Research
Research is a cornerstone of Lendwise. Our research spans interest-rate design, capital allocation and optimal execution in decentralized markets.
Research articles
Optimal risk-aware interest rates for decentralized lending protocols
Abstract. Decentralized lending protocols set interest rates algorithmically according to the supply and demand for liquidity. We propose an agent-based model and determine the optimal interest rate policy. Linear agent responses lead to a system of Riccati-type ODEs, while nonlinear responses are addressed using Monte Carlo estimation and deep learning. After calibrating the model on block-level data, we compare its risk-adjusted performance with industry-standard interest rate models.
- Authors: Bastien Baude, Damien Challet and Ioane Muni Toke
- Source: https://arxiv.org/abs/2502.19862
Leveraged positions on decentralized lending platforms
Abstract. We develop a mathematical framework to optimize leveraged staking strategies in which a staked asset is supplied as collateral, the underlying asset is borrowed and restaked, and the process can be repeated across multiple lending markets. The problem is reduced to a convex allocation across markets, with closed-form solutions for linear, kinked and adaptive interest rate models. The framework accounts for leverage limits, utilization-dependent borrowing costs and transaction fees.
- Authors: Bastien Baude, Vincent Danos and Hamza El Khalloufi
- Source: https://arxiv.org/abs/2601.14005
Optimal execution on Uniswap v2/v3 under transient price impact
Abstract. We study the optimal liquidation of a large position on Uniswap v2 and Uniswap v3 in discrete time. Instantaneous price impact is derived from the AMM pricing rule, while transient impact captures exponential or approximately power-law decay together with a permanent component. For Uniswap v2, optimal strategies are obtained in closed form under general price dynamics. For Uniswap v3, we introduce a two-layer liquidity model and solve the problem through dynamic programming and numerical approximation.
- Authors: Bastien Baude, Damien Challet and Ioane Muni Toke
- Source: https://arxiv.org/abs/2601.03799