DeFi: data-driven characterisation of Uniswap v3 ecosystem & an ideal crypto law for liquidity pools
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- Robin Fritsch & Samuel Kaser & Roger Wattenhofer, 2022. "The Economics of Automated Market Makers," Papers 2206.04634, arXiv.org.
- Hugo Inzirillo & Stanislas de Quenetain, 2022. "Managing Risk in DeFi Portfolios," Papers 2205.14699, arXiv.org, revised Sep 2022.
- Igor Makarov & Antoinette Schoar, 2022. "Cryptocurrencies and Decentralized Finance (DeFi)," NBER Working Papers 30006, National Bureau of Economic Research, Inc.
- Lioba Heimbach & Ye Wang & Roger Wattenhofer, 2021. "Behavior of Liquidity Providers in Decentralized Exchanges," Papers 2105.13822, arXiv.org, revised Oct 2021.
- Jan Arvid Berg & Robin Fritsch & Lioba Heimbach & Roger Wattenhofer, 2022. "An Empirical Study of Market Inefficiencies in Uniswap and SushiSwap," Papers 2203.07774, arXiv.org, revised May 2022.
- Lioba Heimbach & Eric Schertenleib & Roger Wattenhofer, 2022. "Risks and Returns of Uniswap V3 Liquidity Providers," Papers 2205.08904, arXiv.org, revised Sep 2022.
- Lawrence Hubert & Phipps Arabie, 1985. "Comparing partitions," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 193-218, December.
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- Georg Menz & Moritz Vo{ss}, 2023. "Aggregation of financial markets," Papers 2309.04116, arXiv.org, revised Sep 2024.
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This paper has been announced in the following NEP Reports:- NEP-PAY-2023-02-27 (Payment Systems and Financial Technology)
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