一位寻求在多个使用同一供应资产的市场中分配固定预算的贷款人，考虑到供应资金对借贷利率的影响，我们在三种利率模型下推导了闭式解：线性模型、分段线性（kinked）模型以及自适应模型（Morpho的AdaptiveCurveIRM）。我们首先在以太坊上的USDC Morpho借贷市场，随后在WETH Morpho借贷市场进行了回测。我们还表明，在分段线性利率模型下，使某一市场恰好达到拐点（kink）的分配对贷款人而言绝非最优，而对借款人而言则可能是最优的。这种不对称性可能在拐点处造成借贷双方的紧张关系，进而加剧利率波动。
英文摘要
This work complements our previous paper, which studies borrower-side strategies in decentralized lending markets, by focusing on lender-side capital allocation. We consider a lender who seeks to allocate a fixed budget across multiple markets sharing the same supplied asset. Accounting for the impact of supplied capital on lending rates, we derive closed-form solutions under three interest-rate models: linear, kinked, and adaptive (Morpho's AdaptiveCurveIRM). Backtests are conducted first on USDC and then on WETH Morpho lending markets on Ethereum. We also show that, under the kinked rate model, an allocation that brings a market exactly to the kink is never optimal on the lender side, whereas it can be optimal on the borrower side. This asymmetry may create tension between lenders and borrowers around the kink and thereby exacerbate rate volatility.
