Skn

Trying to make sense of this crazy #crypto world

[Beff (e/acc) @beffjezos]

These AI Doomertards have kept making strong predictions that ended up being totally false.

Your Bayesian posterior should be that their predictions are dogsh*t and you should stop listening to them.

[Initia 🪢 @initia]

civitia mainnet June 6th, 9 AM UTC.

what city are we taking over?

[CK @Vitamul]

More gpus than rndr this shit ain’t a shitcoin niggas despite me just referring to it as “this shit”. This shit is the most accessible lowest upfront cost distributed gpu network available to enterprise clients and individuals to deploy existing open source LLM’s and image generation models and run training on datasets in history at this point in time @distributeai

GPU’s are literally the most in demand tech product in history and nvidia can’t produce enough of them to satisfy the demand from the commercial side

This shit got perfect PMF at the perfect point in time

When you buy fartcum coin or pissballs coin praying for an ansem or jingtao or cooker shill or some shit just remember you could be buying a coin that grants you access to this network but you’re choosing to buy a piece of shit memecoin that is guaranteed to be down 95% within 6 months

Remember that the coin only got one week of history atp

Remember how to zoom out

You want asymmetric upside its right here in front of you

They selling 2 dollars for 1.8 cents rn

But you like skinny scrawny guy

[jeff.hl @chameleon_jeff]

Why transparent trading improves execution for whales

Throughout Hyperliquid’s growth, skeptics questioned the platform's ability to scale liquidity. These concerns have been resolved now that Hyperliquid is one of the most liquid venues globally. With Hyperliquid’s adoption by some of the largest traders in crypto, discussion has shifted to concerns around transparent trading. Many believe that whales on Hyperliquid are:
1) frontrun as they enter their position
2) hunted because their liquidation and stop prices are public

These concerns are natural, but the opposite is actually true: for most whales, transparent trading improves execution compared to private venues.

The high level argument is that markets are efficient machines that convert information into fair prices and liquidity. By trading publicly on Hyperliquid, whales give market makers more opportunity to provide liquidity to their flow, resulting in better execution. Billion dollar positions can have better execution on Hyperliquid than on centralized exchanges.

This post covers a complex line of reasoning, so it may be more compelling to start with a real-world example from tradfi to demonstrate this universal principle. After all, actions speak louder than words.

Example

Consider the largest tradfi ETFs in the world that need to rebalance daily. Examples include leveraged ETFs that increase positions when prices move favorably and decrease positions in the other direction. These funds manage hundreds of billions of dollars in AUM. Many of these funds choose to execute on the closing auction of the exchanges. In many ways this is a more extreme version of whales trading publicly on Hyperliquid:
1. These funds’ positions are known almost exactly by the public. This is true on Hyperliquid as well.
2. These funds follow a precise strategy that is public. This is not true on Hyperliquid. Whales can trade however they want.
3. These funds trade predictably every day, often in massive size. This is not true on Hyperliquid. Whales can trade whenever they want.
4. The closing auction gives ample opportunity for other participants to react to the ETFs’ flows. This is not true on Hyperliquid, where trading is continuous and immediate.

Despite these points, these ETF managers opt into a Hyperliquid-like transparency. These funds have full flexibility to make their flows private, but proactively choose to broadcast their intentions and trades. Why?

History of transparency in electronic markets

A complementary example is the history of electronic markets. As summarized above, markets are efficient machines that convert information into fair prices and liquidity. In particular, electronic trading was a step-function innovation for financial markets in the early 2000s. Prior trading occurred largely in trading pits, where execution quality was often inconsistent and spreads wider. With the advent of programmatic matching engines transparently enforcing price-time priority, spreads compressed and liquidity improved for end users. Public order books allowed market forces to incorporate supply and demand information into fairer prices and deeper liquidity.

The spectrum of information

Order books are classified by their information granularity. Note that L0 and L4 are not standard terminology, but are included here as natural extensions of the spectrum.
L0: No book information (e.g. dark pools)
L1: Best bid and offer
L2: Levels of the book with price, total size of level, and optionally number of orders in the level
L3: Individual anonymized orders with time, price and size. Some fields including sender are private
L4 (Hyperliquid): Individual orders with complete parity between private and public information

Each new level of order book granularity offers dramatically improved information for participants to incorporate into their models. Tradfi venues stop at L3, but Hyperliquid advances to L4. Part of this is necessity, as blockchains are transparent and verifiable by nature. However, I argue that this is a feature, not a bug.

Zooming out, the tradeoff between privacy and market efficiency spans the full spectrum from L0 to L4 books. On this scale, L3 books can be viewed as an arbitrary compromise, not necessarily optimal. The main argument against L4 books is that some strategy operators prefer privacy. Perhaps there is some alpha in the strategy that is revealed by the order placement. However, it’s easy to underestimate the sheer talent and effort going into the industry of quantitative finance, which backs out much of these flows despite anonymized data. It’s difficult to enter a substantial position over time without leaking that information to sophisticated participants.

As an aside, I believe financial privacy should be an individual right. I look forward to blockchains implementing privacy primitives in a thoughtful way in the coming years. However, it's important not to conflate privacy and execution. Rather than hand-in-hand concepts, they are independently important concepts that can be at odds.

How market makers react to information

One might argue that some privacy is still strictly beneficial. But privacy is far from free due to its tradeoff with execution: toxic flow can commingle with non-toxic taker flow, worsening execution for all participants. Toxic flow can be defined as trades where one side immediately regrets making the trade, where the timescale of "immediate" defines the timescale of the toxicity. One common example is sophisticated takers who have the fastest line of communication between two venues running toxic arbitrage taker strategies. Market makers lose money providing liquidity to these actors.

The main job of a market maker is to provide liquidity to non-toxic flow while avoiding toxic flow as much as possible. On transparent venues, market makers can categorize participants by toxicity and selectively size up to provide as a non-toxic participant executes. As a result, a whale can quickly scale into a large position faster than on anonymized venues.

Summary

Finally returning to the example of ETF rebalancing, I imagine the conclusion of rigorous experimentation confirmed the points above. Addressing the specific subpoints in the introduction:
1) A transparent venue does not lead to more frontrunning than private venues. Rather, traders with consistently negative short term markouts benefit by broadcasting their autocorrelated flow directly to the market. Transparent venues offer a provable way for every user to benefit from this feature.
2) Liquidations and stops are not “hunted” on transparent venues more than on private venues. Attempts to push the price on a transparent venue are met with counterparties more confident to take the mean reversion trade.

If a trader wants to trade massive size, one of the best things to do is tell the world beforehand. Though counterintuitive, the more information that is out there, the better the execution. On Hyperliquid, these transparent labels exist at the protocol level for every order. This enables a unique opportunity to scale liquidity and execution for traders of all sizes.

[gum @gumsays]

Risk assets look toppy but the dollar looks so cooked that there is no other path than the one where you hold lots of Bitcoin

[Georgios Konstantopoulos @gakonst]

Introducing the Porto Developer Preview!

What if passwords did not exist?

What if the web was built natively for payments?

Porto is the open-source Typescript library we've built @ithacaxyz that gives accounts the superpowers to answer these questions.

Learn more below 🧵

[Zhu Su @zhusu]

supercycle (WHERE'S THE BOUNCE EDITION) https://t.co/cGvkaKq8GX

[echo @echodotxyz]

Today, we are announcing Sonar – a new product by Echo that lets anyone host a public token sale.

[gum @gumsays]

People calling for a true altseason have lost the plot

We will never get a full-blown altseason again because BTC maturing directly translates to a maturing altcoin market

This means markets are starting to shift into real value generation, and most crypto protocols are technically worth $0

It's unironically easier than ever to find the good businesses because almost no one in crypto seems to care to find them

Even if they do, they would rather gamble on pumpdotfun

[Cobie @cobie]

Just learned this invert-and-roll duvet cover changing technique and changed my life, thanks for reading

[Doran.artisan.cash @doranmaul]

🧵
Most people don’t realize how close we are to the shift.

The one where DeFi stops feeling like a sandbox, and starts feeling like the default.

Let’s talk about what has to happen.
And why it’s already underway.

[gum @gumsays]

If you could, would you take an 18% annual return for 2 years?

@MetaWealth just launched their 11th Tokenized Asset:
> Located in Rome
> Locked for 22 months
> 33% return target (18% annualised)
> You can invest from as little as $105

Making money is not the hard part, keeping it is.

Diversify, even if a bit.

[The Daily Degen @thedailydegenhq]

The Daily Degen - Saturday, May 24th, 2025

Apps, Bills, Reminders, Airdrops, Macro, Videos, + New Projects!

Shout-out to mentioned projects and tickers: $RESOLV, $HUMA, $TAO, $KAITO, $BTC, $ETH, $SYRUP, $HYPE, $AVAX, $ZBCN, $QUAI, $GODS, $OIK, $GEAR, @LuckyFuture_AI, @catena_labs, @eth_milano

And shout-out to gigabrain accounts mentioned with >10k followers (make sure to give them a follow!): @mattdotfi, @castle_labs

And please RT/etc to support!

Link in next tweet 👇

[Henrik @Henrik_on_HL]

There are currently ~$27M in HYPE sell orders between $38–$40.

[Dan Greer @0xUxDesign]

DeFi doesn’t need to feel like a science experiment.

Had a great chat with @Malakincrypto for @TheStreet on why we built @defiapp to feel like a CEX but stay 100% on-chain.

https://t.co/EgxHnkXC6f

[*Walter Bloomberg @DeItaone]

US MAY CONSUMER CONFIDENCE INDEX 98.0 (CONSENSUS 87.0) - CONFERENCE BOARD

[Pump.fun @Pumpfun]

X might be down, but the trenches are up. Always.

[gainzy @gainzy222]

my dms are broken and disappearing

if i dont reply it’s bc i literally can’t

[Unit @unitxyz]

uSOL and uFART have been deployed on the HyperEVM. Contract addresses below.

uSOL:
0x068f321Fa8Fb9f0D135f290Ef6a3e2813e1c8A29
uFART:
0x3B4575E689DEd21CAAD31d64C4df1f10F3B2CedF

[Pump.fun @Pumpfun]

return to memes