1 citations · 1 across the 6 of their papers we have counts for
6 papers
Riemannian Geometry of Optimal Rebalancing in Dynamic Weight Automated Market Makers
Matthew Willetts
We show that when a dynamic-weight AMM rebalances by creating arbitrage opportunities, the per-step log loss is the KL divergence between successive weight vectors. The Fisher-Rao…
Pools as Portfolios: Observed arbitrage efficiency & LVR analysis of dynamic weight AMMs
Matthew Willetts, Christian Harrington
Dynamic-weight AMMs (aka Temporal Function Market Makers, TFMMs) implement algorithmic asset allocation, analogous to index or smart beta funds, by continuously updating pools' wei…
Rebalancing-versus-Rebalancing: Improving the fidelity of Loss-versus-Rebalancing
Matthew Willetts, Christian Harrington
Automated Market Makers (AMMs) hold assets and are constantly being rebalanced by external arbitrageurs to match external market prices. Loss-versus-rebalancing (LVR) is a pivotal…
Multiblock MEV opportunities & protections in dynamic AMMs
Matthew Willetts, Christian Harrington
Maximal Extractable Value (MEV) in Constant Function Market Making is fairly well understood. Does having dynamic weights, as found in liquidity boostrap pools (LBPs), Temporal-fun…
Optimal Rebalancing in Dynamic AMMs
Matthew Willetts, Christian Harrington
Dynamic AMM pools, as found in Temporal Function Market Making, rebalance their holdings to a new desired ratio (e.g. moving from being 50-50 between two assets to being 90-10 in f…
Closed-form solutions for generic N-token AMM arbitrage
Matthew Willetts, Christian Harrington
Convex optimisation has provided a mechanism to determine arbitrage trades on automated market markets (AMMs) since almost their inception. Here we outline generic closed-form solu…