---
title: Optimizing Interest Rate Models in DeFi
url: https://www.ml-quant.com/papers/ssrn/4807454/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4807454
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4807454
featured: 2024-05-01
citations: unknown
topic: Crypto & DeFi
---


# Optimizing Interest Rate Models in DeFi

A theoretical framework has been proposed for creating optimal interest rate models on DeFi lending platforms.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4807454
- Identifier: SSRN 4807454
- Released: 2024-04-23
- First featured: Quant Letter No. 47 (2024-05-01): https://www.ml-quant.com/issues/2024-05-01/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Crypto & DeFi

## Related

- [Trust Dynamics in Cryptocurrency Markets: Centralized vs. Decentralized Exchanges](https://www.ml-quant.com/papers/arxiv/2404.17227/): The study investigates the impact of incidents on trust and trading behaviors in centralized and decentralized cryptocurrency exchanges.
- [Implied Volatility in Decentralized Finance Pool](https://www.ml-quant.com/papers/ssrn/4792110/): The article introduces a breakeven implied volatility for decentralized finance pools, which aligns with a previous definition based on a market impact rule in traditional finance.
- [A theoretical framework for fees in AMMs](https://www.ml-quant.com/papers/arxiv/2404.03976/): The study explores the workings of arbitrage in decentralized finance automated market makers (AMMs), aiming to understand how AMMs can optimize revenue or minimize losses, and models the dynamics of arbitrage activity.
- [Deep Learning for Dynamic NFT Valuation](https://www.ml-quant.com/papers/arxiv/2312.05346/): The research suggests a deep learning model to predict non-fungible tokens (NFTs) prices using Ethereum blockchain and OpenSea data, which could be useful in decentralized finance (DeFi).
- [Decentralized Finance: Protocols, Risks, and Governance](https://www.ml-quant.com/papers/arxiv/2312.01018/): Protocols, Risks, Governance: The article discusses the benefits of decentralized finance (DeFi) over traditional finance, the function of smart contracts, and the associated risks, highlighting the need for more research on scalability and auditing.
- [Market Misconduct in Decentralized Finance (DeFi): Analysis, Regulatory Challenges and Policy Implications](https://www.ml-quant.com/papers/arxiv/2311.17715/): The paper investigates the rise of blockchain and DeFi, potential market misconduct, and the challenges of creating a DeFi regulatory framework, suggesting possible regulation strategies.
