Bridge... Then Anchor!

    This dashboard investigates what's being brought over from the Binance Smart Chain (BSC) and Ethereum (ETH) networks through the shuttle, and what users are doing immediately after. PS it looks like Anchor deposits!

    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...

    Executive Summary

    • The value being brought over from the ETH network is almost 20x that of the value being bridged from BSC, while BSC has 2x the unique wallets.
    • UST is the most dominant token being bridged from both chains representing 87% of the value transferred
    • Wallets from ETH and BSC are doing roughly the same things, depositing into the Anchor market, and buying LUNA!

    The Bridges

    Choosing to focus on the Binance Smart Chain (BSC) and Ethereum (ETH) network bridge activities, I first looked at the volume and value being brought over from both BSC and ETH networks. This first graph shows the 6-hour moving average volume being bridged to Terra from both ETH and BSC shuttles, with the ETH shuttle having much more variability due to large transfers. With the volume on the ETH network being much greater than that of BSC, we can see that transfers from the BSC are much smaller on average than those from ETH.

    ETH Shuttle

    The Ethereum shuttle, while only having 7.24k unique wallets interacting with it, has brought in over 2B USD to the Terra Ecosystem. This could be in part due to ETH's price dipping in the last week, while LUNA is holding strong. This tells us that whales (large crypto holders) are moving significant assets over to Terra to interact with its protocols.

    BSC Shuttle

    While the BSC has brought in much less value, over 17k unique wallets have used the shuttle to Terra. As opposed to the ETH network, the BSC shuttle has had much more unique activity over the last 30 days, while bringing in much smaller quantities totaling 131M USD.

    It's UST's world

    Now that we have seen how much value and how frequently assets are being brought over to the Terra network, in what form is it coming in?

    In the below graph, we can see that UST is dominant! Holding over 87% of the USD value bridged, with LUNA just over 10% and MIR just under 2%. What's also interesting is that a variety of mAssets, are being bridged over as well, however only totaling roughly >1%.

    First stop, Anchor!

    Once users have brought over their assets to Terra, it looks like most of the first interactions are going to Anchor's protocol. Crazy how many other protocols/contracts are being listed here, TerraShiba, Luna Monkey Business NFTs, galactic punks, etc. Less than 0.5% are going for these NFTs, but cool to see that they still show some representation!

    Astroport, being launched in December 2021, is also creating a small buzz, being just over 8% of first interactions, behind only Anchor and Terraswap. Definitely cool to see a new protocol finding success on the Terra ecosystem.

    *Note: The following pie charts are based on unique wallet interaction counts and not by volume

    Loading...
    Loading...

    Going a little bit deeper into the analysis, we can see that the majority of interactions are with the anchor market, while Terraswap operations are mostly swaps for LUNA, supported by the fact that UST is being brought over the shuttles.

    the bootstrap auction and the uusd/uluna LP are with respect to Astroport's launch.

    Looking only at those wallets from the BSC, we can see that the trends are similar, meaning that there are no significant differences between the BSC shuttle users and ETH shuttle users once they arrive to Terra. Everyone's doing the same thing!

    A little more about Anchor

    Touching on Anchor some more, as it's shown to be the most prevalent protocol used, anchor deposits are steady with a minimum 6 hour average of 1M USD, with a total deposited value over the last 30 days being just over 6.5B.

    Approach

    • 30 day window
    • First Identified shuttle addresses, then identified next transactions for distinct addresses
    • looked at unique addresses interacting with specific protocols instead of value-based, reducing the influence of whales