Trading and Investments. Ex Getco, Heavy-Autumn-Wolf (#1 trader on Bitmex). angel @usdai_official, @monad, @zellic_io, @ethena, @crusoeai. NFA
Joined June 2011
- Tweets1.7K
- Following424
- Followers3K
- Likes8.5K
Tang retweeted
Ex-Tower Research HFT trader Annanay Kapila (@annanay) on why hedge funds trade mid-frequency instead of HFT:
"Proprietary trading firms who don't have a lot of capital need to achieve a very high return on capital. They tend to do high-frequency trading because they never end up in big positions."
"By contrast, hedge funds tend to end up more in mid-frequency trading, because they're not interested in small gains or losses that you can realize on each trade from high-frequency trading."
"If I have the ability to put a lot of capital behind my trades and take large positions, then I have the privilege of being able to predict much longer in the horizon."
"In that region, where we're trying to predict hours, days, maybe even weeks out into the future, I need to take on bigger positions overall to make it worth my while. I need more capital, and I'll probably achieve lower return on investment."
"I'll be able to make more dollars, even if I don't make as much percentage return."
"Greed makes markets."
Annanay Kapila (@annanay) spent years as an HFT quant at Flow Traders and Tower Research before founding QFEX (@QFEX), a perpetual futures exchange for equities, commodities & FX. Cambridge Maths.
At his last job, the desk traded $10B+ of volume a day, run almost entirely by algorithms.
In this lecture, he builds market making from first principles:
- The map of systematic trading: prop money vs. other people's money, HFT vs. mid-frequency, and why every strategy lives in one quadrant
- Why prop firms can return 50-100% a year while hedge funds can't: HFT never leaves you holding a big position
- The order book from scratch: bids, offers, limit orders, and why the first order on a price level gets the trade
- No free lunch: how arbitrageurs force every order book to reveal a fair price without anyone trying to
- The entire strategy in one line: bid below fair value, offer above it, collect the difference forever
- Market making is "time-spreading risk," warehousing positions between a seller who shows up now and a buyer who shows up later
- Adverse selection: you're most likely to get filled precisely when your price is most wrong
- Why market makers are completely self-serving, and why that's exactly what makes markets work
- The competitive race that compresses spreads: greed among market makers means lower costs for everyone else
- Thick books vs. thin books, and the vicious loop that keeps illiquid markets illiquid
Highlights:
(00:45) The systematic trading map: capital vs speed
(01:45) Prop firms vs hedge funds: return-on-capital economics
(06:29) A message from Onyx
(07:55) Where market making sits: high-Sharpe prop HFT
(08:55) Fungibility and why exchanges exist
(11:00) How a central limit order book actually works
(17:40) No free lunch: arbitrage-free pricing in the book
(19:55) Theo: reading fair value from the mid
(22:45) Who really posts the book (not retail)
(24:35) Market making as warehousing risk across time
(27:20) Edge: quoting around your fair value
(29:45) Queue priority and the adverse selection problem
(33:05) How competition compresses the bid-offer spread
(37:40) Thick vs thin books: liquidity begets liquidity
(43:55) Scaling to $10B a day on algorithms
Tang retweeted
Tokenized real-world assets total about $65B, 0.12% of the S&P 500's value and 0.20% of US Treasuries outstanding, per the IMF's new Global Financial Stability Report.
Most of it is credit (30.4B)and money market funds(17.5B). Tokenized repo is the one use with real volume, about $303B a day, still small next to the roughly $13T a day in US repo.
The IMF puts it down to four constraints: legal certainty, regulatory clarity, interoperability and safe money to settle in. On its current path, tokenization stays confined to specific uses, with limited risk but limited gains.
Tang retweeted
介绍比Jev快50倍，在你设备上跑的laya-mlx!
只在你的设备上占用最高1G内存
Laya是一个开源的类似于Jev的,基于文本输出概率的分类系统
我将其移植到MLX,并且做了一些性能优化!
视频中就是这个模型在我的本地M3Max上玩贪吃蛇
这个模型能够以每秒决策60次的速度玩贪吃蛇！
github.com/mizorewww/laya-ml…
Startups and Monopolies
tangtrades.medium.com/a-head…
- Being first buys time. Use it to build something competitors can’t cheaply reproduce.
- Scale matters when it lowers costs. Networks matter when they improve the product.
- Someone may copy your product. Can they copy your economics?
Tang retweeted
IMO the bigger opportunity for tokenized equities is in the long tail.
Through Oct 24, $VIDA and $PTN generated 7.8x and 2.1x their underlying stocks’ estimated US turnover over matching periods since first observed on @solana.
Harder to access stocks (e.g. small cap-stocks on exchanges outside the US) could reach new investors through apps built around discovery, community and simple trading, all drawing on shared liquidity.
If that activity develops into deeper, informed markets, Solana could become a place where prices are set, not just followed.
Tang retweeted
Last month, we demonstrated high-rate alchemy: turning mercury into real, stable gold, beating CERN’s record by a factor of 10.
Last week, we enriched isotopes in the world’s most powerful plasma centrifuge, beating the Soviet record that stood for 40 years.
Now, we’re building a fusion reactor in San Francisco to achieve record power density.
Tang retweeted
crypto tokens paired with crypto-native usage -> DeFi TVL, lending / borrowing, launchpads, DEX volumes -> all undergo booms and busts, no structural growth over time
crypto tokens paired with extraneous demand -> secular growth, higher valuation ceilings, growing floors
like i said, you can't rely on crypto liquidity expanding anymore. like a emerging market, it'll have short booms, with busts.
you have to look towards the outside. card spending ramping. gpu loans going up. inference demand. all of these are fresh blue oceans.
there are coins tied to crypto liquidity (bad), and then there are coins tied to external liquidity (good).
Tang retweeted
So many people have DM’d me about this trailer and I’ll be honest, watching it made me physically throw up.
I was COO from before FTX even had a name, it was my baby, and I was the last one out of the Bahamas after Sam got extradited. I lost everything I had on it and it took me a long time to get over, so I have zero interest in defending the people who caused this.
The media loves the story that FTX blew up because we were all partying in the Bahamas, but the place I worked looked nothing like that.
We had under 200 people in the core company at its peak, not counting subsidiaries, when other exchanges our size had thousands, so a lot of us were doing 16 to 18 hour days for over three years and barely had time to sleep, and whenever we walked in, day or night, Sam was at his desk.
I worked with Caroline and never once saw her get aggressive like she does in this trailer. She’s quiet and mild, and often lost in her own thoughts.
Most of us didn’t even know she and Sam were dating until we read about it after the bankruptcy, and I never saw him so much as put an arm around anyone.
FTX’s collapse ruined so many people’s lives, including ours, and Netflix decided to make it a love story.
Shame on you @netflix.
Tang retweeted
Introducing GLX, USDAI’s GPU Loan Exchange.
Launching with a $98.1M season-and-sell transaction for Duos Edge AI's facility.
GLX unlocks and entirely new method of capital recycling to the sUSDai vault to scale originations into the billions.
The borrower behind USDAI’s latest $98.1M loan:
@duosEdgeAI, a subsidiary of Nasdaq-listed @duostech.
@get_hydrahost will manage GPU-as-a-Service distribution and operations.
Pricing the interest rate of intelligence, one loan at a time.
Tang retweeted
It paid out 1000 to one for a bet where if you and I each picked an atom at random on the earth, we'd be about 100 sextillion times more likely to pick the same one than that parlay was to hit.
Tang retweeted
Borrow with sUSDai, now available on @jupiter_earn.
New Loop Alert:
sUSDai, the $600M+ yield-bearing dollar from @USDai_Official, makes its Solana debut with 3 new vaults.
Borrow against your sUSDai while you keep earning its GPU-backed yield
Or currently multiply it up to 35% APY.
Tang retweeted
Thanks for having me @andrewrsorkin!!
Data center developer Crusoe is raising $3.9 billion, bringing its valuation to ~$31 billion dollars. @ChaseLochmiller outlines the details: cnb.cx/4cQzN2a