Tick Spacing

Tick spacing is the fixed, protocol-defined distance between discrete price points, or ticks, where liquidity can be provided in a concentrated liquidity AMM like Uniswap V3. It is expressed as a multiple of the base tick, which is a 1.0001 price ratio (a 0.01% price movement). For example, a tick spacing of 10 means liquidity can only be placed at every 10th tick, corresponding to price increments of approximately 0.1%. This parameter creates a grid of permissible price ranges, balancing capital efficiency against gas costs for position management.

The choice of tick spacing is a critical trade-off determined by the pool's fee tier. Higher fee tiers (e.g., 1%) typically use wider spacing (e.g., 200) to accommodate less volatile, large-trade pairs, reducing the number of ticks and thus the gas cost for swaps that cross them. Lower fee tiers (e.g., 0.01%) use tighter spacing (e.g., 1) for highly volatile pairs, allowing liquidity providers (LPs) to concentrate capital in extremely narrow price bands for maximum efficiency. This design ensures that gas overhead is proportional to the expected trading activity and fee revenue of the pool.

From a technical perspective, tick spacing governs the granularity of the liquidity liquidity distribution curve. It directly impacts how a swap traverses the pool's liquidity: a swap execution moves from the current tick to the next initialized tick, which is always a multiple of the spacing. This also defines the minimum price range a position can have; a position's width must be at least one tick spacing. Consequently, tick spacing is a fundamental constraint in LP strategy, influencing everything from impermanent loss hedging to the precision of range orders.

Tick spacing is the fixed distance between discrete price points, or ticks, where liquidity can be concentrated in a decentralized exchange (DEX) like Uniswap V3. It is expressed as a multiple of the base tick, which is derived from the formula 1.0001^i, where i is the tick index. For example, a tick spacing of 10 means liquidity can only be placed at every tenth tick (e.g., ticks -100, -90, -80... 80, 90, 100), not at every possible price. This parameter is set per liquidity pool and is typically a power of two, such as 1, 2, 10, 60, or 200, balancing granularity against gas efficiency.

The primary function of tick spacing is to reduce gas costs and computational complexity. Without spacing, liquidity could be deposited at every one of the billions of possible ticks, making position management and swap calculations prohibitively expensive. By constraining liquidity to specific intervals, the protocol dramatically reduces the number of ticks that must be checked during a trade, optimizing the constant product formula x * y = k within each active tick range. A wider spacing (e.g., 60 for a stablecoin pair) consolidates liquidity into fewer, deeper price ranges, while a tighter spacing (e.g., 1 for an exotic pair) allows for more precise, albeit more gas-intensive, price targeting.

Choosing the correct tick spacing is a critical decision for both pool creators and liquidity providers (LPs). For LPs, it determines the precision of their position and their exposure to impermanent loss. A narrow spacing allows capital to be deployed very close to the current price, maximizing fee earnings, but requires frequent rebalancing if the price moves outside the chosen range. A wide spacing provides a larger safety net against price movement but dilutes fee income as capital is spread over a broader range. The protocol's fee tier (e.g., 0.05%, 0.30%, 1%) is often paired with a recommended tick spacing, creating a trade-off between capital efficiency and management overhead for automated strategies.

Tick spacing is a configurable integer multiple that determines the permissible locations for liquidity positions within a price range. In protocols like Uniswap V3, prices are represented as discrete ticks, which are indexed positions on a logarithmic price curve. The spacing, such as 1, 10, or 100, dictates that liquidity can only be provided at ticks whose indices are evenly divisible by this number. This creates a grid of allowable price points, balancing continuous pricing approximation with computational and storage efficiency on-chain.

The choice of tick spacing involves a fundamental trade-off between capital efficiency and gas costs. A smaller spacing (e.g., 1) allows liquidity to be concentrated within a tighter price range, maximizing fee earnings for liquidity providers (LPs) and reducing slippage for traders. However, it increases the number of potentially active ticks, leading to more complex computations and higher gas fees for swapping and position management. Conversely, a larger spacing (e.g., 100 for a stablecoin pair) reduces gas overhead but forces LPs to deposit liquidity over a wider, less efficient price band.

Protocols typically set a default tick spacing per fee tier, correlating higher fee percentages with wider spacings suitable for more volatile assets. For instance, a 0.05% fee pool might use a spacing of 10, while a 1% fee pool uses 200. This alignment ensures that the expected trading frequency and price movement volatility of an asset pair are matched with an appropriate granularity of liquidity, optimizing the overall system performance. The spacing is immutable once a pool is created, making its initial selection a critical decision for pool deployers.

From a developer's perspective, tick spacing defines the granularity of the tick data structure in the smart contract. Each tick stores liquidity net changes and fee growth data. A smaller spacing increases the cardinality of this tick bitmap, affecting the gas cost of crossing ticks during a swap. The swap algorithm must iterate through initialized ticks within the swap path, so spacing directly impacts execution complexity. This design showcases how AMMs use discretization to make continuous finance computationally feasible on blockchain virtual machines.

Understanding tick spacing is essential for advanced DeFi activities. Liquidity providers must consider it when constructing hedging strategies or calculating impermanent loss, as it defines the precision of their price range. Protocol integrators and oracle designers must account for the discrete price points when fetching spot prices or TWAPs, as the reported price will always be at the nearest valid tick. This parameter is a key differentiator between classical constant-product AMMs and their concentrated liquidity successors.