Curtis Chen (Chutian)
Curtis Chen (Chutian) · Co-founder, Quanta Edge · Hong Kong
Strategies are about to become free, and so is the silicon that runs them. What a trading firm will still own is its judge, the protocol that decides what is real, and the right to act on it fast. I am building that firm.
What I am building
Quanta Edge is a trading firm where a handful of people write the exam and agents write everything else: the strategies, and the hardware that runs them. The judge is frozen and out of the agents’ reach. Unseen data and device builds are spent like a budget, and every live position carries a receipt back to the test that authorised it.
Three bets behind it:
- Strategies become inventory. The asset is the process that regenerates them, and the record of what each was tested against.
- Hardware follows. One strategy, one piece of silicon, searched by agents and judged on the device.
- What cannot be generated decides the winner. Unseen data, a build that closes timing, a venue to act on. They are spent, not made.
Proof
Futuristic Group, 2025–2026: the trading firm I founded and ran before this.
Sharpe 4.3
Agent alpha, live
Agent-mined signals on 50 crypto markets, run live through a partner fund. +10.3% net of costs in five months, max drawdown 1.5% (May to September 2026).
+500% in a month
Prediction markets, on-chain
A high-frequency book on Polymarket’s five-minute BTC markets: about 3,000 public trades in two months, and a top-30 leaderboard finish.
3 DEXs
Designated market maker
Market maker for tokenized Asian equities on three on-chain perp exchanges. First-month KPIs met; reactive cancellation adds about 0.9 bp per fill.
Open questions
- Can a check carry information when a candidate’s evidence is the same size as the noise the search itself produces?
- Where is the line between what the system may rewrite and what it must not, and how do you know, from inside, that it was crossed?
- How much of the judge can be learned? A build takes hours and an unseen window is spent once; surrogates are cheap, and the agent will learn to fool them.
Join us
HFT trader
AI researcher
Chief Scientist
If one of the questions above is already yours, especially if you think we have it wrong, write to me.
Earlier: AI research at Megvii, and reinforcement-learning trading at Graphen, New York. Columbia (M.S. Computer Science) · Peking University (Economics) · Tsinghua (Engineering Physics). Full CV