How EigenLayer seems to be giving a boost to ETH staking
- EigenLayer was the second-largest DeFi protocol on the time of writing.
- EigenLayer’s exponential development spurred rise of tasks like Ether.fi.
EigenLayer’s development because the starting of 2024 has been nothing in need of historic.
The restaking protocol noticed a mindboggling 11x leap in whole worth locked (TVL) because the 1st of January, in accordance with AMBCrypto’s examination of DeFiLlama knowledge. The DeFi challenge, which was at present the second-largest, was not even within the prime 10 record when 2024 started.
Restaking>>Staking
One of many hottest new DeFi narratives, restaking entails repurposing staked ETH to increase safety to different functions, thus permitting stakers to earn additional rewards on their investments.
Other than staking ETH natively, customers have an choice of staking the liquid derivatives of their staked property (LSD), equivalent to these from Lido [LDO], Rocket Pool, and Coinbase.
As per a latest X publish by IntoTheBlock, a couple of quarter of all LSD was restaked on EigenLayer, whereas 2.38% of ETH’s whole provide has been deposited.
Sharp rise in ETH staking
The hype round EigenLayer additionally appeared to have boosted the broader ETH staking market.
In keeping with AMBCrypto’s evaluation of Staking Rewards’ knowledge, greater than 26% of all ETH in circulation had been locked on the community’s deposit contract at press time.
Apparently, the expansion curve went parabolic within the final month, mimicking EigenLayer’s TVL rise.
Native ETH restaking gaining traction
EigenLayer’s exponential development has additionally resulted within the rise of distinctive enterprise fashions seeking to faucet into the rising restaking market.
Ether.fi, for example, launched the so-called native restaking idea. It entails staking ETH on the protocol, which might be then robotically restaked on EigenLayer.
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That is completely different from the normal restaking concept the place a consumer deposits already staked ETH onto EigenLayer.