Automated Market Makers (AMM): How Liquidity Pools Replace Order Books

Automated Market Makers (AMMs) revolutionized DeFi by replacing traditional exchange order books with "liquidity pools" powered by smart contracts. We analyze how this mechanism provides continuous liquidity and its inherent trade-offs.

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🕒 8:25 AM

📅 Oct 22, 2025

✍️ By Nathanael707

Defining the AMM Mechanism and Liquidity ProvisionAn Automated Market Maker (AMM) is a smart contract protocol that manages the exchange of assets automatically using a mathematical formula rather than relying on a traditional order book (buyers and sellers setting prices). Assets are deposited into a Liquidity Pool (LP) by users, and the AMM uses the ratio of assets in the pool to determine the current exchange rate and execute trades.

Weighted Comparison: AMM vs. Traditional Order BooksTraditional centralized and decentralized exchanges rely on an order book where buyers and sellers manually set bid and ask prices. This system is efficient for high volume but can suffer from low liquidity and wide spreads. AMMs sacrifice some capital efficiency for always-on liquidity. While order books offer better price control, AMMs offer unparalleled accessibility and decentralization.

Implementation and Trade Execution FlowWhen a user wants to swap Asset A for Asset B, the smart contract first calculates how much of Asset A is required to be deposited to maintain the constant ratio (K).The user deposits A, the contract automatically sends B, and the price is instantly updated for the next trader. The executed trade incurs a small fee, which is automatically distributed to the Liquidity Providers, incentivizing pool stability.
Challenges and Considerations for Liquidity PoolsThe primary risk for liquidity providers is Impermenant Loss (IL), where the value of their deposited tokens decreases relative to simply holding the two assets outside the pool. Furthermore, AMMs suffer from poor capital efficiency, as most of the liquidity near the median price is rarely used. This has driven the development of concentrated liquidity models to address these flaws.