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Online Estimation Algorithm for Observation Noise Covariance in Floating-Rate Models of Lending Protocols This study introduces an online estimation algorithm for observation noise covariance in floating-rate models of lending protocols. By dynamically adjusting model parameters, we improve interest rate prediction accuracy, supporting informed decision-making and risk management in decentralized lending markets.

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