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Introducing Index. Turn your trading idea into a live perps trading agent. → Index lets you create AI agents that trade perpetual futures. You can describe a trading idea in plain English, backtest it on historical data, improve it through an experimentation loop, and deploy an agent that follows...

64,482 просмотров • 3 месяцев назад •via X (Twitter)

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Ken Griffin, CEO of Citadel, said: "I'm fairly depressed watching AI do a week of PhD work in a few hours" He's worth $51.2 billion and 20% of every stock trade in America goes through his firm. The money isn't what's bothering him. Citadel pays $400,000 to $650,000 a year for that work. New trading AI agent does it now, on a free trial, for people who have never written a line of code. It went live this summer and most of your timeline still hasn't noticed. You type one sentence in plain English. AI agents loop takes it from there: > an AI agent turns your sentence into a real trading strategy > backtests it across 5 years of data in about 12 seconds > scores it 0 to 100 and shows you the exact spot where it leaks > kills the versions that only look good on paper > rebuilds what's left and runs the loop again > stress-tests the survivor on years it has never seen, then puts it live on your exchange in about 90 seconds That list is the entire job description of a junior quant. At a desk, one properly tested idea burns about $87,500 in salary time, and most of what they build is dead by week six. Two clicks and this AI agent is testing your own idea. Costs you nothing and it runs the whole thing by itself: Griffin gets to be depressed about it. He already owns the desk. You just got handed one. Bookmark & read full story of how they got an AI to build trading strategies and kill its own bad ones is in the article below.

cvxv666

222,320 просмотров • 20 дней назад

A finance professor manages $200M with AI agents, and he told everyone why: "Large language models are at the level of a fourth-year PhD student in every field" Alejandro Lopez-Lira's AI fund, Autopilot, returned 56% last year. The S&P did 16%. There are 52,000 people with money in it, and most of them just watch the machine work. What he automated is the same six-step loop every fund on earth runs: find an idea, code it, backtest it, deploy it, read the autopsy, learn from it. A quant at Two Sigma runs that loop once a month, and the salary time alone costs around $50,000 per hypothesis. All steps from this loop now fit in AI trading text box. Plain English in, executable strategy out, five-year backtest in 12 seconds, live on a broker 90 seconds after you typed the sentence. He runs $200M with AI. You can run same AI fund in two clicks, free to try: Step 6 on this loop is where everyone is stuck. Your agent has no memory. Every strategy it kills goes into a log nobody reads, and the next one starts from zero. Nobody keeps negative results. Not Citadel, not Man Group, not a single repo on GitHub. Fix that and the agent remembers every hypothesis it killed and the regime it died in. It stops burning cycles on your old mistakes. Jane Street pays 3,500 people to run this cycle and made $39.6 billion doing it. Five sixths of it is now free. Bookmark & read full map of this loop in the article below. Most people still think AI trading is out of reach for them - it isn't. Don't want to spend a dollar for testing this? Kalshi just opened a perps exchange and gives US users $25 free to start ->

cvxv666

82,211 просмотров • 16 дней назад

A one-man trading hedge fund now costs about $100 a month in AI subscriptions. Five PhDs on a Citadel desk cost $270,000 a month, and that is the cheap end. That buys one tested idea a month. Man Group's AI writes hundreds of new signals a week, on a floor where the humans used to manage twenty in a quarter. Fifty AI agents do the reading and the writing. One of them exists only to destroy what the others build, and that one is the reason any of it works. Every job on that payroll is now an agent you can run yourself: > AI research agents reading filings, transcripts, options flow and on-chain data overnight, fifty personas at once, none of them allowed to see what the crowd is pricing > coding agent that turns one sentence of plain English into entry rules, exit rules, sizing and risk limits, then debugs itself until it runs > backtest agent that replays five years of that idea in about 12 seconds > breaker agent, an AI whose only job is killing the thing, at double the trading costs and in the ten worst markets that asset has ever seen > critic agent that reads your journal and names the mistake you keep making Nobody on that list asks for a bonus in January. $200 million is already run this way on one platform where 52,000 people mostly sit and watch the machine work. The full map of what is built and what is missing is in the article below. Bookmark & read it If you're not yet using AI in your trading and investing.

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171,347 просмотров • 11 дней назад