# Provisioning in Liquidity Pools

#### Overview

Liquidity pools form the bedrock of decentralised finance ("DeFi"). They are the mechanism that enables users to swap freely between tokens without relying on traditional order books or central intermediaries. In these pools, users, known as liquidity providers ("LPs"), deposit pairs of assets into automated market makers ("AMMs"). Each time a swap occurs, a small fee is charged and distributed proportionally to LPs, creating a sustainable and organic source of yield within DeFi.

#### The Evolution of Liquidity Provision

When AMMs were first introduced, liquidity was deployed uniformly across the full price spectrum. This design was groundbreaking for its time but highly capital-inefficient, as most liquidity sat unused in price ranges far from where actual trades occurred.

Newer innovations, such as concentrated liquidity, transformed this dynamic. Providers can now allocate their capital within a narrower, active price range, allowing for far greater capital efficiency and higher yield potential. By focusing liquidity where trading happens most frequently, each dollar of capital deployed can generate significantly more in fees.

#### Elemental’s Liquidity Pool Strategies

At Elemental, we employ a range of strategies designed to maximize returns while managing risk across different market conditions:

* **Highly Concentrated Stable Pools:**\
  In pools where both assets maintain a tight price correlation (such as stablecoin pairs), we deploy liquidity in extremely narrow bands. This allows us to capture consistent trading fees with minimal impermanent loss.
* **Drift Strategies with Yield-Bearing Tokens:**\
  For pools that include a yield-bearing asset - for example, a liquid staking token or an yield-bearing stablecoin, we employ strategies that drift along the natural yield curve of the underlying asset. This lets us compound both swap fees and the base yield, amplifying overall returns.

#### Deep Understanding

At Elemental, our advantage lies not in generic optimization or automation, but in a deep understanding of the underlying assets that make up each liquidity pool. Every token behaves differently.

For example, two LSTs may accrue value in very different ways: one might increase linearly throughout the staking epoch, while another delivers most of its yield in a final-hour adjustment. By understanding these patterns, we can customize our liquidity placement and rebalancing cycles to align with each asset’s yield dynamics.

This granular understanding allows us to capture additional performance that more generalized liquidity strategies often overlook.


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