---
title: DeFi Potential Risks
url: https://www.ml-quant.com/papers/ssrn/5191051/
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 5191051
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5191051
featured: 2025-03-26
citations: unknown
topic: Crypto & DeFi
---


# DeFi Potential Risks

The article discusses the opportunities and risks of financial services offered by centralized and decentralized finance organizations in the crypto finance sector.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5191051
- Identifier: SSRN 5191051
- Released: 2025-03-24
- First featured: Quant Letter No. 90 (2025-03-26): https://www.ml-quant.com/issues/2025-03-26/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Crypto & DeFi

## Related

- [Price manipulation schemes of new crypto-tokens in decentralized exchanges](https://www.ml-quant.com/papers/arxiv/2502.10512/): An analysis of decentralized exchanges (DEXs) shows high risks in investing in new tokens due to liquidity traps and fraud, emphasizing the importance of understanding the financial dynamics and risks of decentralized markets.
- [Private MEV Protection RPCs: Benchmark Stud](https://www.ml-quant.com/papers/arxiv/2505.19708/): OFA Implications: The Ethereum DeFi sector has seen a shift with 80% of transactions now using private RPCs, emphasizing the impact of Order Flow Auctions on transaction efficiency and quality.
- [Price Discovery in Cryptocurrency Markets](https://www.ml-quant.com/papers/arxiv/2506.08718/): Centralized markets typically lead in Ethereum price discovery compared to decentralized exchanges, affecting liquidity, arbitrage, and market efficiency.
- [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.
- [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).
- [Regulating Financial Innovation: Thoughts about Securitization](https://www.ml-quant.com/papers/ssrn/5029706/): Securitization: The author suggests a regulatory framework for financial innovation, including FinTech, cryptoassets, and DeFi, applicable to past and future securitization transactions, including NFTs.