jeff.hl Profile picture
May 29, 2024 1 tweets 1 min read Read on X
Reminder: the Hyperliquid dev team does not profit from increased activity as it does not collect trading fees. On the contrary, it is entirely self-funded with exponentially increasing burn. There is not a single private investor.

>$25M of revenue has gone back to the community through HLP. Another project could have easily pocketed some or all of these profits.

What’s the point of all this? To build something that really matters. When finance moves onchain, it will bring trillions of dollars of value to billions of users. It won’t move for a half-baked system, but the Hyperliquid L1 has a shot.

Some users think that Hyperliquid is already a complete platform. This is flattering, and the Hyperliquid community is indeed one-of-a-kind!

But as someone spending most waking moments pushing Hyperliquid to its full potential, I’m confident that there is a long way to go. In particular, the following are all complex, multi-phase undertakings:
1) deploying the native EVM
2) seamlessly integrating the EVM with existing native components (e.g., order books)
3) fully decentralizing the network 

On top of that, the following are continuously being improved:
1) high TPS and low latency L1 with HyperBFT consensus
2) performant financial primitives including fully onchain spot and perp order books, vaults, oracles, automated liquidity and account abstractions
3) state-of-the-art and community-owned order book liquidity via HLP

When you see a 100x, you drop everything to make that a reality. Factors of <2 are insignificant. Big things take time to build, but nothing else is worth building.

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More from @chameleon_jeff

Jun 30, 2023
1/ Cool to see people trying market making and documenting the progress in public!

Usually it's an opaque space and hard to learn from others. Most professionals want to protect their alpha at all costs.

Here's my advice on dealing with these practical issues 🧵
2/ First of all in HFT there are "strict" problems that you must get right and "loose" problems that you just want to 80/20 at the beginning.

More problems than you think will fall into the second bucket.

Problems will migrate to the first bucket, but slower than you think.
3/ When getting started, only model, strategy, and latency should be part of the first problem class.

Some important sounding things that I would recommend the 80/20 principle on:
1) inventory management
2) sizing
3) hedging

I.e. almost all of the issues @pedma7 mentioned
Read 8 tweets
Jun 24, 2023
1/ Order book perp DEXs are a hot "narrative" these days.

Most protocols run order books offchain. What does this mean for MEV?

Answer: it's far worse than sandwiching and frontrunning on AMMs.

A thread on why onchain order books are the only viable protection for end users 🧵
2/ I'm going to focus on problems, ideas, and approaches in this thread.

I'm not going to call out any specific projects.

But hopefully after reading this thread you more objectively assess what each project is building.
3/ First off, the mission statement.

Perps on CEXs have found the most product-market fit out of any business in crypto.

But many users want to move off CEXs.

So the problem is to build something truly decentralized but offering the same UX as CEXs.
Read 26 tweets
Jun 22, 2023
1/ Sharing some interesting insights from this slick new dashboard for @HyperliquidX
2/ After taker fees and maker rebates went live, non-HLP volume is pretty evenly split between maker and taker.

This is only possible because cancels and modifies are on Hyperliquid's custom performant L1. Image
3/ I suspect retail flow is overusing maker orders for the 0.2bp rebate, but it's cool to have the optionality

Read 5 tweets
May 15, 2023
1/ Many in crypto HFT rely heavily on historical simulation, while A/B testing is an afterthought.

In my experience there is real alpha in live testing well.

With proper experimental setup and sufficient market share, you can glean causal insights not available in tick data 🧵 Image
2/ First some background:

A/B testing is a useful tool in consumer tech.

Classic example: Google optimized their shade of blue for an additional $200M in yearly ad revenue.

When controlled experiments are cheap, A/B testing is a great way to juice marginal gains.
3/ Crypto HFT is an interesting domain for a few reasons though:

1) Your experiment has market impact at scale
2) You can simulate with historical data

So it's less clean to A/B test, and there is a viable alternative. So, is it still worth the trouble?
Read 15 tweets
Apr 30, 2023
1/ There's a lot of edge in building a production crypto HFT system the right way.

The abstractions should be rich enough to prevent careless mistakes but not too rigid to work with.

I converged on these after countless hours of building, debugging, and rewriting code 🧵
2/ Let's focus on a concrete example: How do you deal with continuous quantities?

Doing math in code with raw numeric types is error prone. Multiplying the price of one symbol by the size of another is sure way to blow up your strategy.

Just be careful? Nah, we can do better.
3/ A pervasive feature of our trading system is the concept of "units."

The first idea is to have separate types for Price, Size, Notional, etc.

Define relations:
Price * Size = Notional
Size + Size = Size
etc.

But Size * Size? Nonsensical, and now you get a compiler error.
Read 12 tweets
Apr 25, 2023
1/ Building a crypto HFT system is a challenging and rewarding journey.

A mega-thread covering:
Trading strategies ("what")
The infrastructure and latency optimization ("how")
Exchange selection ("where")
Market dynamics ("who")

What I wish I knew when getting started 🧵
2/ Starting out with the core of the trading system: the strategy itself.

First some general HFT strategy selection advice before specific alpha:
3/ A specific strategy on locked books with maker rebates.

This is a case study in the alpha research process, going from raw data to an idea to a strategy:
Read 16 tweets

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