Automated Market Making and Loss-Versus-Rebalancing
Dr. Anthony Lee Zhang
Assistant Professor of Finance
Booth School of Business
University of Chicago
We consider the market microstructure of automated market making and, specifically, constant function market makers (CFMMs), from the economic perspective of passive liquidity providers (LPs). In a frictionless, continuous-time Black-Scholes setting and in the absence of trading fees, we decompose the return of an LP into a instantaneous market risk component and a non-negative, non-decreasing, and predictable component which we call “loss-versus-rebalancing” (LVR, pronounced “lever”). Market risk can be fully hedged, but once eliminated, LVR remains as a running cost that must be offset by trading fee income in order for liquidity provision to be profitable. We show how LVR can be interpreted in many ways: as the cost of commitment, as the time value for giving up future optionality, as the compensator in a Doob-Meyer decomposition, as an adverse selection cost in the form the profit of arbitrageurs trading against the pool, and as an information cost because the pool does not have access to accurate market prices. LVR is distinct from the more commonly known metric of “impermanent loss” or “divergence loss”; this latter metric is more fundamentally described as “loss-versus-holding” and is not a true running cost. We express LVR simply and in closed-form: instantaneously, it is the scaled product of the variance of prices and the marginal liquidity available in the pool, i.e., LVR is the floating leg of a generalized variance swap. As such, LVR is easily calibrated to market data and specific CFMM structure. LVR provides tradeable insight in both the ex ante and ex post assessment of CFMM LP investment decisions, and can also inform the design of CFMM protocols.