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Background and Motivation

Majority of the most popular Defi projects are currently on Ethereum. This includes Curve, AAVE, Convex, Yearn, Uniswap. These Defi platforms represent some of the most stable yield sources, i.e. users can earn fees and interests by providing liquidity or lending. However, users who want to participate on these platforms face significant friction because the gas fee on Ethereum L1 is notoriously high. For most average users, the gas fees far outweigh the potential gain in yield, which prevents wider Defi adoption.

At the same time, in a multichain world, more and more assets are residing on different chains. For example, wrapped ETH exists on almost all major alt L1s. However, many of the alternative L1s do not have the same selection of yield options. This means that users are stuck with two non-ideal options: keep your asset on Ethereum to access the yield opportunities, but potentially lose all your gains from gas fees. Or, keep your assets on an alt L1, but lose the yield opportunities.

xStaking offers solution to these two problems average users face by combining the low fees on modern high throughput blockchains such as Algorand, and the cross-chain messaging platform Wormhole, into a service that allows users to earn yield from Ethereum Defi protocols without leaving the low fee environment on Algorand. This makes it super simple (1-click) and cheap (pay only Algorand gas fees <$1) while retaining security through smart contracts.

Cross chain Defi typical workflow (pre xStaking)

Consider a user on Algorand who owns say 100 ALGO coins. In order for them to earn yield from Lido, while remaining liquid with their funds they have to
1. exchange ALGO for wrapped ETH (wETH) on Algorand
2. Bridge wETH on Algorand to native ETH on Ethereum via Wormhole
3. Deposit native ETH on Lido and receive stETH
4. Transfer stETH back through Wormhole and receive wstETH on Algorand

The combined gas fee for these transactions could easily exceed the value of 100ALGO, and is convoluted. In the next section we illustrate how our service can allow this user to earn staking rewards on Ethereum with low gas fees.

Typical workflow with xStaking

1. User deposits wETH into the xStaking’s Algorand endpoint, immediately receives wstETH_LP on Algorand.
2. Profit.

The user was able to do everything in one step, and pay only Algorand gas fees (<$1). All the benefits are retained (wsETH_LP is a fully liquid token, native to Algorand, and redeemable anytime for the underlying staked ETH and rewards) and more (Algorand’s instant finality and no-forks means this process is faster and more secure).

We believe that the future is Multichain, so demand will grow exponentially for low-fee, easy-to-use, cross-chain solutions. This makes xStaking a key primitive in the cross-chain DeFi landscape.

How xStaking works

The key observation is that although Ethereum transactions have high gas fees, the gas fee does not scale with the value of the transaction. Meaning, for the same transfer transaction for example, the gas fee is the same whether you are transferring 0.1ETH or 100 ETH. Our solution to the high gas fee problem is to aggregate individual users’ transactions into batches so that the users in each batch pay for the gas fee once, effectively reducing the gas fee by a factor of ~n, where n is the number of users in the batch.

Our solution consists of two “xStaking endpoints”. Endpoint A sits on the Algorand side, and endpoint B sits on the Ethereum side. Different users can deposit wETH into endpoint A (they can also directly deposit ALGO to endpointA, which will in the background use C3 exchange to swap ALGO for wETH). After depositing, users are issued stETH_LP tokens (implemented as an Algorand Standard Asset or ASA) that represent their shares in the staking pool.

Once endpoint A’s balance in wETH exceeds a prefixed threshold (say 10 wETH), the contract will automatically trigger a transaction over Wormhole, bridging the entire wETH balance in endpoint A to endpoint B on Ethereum in the form of native ETH. At this point endpoint B will automatically deposit the ETH balance to the LIDO contract, receiving stETH in return. Endpoint B will keep custody of these stETH until the users want to redeem.

To redeem, users can send the stETH_LP, along with a destination wallet on Ethereum, to Algorand endpoint A, which will then send a message to Ethereum endpoint B via Wormhole, telling endpoint B to release the funds to the user specified address.

Note that since stETH_LP (which sits on Algorand) represents the ability to redeem stETH on Ethereum, its value should be pegged to the value of the stETH that it can redeem. This means that users can trade stETH_LP for ALGO / other tokens on Algorand at any time. In particular, they can use stETH_LP as collateral to borrow assets on Algorand via for example C3. This means that the users remain liquid on Algorand, while their assets are earning staking reward on Ethereum!

Longer Term Vision

We chose to start with liquid staking because it is one of the most widely used services on Ethereum (>4million ETH staked on Lido). However, the long term vision is to become a cross-chain defi aggregator, where users can hold assets in one place (Algorand), and earn yield from any other chain. Users will no longer have to think about how their assets are distributed across many different chains, and focus solely on how to choose the best yield opportunities.

Many cross chain interoperability solutions are being built out right now, but we have yet to see any real cross chain application other than bridges. xStaking will become one of the first cross-chain native applications, and in the process democratize Defi to the next billion users.


The xStaking founding team consists of three members.

Steven Yin is a PhD student in Operations Research at Columbia. His research focuses on theoretical machine learning and mechanism design. He has previously interned at Hudson River Trading, Citadel, and Amazon. When he’s not proving theorems or writing smart contracts, he can be found training for triathlon races.

Jason Yuan is a Princeton undergraduate studying CS and Applied Math. He has previously interned at Amazon and Hudson River Trading. He has also done research in Topological Data Analysis and Federated Learning.

Nickolas Casalinuovo is a Princeton undergraduate studying CS and Neuroscience. Nick is a Founding Research Member of Princeton’s Blockchain Society. His research focuses on the adoption of emerging technologies to businesses and their practices.