Impermanent loss in crypto: Understanding the real risk of providing liquidity
Impermanent loss (IL) is a risk associated with providing liquidity in decentralized finance (DeFi). This loss occurs when the value of tokens held in a liquidity pool drops compared to holding those tokens directly in a crypto wallet. The primary cause of IL is the price divergence between the tokens in the pool due to how automated market makers (AMMs) calculate swap values. However, swap fees earned from trades can often offset the impermanent loss, resulting in a net gain.
To understand IL, you must first grasp how liquidity pools function in DEXs. Unlike traditional exchanges with order books, AMMs use liquidity pools consisting of pairs of tokens. For instance, a pool may hold ether (ETH) and USDC, a stablecoin pegged to $1. The AMM employs a constant product formula (x * y = k) to manage token prices and ratios, ensuring the formula's constant value (k) remains unchanged during trades.
When you provide liquidity to a pool, you deposit your tokens, receiving LP tokens representing your share of the pool. Liquidity providers earn a fee from every swap, proportionate to their share of the pool's inventory. These fees, along with incentives, compensate for the impermanent loss. The loss is called "impermanent" because the tokens remain in the pool, becoming permanent only when withdrawing.
If token prices remain stable, there's no impermanent loss. However, when prices diverge, the pool adjusts your holdings, causing a slower growth rate in your pool position compared to holding the same tokens. This gap represents the impermanent loss, which measures the opportunity cost of not holding the tokens directly. In a concrete example, depositing 1 ETH and 2,000 USDC into a pool when ETH trades at $2,000 results in a $344 impermanent loss when ETH's price later doubles to $4,000, despite still having a higher value than the initial deposit.
Written by urgent.news from Yahoo Finance's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.