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@robotevm

working on https://t.co/Pa7kB2amt5 optimizing your trade execution, yc alum

C-137 Katılım Eylül 2018
563 Takip Edilen2.2K Takipçiler
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robot@robotevm·
me monitoring the situation while it's sunny outside
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robot@robotevm·
1/ a comparison of revert rates across bridges data is collected from actual trades on @matchametaxyz over the last few months these numbers are looking very solid across the board
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robot@robotevm·
@mayorxbt i mean more than anakin's character hahaha, didn't know about eren but makes sense!
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MAYOR
MAYOR@mayorxbt·
@robotevm dune even inspired Star wars' Anakin character and Eren
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robot@robotevm·
small tam meme
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robot@robotevm·
@kiraonchain we used the bridge txns completed on matcha meta for the past few months
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niharika
niharika@kiraonchain·
Great analysis. What routes did you use in your test dataset? ETA estimation is tricky because it depends on variables that shift in real time. Indexing time, relayer liquidity, api response time, rpc availability, and finality assumptions all affect fill times differently per route.
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robot@robotevm·
1/ a thread on bridge ETA accuracy we’ve been going deep in swap meta-aggregation, taking a closer look at bridges as well. i pulled estimated vs realized completion times for bridge txns and put together a breakdown by bridge. graph below is the high-level overview
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Matcha Meta
Matcha Meta@matchametaxyz·
Solana just launched on @matchametaxyz 2 days ago. And we’re already shipping. @dflow is now live - More liquidity. - Better routing. - Better swaps. This is what meta aggregation looks like.
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DFlow
DFlow@dflow·
Powering the largest applications across any chain. DFlow is now live in @Matchametaxyz from @0xProject. Matcha Meta is a meta DEX aggregator that routes swaps across multiple DEX aggregators to find the best execution.
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robot@robotevm·
frogot to mention that this is all based on bridge txns that happened on @matchametaxyz over the last few months
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robot@robotevm·
/ end of thread if any of the bridging teams see this, would love to get more info on what goes into estimating bridge transaction times and what makes it so hard
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robot@robotevm·
@SuriPuri23 don't have any insights into this myself either, added at the end of the thread that i would be interested in learning more about this problem from bridge providers
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Suri
Suri@SuriPuri23·
@robotevm why is estimating bridging time so hard? with a large enough dataset across diff assets and chains wouldn't it be possible to model it?
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