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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2307.02074 |
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| _version_ | 1866913697116454912 |
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| author | Canidio, Andrea Fritsch, Robin |
| author_facet | Canidio, Andrea Fritsch, Robin |
| contents | We study a novel automated market maker design: the function maximizing AMM (FM-AMM). Our central assumption is that trades are batched before execution. Because of competition between arbitrageurs, the FM-AMM eliminates arbitrage profits (or LVR) and sandwich attacks, currently the two main problems in decentralized finance and blockchain design more broadly. We then consider 11 token pairs and use Binance price data to simulate the lower bound to the return of providing liquidity to an FM-AMM. Such a lower bound is, for the most part, slightly higher than the empirical returns of providing liquidity on Uniswap v3 (currently the dominant AMM). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_02074 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Arbitrageurs' profits, LVR, and sandwich attacks: batch trading as an AMM design response Canidio, Andrea Fritsch, Robin Distributed, Parallel, and Cluster Computing Theoretical Economics We study a novel automated market maker design: the function maximizing AMM (FM-AMM). Our central assumption is that trades are batched before execution. Because of competition between arbitrageurs, the FM-AMM eliminates arbitrage profits (or LVR) and sandwich attacks, currently the two main problems in decentralized finance and blockchain design more broadly. We then consider 11 token pairs and use Binance price data to simulate the lower bound to the return of providing liquidity to an FM-AMM. Such a lower bound is, for the most part, slightly higher than the empirical returns of providing liquidity on Uniswap v3 (currently the dominant AMM). |
| title | Arbitrageurs' profits, LVR, and sandwich attacks: batch trading as an AMM design response |
| topic | Distributed, Parallel, and Cluster Computing Theoretical Economics |
| url | https://arxiv.org/abs/2307.02074 |