Problem
Research questions and friction points this paper is trying to address.
Automated Market Makers
Oracle-Parametrized AMMs
Loss-Versus-Rebalancing
Price Discovery
Tokenized Securities
Oracle-Parametrized Constant Function Market Makers: From Price Feeds to Pricing Rules
🤖 AI Summary
This study addresses the pricing deviations and capital inefficiency of off-chain price-discovered assets in traditional automated market makers (AMMs) arising from information insensitivity. To this end, it proposes the Oracle-Parameterized AMM (OP-AMM), which extends the information-insensitive framework by making quotes jointly dependent on pool reserves and external oracle prices. Methodologically, the authors derive a loss-versus-rebalancing (LVR) decomposition to disentangle losses from market latency and oracle error, establish a price interpolation theory under strict contraction conditions to characterize the Pareto frontier, and conduct counterfactual backtesting using SPY NBBO data. The results identify theoretical conditions for improving capital efficiency while reducing normalized LVR, revealing a fundamental trade-off wherein noisy or stale oracles can reverse these performance gains.
📝 Abstract
This paper introduces oracle-parametrized automated market makers (OP-AMMs), i.e., automated market makers whose quoted price depends jointly on the pool reserves and an external oracle price. In doing so, we extend the information-agnostic AMM framework to settings, such as tokenized securities, for which price discovery occurs off-chain. Under a strict oracle-contraction condition, we show that the quoted price of any OP-AMM interpolates between the oracle price and an implicit autarkic price determined by the pool reserves. We then derive a general loss-versus-rebalancing (LVR) decomposition that separates the residual exposure to market lags from the losses induced by oracle errors. This analysis is further extended to stale, discrete-update oracles and to sandwich attacks around oracle updates. Using this framework, we find conditions under which OP-AMMs simultaneously increase local capital efficiency and reduce normalized LVR relative to information-agnostic AMMs. However, sufficiently noisy or stale oracles can reverse these gains. A counterfactual backtest using one-second SPY NBBO data is provided to demonstrate these trade-offs. In particular, we map the Pareto-efficient frontier of oracle-parametrized constant function market maker (OP-CFMM) designs across stylized oracle regimes.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Oracle-Parametrized AMM
Loss-Versus-Rebalancing Decomposition
Constant Function Market Maker
Capital Efficiency
Pareto-Efficient Frontier
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