AMM Pool

Users called Liquidity Providers (LPs) deposit an equal value of two tokens into the pool's reserve, receiving LP tokens as a receipt. These tokens represent their share of the pool and can be redeemed later, earning a portion of the trading fees generated by the pool.

• Impermanent Loss: The risk that the value of deposited assets changes compared to simply holding them.
• Fee Structure: LPs typically earn a small percentage (e.g., 0.01% to 1%) on every trade.

Prices are not set by an order book but by a deterministic Constant Function Market Maker (CFMM) formula, most commonly x * y = k. The product (k) of the two token reserves must remain constant, causing the price of one token to rise as its reserve decreases.

• Slippage: The price impact of a large trade, which increases as the trade size approaches the available liquidity.
• Spot Price: The instantaneous price is simply the ratio of the two reserves.

Traders can swap one token for another directly with the pool's smart contract. To swap Token A for Token B, the trader sends A to the pool, and the contract sends B back, automatically adjusting the reserves and price according to the CFMM formula.

• Swap Fee: A fee (e.g., 0.3%) is deducted from the input amount before the swap, which is added to the reserves for LPs.
• Minimum Output: Traders set a slippage tolerance to protect against front-running and large price movements.

An evolution of the basic model where LPs can allocate their capital to a specific price range instead of the full (0, ∞) spectrum. This increases capital efficiency for the chosen range, allowing for deeper liquidity and lower slippage around the current price.

• Active Management: LPs must adjust or "rebalance" their positions as the market price moves outside their chosen range.
• Examples: Uniswap V3 and its forks pioneered this model.

Different CFMM formulas create pools with distinct trading curves and use cases.

• Constant Product (x*y=k): Standard for most volatile asset pairs (e.g., ETH/DAI).
• Constant Sum (x+y=k): Used for stablecoin pairs (e.g., USDC/DAI), often implemented as a StableSwap curve (like Curve Finance) which blends constant product and constant sum for low slippage.
• Weighted Pools: Allow for unequal weightings of assets (e.g., 80/20 BAL/WETH pools in Balancer).

Many AMM protocols are governed by decentralized autonomous organizations (DAOs) that control key parameters via governance tokens. These parameters include:

• Protocol Fee: A portion of the trading fees that may be directed to a treasury.
• Fee Tiers: Different pools can have different swap fees (e.g., 0.05% for stablecoins, 0.3% for standard pairs, 1% for exotic pairs).
• Whitelisting: Deciding which tokens or factory contracts can create new pools.

Impermanent loss is the opportunity cost incurred by liquidity providers when the price of deposited assets diverges from the price at deposit time. It occurs because the AMM's constant product formula (x * y = k) automatically rebalances the pool, selling the appreciating asset and buying the depreciating one.

• Mechanism: If ETH price doubles relative to USDC, the pool sells ETH for USDC, reducing the LP's ETH holdings.
• Impact: The LP's portfolio value in the pool becomes less than if they had simply held the assets. Loss becomes permanent upon withdrawal.

AMM pools are governed by smart contracts, which are vulnerable to bugs, logic flaws, and exploits. A single vulnerability can lead to the complete loss of user funds.

• Historical Examples: The 2021 PancakeBunny exploit ($200M+) involved a flash loan attack manipulating a pool's price oracle.
• Mitigation: Relies on rigorous audits, formal verification, and bug bounty programs. Users must assess the audit history and the team behind the protocol.

Many AMMs or related protocols (e.g., lending) rely on price oracles derived from pool prices. These can be manipulated via flash loans to drain funds.

• Attack Vector: An attacker borrows a large amount of asset X via flash loan, swaps it in the target pool to drastically move the price, triggering faulty liquidations or minting in a dependent protocol, then reverses the swap.
• Defenses: Protocols use time-weighted average prices (TWAPs), multiple oracle sources, and circuit breakers to resist manipulation.

Advanced AMMs like Uniswap V3 allow concentrated liquidity within custom price ranges. This introduces nuanced risks.

• Range Risk: If the price moves outside the LP's set range, their assets stop earning fees and become 100% exposed to the less valuable asset.
• Slippage: Large trades in pools with low liquidity (or concentrated LPs) experience high slippage, where the execution price is worse than expected. Traders must set slippage tolerances to avoid front-running MEV bots.

Many AMM protocols have administrative privileges or are governed by a DAO holding a treasury and upgrade keys. This centralization creates risk.

• Upgradeability: A malicious or compromised governance vote could upgrade the contract to a malicious version.
• Fee Switch: Governance may activate a protocol fee, diverting a portion of LP rewards.
• Mitigation: Assess the protocol's governance process, time locks on upgrades, and the distribution of governance tokens.

AMM pools are money legos in DeFi, interconnected with lending protocols, yield aggregators, and derivatives. This creates systemic risk.

• Contagion: A failure or exploit in one major pool or protocol can cascade, causing liquidations and insolvencies across the ecosystem (e.g., UST depeg affecting Curve's 3pool).
• Integration Risk: Yield strategies that auto-compound LP tokens add layers of smart contract risk from each integrated protocol.

The most common AMM pricing algorithm, defined by the equation x * y = k. It ensures liquidity is always available by automatically adjusting the price of one asset based on the available quantity of the other. This creates the slippage experienced in trades.

• Example: In a pool with ETH and DAI, if a trader buys a large amount of ETH, the pool's ETH reserve decreases, making the next unit of ETH more expensive in DAI terms to maintain the constant k.

An entity that deposits an equal value of two assets into an AMM pool to provide liquidity. In return, they receive LP tokens, which represent their share of the pool and entitle them to a portion of the trading fees.

• Role: Enables trading by funding the pool's reserves.
• Risk: Exposed to impermanent loss, which occurs when the price ratio of the deposited assets changes compared to holding them.

A temporary loss of capital experienced by Liquidity Providers compared to simply holding the assets. It occurs when the price of the deposited assets diverges from their price at deposit, due to the AMM's rebalancing mechanism.

• Mechanism: The AMM automatically sells the appreciating asset and buys the depreciating one to maintain the pool ratio, locking in a relative loss.
• Mitigation: Often offset by accumulated trading fees, making it 'impermanent' unless the LP withdraws during the price divergence.

The difference between the expected price of a trade and the executed price. In AMMs, slippage is inherent due to the constant product formula; larger trades move the price more significantly as they consume liquidity.

• Cause: Executing a trade changes the pool's reserves, altering the price for subsequent units of the asset.
• Management: Traders set a slippage tolerance (e.g., 0.5%) to prevent unfavorable trades in volatile markets.

An advanced AMM design that allows Liquidity Providers to allocate capital within specific price ranges, rather than across the entire 0 to ∞ price curve. This dramatically increases capital efficiency.

• Example: Uniswap V3 popularized this model.
• Benefit: LPs can provide deeper liquidity around the current market price, earning more fees with less capital, but must actively manage their chosen price ranges.

A source of external price data. While AMM pools generate prices internally, these can be manipulated by large trades. Oracles provide a tamper-resistant reference price for other DeFi protocols.

• Use Case: Lending protocols use oracles (not AMM spot prices) to determine collateral values and loan health.
• AMM Integration: Some advanced AMMs, like Balancer, can themselves act as on-chain price oracles by using time-weighted average prices (TWAPs) from their pools.