User:Caputmundi22/sandbox

= Impermanent Loss = In Decentralized Finance, impermanent loss is a phenomenon whereby the value of assets locked in a smart contract decreases due to decorrelation of their prices. It arises due to the original design of Automated Market Makers, which determines asset prices based on their relative quantities in a pool and not on market data. Liquidity Providers are the main victims of impermanent loss, but traders are often affected too.

Definition
Impermanent loss arises for two reasons:


 * Protocol design: many AMMs, like Uniswap v2, use the constant product formula . This formula rules that the product of asset quantities in the pool must stay constant at all times. If the price of one asset increases against the other, the pool automatically reduces its quantity. As a consequence, pools are always selling their best-performing asset, which for their LPs.
 * No external market data: the only way to change asset prices in the pool is to adjust their quantities through buying and selling. There are traders specialised in this business: arbitrage traders . They generate profits by exploiting price differences between pools and centralized exchanges . Their activity extracts value from the pool’s LPs.

It is possible to calculate the IL for any asset and price using an Impermanent Loss Calculator.

Consequences on investors and traders
A recent study analysed 17 pools on Uniswap v3, covering 43% of TVL. If found out that the total IL suffered by LPs during the 4.5 month period was $260.1m. The LPs earned $199.3m in fees over the period, which translates in a net loss of around $60m for the whole group. A total of 49.5% of LPs in the studied pools faced negative returns.

With this data in mind, we can estimate that each year several billion dollars in value are lost by LPs due to Impermanent Loss. At least part of this is passed on to traders through an increase in trading fees.

Proposed solutions to Impermanent Loss
In another recent paper, researchers have been highlighting the inefficiency of current AMMs and the need to better match transaction fees with LVR (loss versus rebalancing). They suggest the use of price oracles, dynamic fees, or both. Examples of this new generation of AMMs include Swaap Finance.