3 papers
q-fin.MF2026
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…
q-fin.TR2026
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…
q-fin.TR2024
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…