DeFined: What is Concentrated Liquidity?

An overview of the concentrated liquidity model.

Short Answer

Concentrated liquidity is a new concept of liquidity provision within decentralized finance (DeFi) platforms that claims to optimize liquidity to specific price ranges. The ranges can be set by liquidity providers based on their own unique strategies.

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Concentrated liquidity is a new concept of liquidity provision within decentralized finance (DeFi) platforms that claims to optimize liquidity to specific price ranges. Essentially, liquidity providers have the ability to concentrate their funds into specific price ranges or regions within an asset’s trading pair.

This is in contrast to the more traditional models we’ve experienced across liquidity pools so far, where traditional automated market maker (AMM) models evenly distribute liquidity across the entire price spectrum.

Using a concentrated liquidity model, a DeFi user (liquidity provider) can define price ranges or boundaries where they want to allocate their funds — a “concentrated liquidity position” within a liquidity pool. By concentrating liquidity within specific price ranges, liquidity providers aim to provide deeper liquidity and reduce slippage for trades that occur within those ranges.

Comparing Concentrated Liquidity & Traditional AMM Models

The liquidity provision model used by most AMMs uses a simple formula: x*y=k, Where x and y represent the quantities of two tokens in a liquidity pool, and k is a constant.

This model ensures that, despite changes in the ratio of tokens within the pool, the prices remain stable and allow traders the ability to swap assets.

Understanding & Visualizing Concentrated Liquidity

In a traditional, centralized exchange (CEX), we can understand the order book to look like a histogram, with data related to the active orders for the specific asset(s). With a concentrated liquidity model, we can picture the inverse.

We can imagine the traditional AMM model to have even bars, representing even liquidity across all price ranges.

Differing Models for Liquidity Provision

Within a concentrated liquidity model, the histogram reflects the areas of concentrated liquidity based on an aggregated set of the liquidity providers’ specified ranges. Areas with the longer bars reflect the areas of higher liquidity across the pool.

Per Uniswap’s documentation:

Concentrated liquidity serves as a mechanism to let the market decide what a sensible distribution of liquidity is, as rational LPs are incentivize to concentrate their liquidity while ensuring that their liquidity remains active.

If you’re a fan of the educational YouTube channel Finematics, you’ll appreciate this tutorial which cover’s Uniswap V3 in more detail. This segment starts at the Concentrated Liquidity overview.

Potential Benefits of Concentrated Liquidity:

Lower Slippage
By focusing liquidity provision within specific price ranges, concentrated liquidity models can reduce slippage for trades occurring within those ranges. Traders can execute larger orders with less impact on the asset’s price within the liquidity pool.

Gain a deeper understanding of liquidity pools here.

Capital Efficiency
As mentioned, concentrated liquidity models allow liquidity providers to allocate their funds more efficiently by targeting specific price regions based on their own analysis or investment goals. This enables them to provide higher liquidity for frequently traded price ranges while potentially reducing exposure to less frequently traded ranges.

Customizable Risk Exposure
Since liquidity providers can set their own ranges, concentrated liquidity models provides them with more control over the specific price ranges for which they choose to provide liquidity. Essentially, this allows them to tailor their risk exposure to their unique preferences and trading strategies by allocating funds to the price ranges they consider optimal.

Considerations & Potential Risks of Concentrated Liquidity

Impermanent Loss
Concentrated liquidity models do not eliminate the risk of impermanent loss, which refers to the temporary loss in asset value that liquidity providers may experience due to price changes within the pool. Depending on market conditions, asset volatility, and the chosen price ranges, impermanent loss can still occur.

Gain a deeper understanding of impermanent loss here.

Range Selection Risk
Liquidity providers need to carefully select the price ranges in which they concentrate their funds. Poorly chosen ranges or incorrect price predictions could result in suboptimal returns or potential losses. Depending on nuanced factors, concentrated liquidity models may require a liquidity provider to may closer attention to their positions when compared to a more traditional model.

Put more simply: in concentrated liquidity models, a liquidity provider may select a price range that is not used often, or at all, based on the trading activity within the pool. In this case, a liquidity provider may miss out on returns or incentives since their liquidity / range is not being used.

Increased Complexity
Concentrated liquidity models introduce additional complexity compared to traditional AMMs, requiring liquidity providers to actively manage and monitor their positions within specific price ranges. It also requires DeFi protocols to have more advanced data infrastructure to support their users with speed, accuracy, and transparency.

This is why analytics providers like Yield Monitor can support DeFi liquidity providers and protocol developers with a growing suite of high-powered portfolio and data tools.

Yield Monitor Onboarding Browser Tutorial — Impermanent Loss

Protocols Building & Leveraging Concentrated Liquidity Models

Examples of DeFi protocols that incorporate concentrated liquidity models include Uniswap V3, Balancer, Trader Joe, and Ramses Exchange. These platforms allow liquidity providers to concentrate their funds within custom-defined price ranges, enabling more tailored and efficient liquidity provision.

More Customized Concentrated Liquidity Model — an Example

It’s worth nothing that individual protocols can adopt concentrated liquidity models to their own specific needs, utility, incentive models, etc.

Protocols like Trader Joe have created more customization and ability for users, with options like Auto-Pools that automatically rebalance positions, auto-compound fees and rewards for the liquidity provider. While the liquidity provider pays a fee for this automated service, the higher ROI for contracted liquidity over a traditional AMM model means this tool might make sense for liquidity providers who can’t — or don’t want to — monitor and manage their positions.

Learn more about Trader Joe’s novel take on concentrated liquidity (“Liquidity Book”) in their documentation here. Additionally, see their resource that visualize various “bin strategies” for managing liquidity within the Trader Joe protocol.

Take a deeper dive with Liquidity Book in this introductory video from Trader Joe. Parts 2 and 3 are shown alongside this video on YouTube.

Note: This is not an endorsement of Trader Joe or Liquidity Book. This is meant to illustrate and highlight how some teams are leveraging the concentrated liquidity model with their own customizations to differentiate their products within DeFi.


For more active, hands-on liquidity providers, the concentrated liquidity model shows existing promise for higher returns and more efficient trading due to strategically placed liquidity. While we see some drawbacks with regard to passive earning, there are teams working to deploy bespoke, automated systems to bridge the gap between higher returns and more passive liquidity provision for less active DeFi participants.

Users can expect to see a widening range of adopted and customized concentrated liquidity models as more developers and teams become familiar with them.

It’s worth noting that concentrated liquidity is just one approach within the broader landscape of liquidity provision in DeFi, and its suitability depends on various factors, including individual risk appetite, asset volatility, and market conditions.

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