Uniswap Exchange

Uniswap v3 was released less than two months ago, which brought a major innovation to liquidity provision on DeFi: concentrated liquidity. Rather than offering the assets you staked in a liquidity pool over all possible prices, you are free to offer your liquidity over a specific range of prices. This innovation is expected to improve capital efficiency, while at the same time adding significant complexity to liquidity provision, requiring active monitoring in order to effectively earn fees.

In this first post, we will be discussing recent research from Harvard researchers who analyze a set of liquidity provision strategies on Uniswap v3, evaluating which strategy offers the most attractive risk-reward proposition for liquidity providers (“LPs”).

The paper is titled “Strategic Liquidity Provision in Uniswap v3”, and it develops a framework for analyzing expected price range strategies¹, which are an intuitive decision rule used to decide at which prices and with which intensity to provide liquidity on automated market makers that allow concentrated liquidity.

In the expected price range strategies proposed by the authors, liquidity is provided over a range around the current price, drawn from historical data on where the price is likely to move in the next 10 minutes (“expected price range”). Thus, the strategy uses prior experience in order to provide liquidity only in the range where the price is expected to be in the near future. This liquidity is provided within the expected price range until the price moves outside a second price range called the “move strategy range”, as indicates when to move the strategy.

A figure from the paper provides an illustration of the strategies that they propose:

Figure 2 from “Strategic Liquidity Provision in Uniswap v3”

Imagine that we are providing liquidity in an ETH/USD stablecoin pool, and that prices are divided into bins, represented as circles in the chart above. The strategy indicates that liquidity should be offered in a three bin range, the green colored circles labelled “allocation 1”, with an identical indicator range. The price begins in the center green ball with a darker overlay, which represents the current price.

The price begins to increase (shown as dark circle shifting to the right), and by t = 2 has left the range over which liquidity is being provided. This implies that the strategy must be moved, with the current price as the new center of the expected price range to be established. In t = 3 the strategy has moved the expected price and move strategy ranges, as can be seen from the change in color to yellow (“allocation 2”) and a movement of the colored bins to the right. In this same time period the price began to drop, and by t = 4 the strategy dictates another movement, with a shift of the strategy visible in t = 5 (“allocation 3”) to cover the downwards moving price.

To calibrate the expected price and move strategy ranges, the authors collected 10-minute ETH price data from March 2018 to April 2020, and estimated how likely the price is to move within this time interval, which varies within the [-3%, 3%] range. The authors consider setting the width of the expected price and move strategy ranges as a percentage of the probability that the price will be within the range in the next 10 minutes. The paper provides visual representation of this distribution of percentage price changes, which is used to derive the strategy’s ranges when a movement for the strategy is triggered:

Figure 6 from “Strategic Liquidity Provision in Uniswap v3”

Having described the general strategy, I will introduce an additional innovation the authors consider that goes beyond the flexibility currently provided by Uniswap v3. In the concentrated liquidity framework, you provide liquidity in the indicated range uniformly, that is, with a similar willingness to trade your assets as long as the price remains in your range.