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Optimal risk-aware interest rates for decentralized lending protocols

Author

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  • Bastien Baude
  • Damien Challet
  • Ioane Muni Toke

Abstract

Decentralized lending protocols within the decentralized finance ecosystem enable the lending and borrowing of crypto-assets without relying on traditional intermediaries. Interest rates in these protocols are set algorithmically and fluctuate according to the supply and demand for liquidity. In this study, we propose an agent-based model tailored to a decentralized lending protocol and determine the optimal interest rate model. When the responses of the agents are linear with respect to the interest rate, the optimal solution is derived from a system of Riccati-type ODEs. For nonlinear behaviors, we propose a Monte-Carlo estimator, coupled with deep learning techniques, to approximate the optimal solution. Finally, after calibrating the model using block-by-block data, we conduct a risk-adjusted profit and loss analysis of the liquidity pool under industry-standard interest rate models and benchmark them against the optimal interest rate model.

Suggested Citation

  • Bastien Baude & Damien Challet & Ioane Muni Toke, 2025. "Optimal risk-aware interest rates for decentralized lending protocols," Papers 2502.19862, arXiv.org.
    • Handle: RePEc:arx:papers:2502.19862
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    References listed on IDEAS

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    Cited by:

    1. Philippe Bergault & S'ebastien Bieber & Olivier Gu'eant & Wenkai Zhang, 2025. "Cryptocurrencies and Interest Rates: Inferring Yield Curves in a Bondless Market," Papers 2509.03964, arXiv.org, revised Dec 2025.

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