Price Range

In the context of concentrated liquidity protocols like Uniswap V3, a price range (or tick range) is a user-defined interval, specified by a lower price (P_low) and an upper price (P_high), within which a liquidity provider's deposited assets are utilized for trading. Unlike traditional constant product AMMs where liquidity is distributed uniformly across all prices (from 0 to ∞), concentrated liquidity allows capital to be allocated to a specific, finite price band. This dramatically increases capital efficiency for the provider, as their funds are only deployed where they are most likely to be swapped, earning more fees per dollar of capital at the cost of requiring active management.

The mechanics are governed by a tick-spacing system, where the continuous price curve is discretized into individual ticks. A provider selects a starting and ending tick to define their active range. When the market price of the asset pair moves entirely outside this defined range, the provider's position becomes 100% composed of one of the two assets and stops earning fees. For example, a provider depositing ETH/USDC might set a price range from $1,500 to $2,500. Their liquidity is only used for swaps occurring within that band; if ETH's price falls to $1,400 or rises to $2,600, their position is no longer active.

Managing a price range introduces impermanent loss dynamics that are more pronounced and complex than in simpler AMMs. The narrower the range, the higher the fee-earning potential, but also the greater the risk of the price exiting the range, rendering the capital idle. This creates a trade-off between fee income and portfolio rebalancing frequency. Strategies often involve setting ranges around perceived support and resistance levels or using wider bands for a more passive, "set-and-forget" approach that mimics the behavior of older AMMs like Uniswap V2.

In traditional AMMs like Uniswap V2, liquidity is distributed uniformly across the entire price spectrum from zero to infinity. A price range (or concentrated liquidity) changes this model by allowing liquidity providers (LPs) to allocate their capital to a specific, user-defined interval. This means an LP's funds are only used for swaps when the asset's market price is within their chosen min price and max price. Capital outside this range sits idle, enabling much greater capital efficiency for the same level of liquidity within the active band.

The mechanism is defined by a liquidity curve, typically implemented via the x * y = k constant product formula, but constrained within the chosen bounds. When the price moves to the edge of the range, one of the two assets in the pool is fully depleted, converting the entire position into a single asset. This creates an impermanent loss profile that is bounded by the range limits; loss is only realized if the price exits the range and does not return. The narrower the range, the higher the fee-earning potential but also the greater the required active management and risk of the price moving outside.

Setting a price range involves strategic decisions. A wide range (e.g., ±50% around current price) requires less frequent adjustment but offers lower fee density. A narrow range (e.g., ±5%) provides high fee returns but acts more like a limit order, requiring the LP to actively rebalance or reposition the range as the market moves. This concept is fundamental to concentrated liquidity AMMs such as Uniswap V3, PancakeSwap V3, and Trader Joe's Liquidity Book, where it forms the basis for advanced strategies like range orders and passive market making.

In automated market makers (AMMs) like Uniswap V3, a price range (or liquidity range) is defined by a lower tick and an upper tick. This creates a virtual bucket of liquidity that only interacts with trades when the market price of the asset pair is within that specific interval. Visualizing this range is often done on a chart, where the active band is highlighted against the current price line, showing exactly where a provider's funds are working. When the price exits the range, that portion of liquidity becomes inactive and stops earning fees, a state known as being out-of-range.

The visualization of concentrated liquidity is key to understanding capital efficiency. Unlike traditional AMMs where liquidity is spread across all prices (0 to ∞), a narrow, strategically placed price range allows the same amount of capital to provide deeper liquidity around the current price. On a liquidity distribution chart, this appears as a tall, narrow peak within the chosen bounds, contrasting with the flat, wide curve of full-range liquidity. This concentration amplifies fee earnings while the price stays in range but introduces impermanent loss risk if the price moves beyond it.

For practical management, interfaces display a user's active price ranges in a dashboard, often as colored bands on a price chart. Key metrics visualized include the current price relative to the range, the fee accrual rate, and the asset composition (e.g., the ratio of ETH to USDC), which changes as the price moves within the range due to the constant product formula. Advanced tools may show historical performance backtesting, simulating how a chosen range would have performed based on past price volatility, aiding in strategic range placement.