danrobinson
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danrobinson
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Trying to get o3 to write a paper for me and it got stuck on a pretty basic misunderstanding of AMMs and path dependency
So we're now 10 messages deep into an argument about it
Incredibly addictive, this will replace Twitter
So we're now 10 messages deep into an argument about it
Incredibly addictive, this will replace Twitter
The deeper you get into DEX design, the sillier it feels to be dogmatic about any of it
Everything depends on fiddly microstructure details
Everything depends on fiddly microstructure details
Is there any way to do an onchain prediction market for p(doom)?
Given the impossibility of settlement in the apocalypse and the difficulty of credit in the non-apocalypse case
Given the impossibility of settlement in the apocalypse and the difficulty of credit in the non-apocalypse case
“Don’t use chains with centralized sequencers, since someday they might subtly extract value from you
Instead use decentralized sequencers that are guaranteed to extract maximum value from you, today”
Instead use decentralized sequencers that are guaranteed to extract maximum value from you, today”
I don’t think whether a sequencer is decentralized matters too much
What matters most is what rules they follow, and particularly whether they use their power to hurt users or extract value
You can have extractive decentralized sequencers, or nonextractive centralized ones
What matters most is what rules they follow, and particularly whether they use their power to hurt users or extract value
You can have extractive decentralized sequencers, or nonextractive centralized ones
Here's a mystery:
AMMs seem to be much more profitable when buying ETH than selling it
Look at how these cumulative markouts (grouped by direction) diverge over time
The pool made >$20m from its ETH buys, but lost >$24m from its ETH sells!
Any theories?
AMMs seem to be much more profitable when buying ETH than selling it
Look at how these cumulative markouts (grouped by direction) diverge over time
The pool made >$20m from its ETH buys, but lost >$24m from its ETH sells!
Any theories?
These are the cumulative 15m markouts for the Fluid ETH/USDC pool.
It has bled out $8.5m in EV, and its trades were unprofitable all the time, not just during rebalances.
There are no profits to make up for the costs from rebalancing. The pool never makes money in expectation.
It has bled out $8.5m in EV, and its trades were unprofitable all the time, not just during rebalances.
There are no profits to make up for the costs from rebalancing. The pool never makes money in expectation.
Respect for @0xfluid posting this post-mortem
But their proposed solution—to make liquidity more concentrated—seems like the wrong choice
The pool is not just losing money during rebalances. It is losing money constantly—AFAICT, fees do not make up for arb losses
So concentrating liquidity more would be a double whammy—faster loss to arbs between rebalances, and more frequent rebalances
But their proposed solution—to make liquidity more concentrated—seems like the wrong choice
The pool is not just losing money during rebalances. It is losing money constantly—AFAICT, fees do not make up for arb losses
So concentrating liquidity more would be a double whammy—faster loss to arbs between rebalances, and more frequent rebalances
Fast trustless bridges usually require payments to be locked up in escrow
But what if users could just send to the relayer—trustlessly, and at a fraction of the capital and gas cost of the escrowed model?
Introducing Across Prime, a new design from me @hal2001 @mrice32
🧵
But what if users could just send to the relayer—trustlessly, and at a fraction of the capital and gas cost of the escrowed model?
Introducing Across Prime, a new design from me @hal2001 @mrice32
🧵
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