New Protocol Aims to Reduce Non-Permanent Losses in Crypto Liquidity Pools
A recently introduced protocol, Layer-Based, developed by the Curve Finance platform, aims to mitigate non-permanent losses for liquidity providers (LPs) of tokenized Bitcoin (BTC) and ether (ETH). It proposes a market-driven approach to tackle token inflation and emissions.
Non-permanent loss occurs when the value of assets in a liquidity pool changes, causing users to end up with less than if they had simply held onto their crypto without providing liquidity.
According to Dr. Egorov, if the funds in the liquidity pool are allocated relative to the square root of Bitcoin’s price, this will lead to non-permanent losses. He explained, “These square root dependencies cause the issue. To address it, we need to eliminate the square root—essentially, we should square it.”
The protocol operates through combined leverage, maintaining 200% excess positions by leveraging CRVUSD, a decentralized stablecoin pegged to the US dollar.
This structure ensures that the position price remains exactly double the deposited collateral, effectively addressing the square root dilemma associated with non-permanent losses, as noted by Egorov.
For years, non-permanent losses have been a significant hurdle for liquidity providers, discouraging participation in future LP activities.
Yield Options Offer Flexibility in Token Emissions
Users can now choose to receive returns from either tokenized Bitcoin or yield-based tokens, facilitating market-driven strategies to adjust inflation rates and manage token emissions, according to Curve founders.
“In different market circumstances, a varied approach is essential,” Egorov mentioned. He pointed out that during bullish speculative markets, users often opt to hold YB tokens, anticipating rising prices, while actual yields can manifest on the platform.
Conversely, in a prolonged bear market, users tend to adopt a safer strategy, opting for yields in Bitcoin to counterbalance YB token inflation that arose during more speculative times, thereby delivering “optimal” value for those tokens.
