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cvxv666

@antpalkin17,422 subscribers

27 | research AI since 2021 | now looking for edge on quant trading with AI

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elon realizing his $300 Grok Bot just did the job a $294,000 wall street research desk does, and the guy who built it posted every prompt for free

elon realizing his $300 Grok Bot just did the job a $294,000 wall street research desk does, and the guy who built it posted every prompt for free

794,589 views

Chinese quant built a simulation of how SPX price reacts to any global event. He’s already made over $100k - with full blockchain proof. He knows exactly where price will go. More than 40 years of SPX trading history have been loaded into MiroFish simulator (18k stars on GitHub) AI analyzed every single moment in that trading history. Now this guy has a fully functional SPX price prediction system. His wallet: Dozens of successful SPX price-prediction trades and hundreds of tests across other stock markets. Here’s exactly what you need to replicate his stack: - market data APIs (SPX price, use Alpha Vantage or Quandl) - data pipeline (use Python) - feature engineering (for output signals like RSI, MACD) - seed dataset for MiroFish (convert data into structured context) - multi-agent simulation (macro strategist, earnings analyst, sentiment analyst agents etc.) - probability forecast (run different scenarios) - trading / decision Model (SPX futures ES, SPY ETF) Save this pipeline if you want to run a similar simulation on your own data. You can feed the whole thing to your Claude and build your first (even small) simulation model together.

Chinese quant built a simulation of how SPX price reacts to any global event. He’s already made over $100k - with full blockchain proof. He knows exactly where price will go. More than 40 years of SPX trading history have been loaded into MiroFish simulator (18k stars on GitHub) AI analyzed every single moment in that trading history. Now this guy has a fully functional SPX price prediction system. His wallet: Dozens of successful SPX price-prediction trades and hundreds of tests across other stock markets. Here’s exactly what you need to replicate his stack: - market data APIs (SPX price, use Alpha Vantage or Quandl) - data pipeline (use Python) - feature engineering (for output signals like RSI, MACD) - seed dataset for MiroFish (convert data into structured context) - multi-agent simulation (macro strategist, earnings analyst, sentiment analyst agents etc.) - probability forecast (run different scenarios) - trading / decision Model (SPX futures ES, SPY ETF) Save this pipeline if you want to run a similar simulation on your own data. You can feed the whole thing to your Claude and build your first (even small) simulation model together.

2,427,583 views

your life when instead of sending dumb "make me a trading bot for Polymarket" prompt you fed Claude this entire article with 28 links and a 6-layer pipeline.

your life when instead of sending dumb "make me a trading bot for Polymarket" prompt you fed Claude this entire article with 28 links and a 6-layer pipeline.

315,001 views

Claude and a free weather API will earn you $100k+. Success rate for beginners: 80%. Complete guide and algorithm for building Polymarket weather trading bot. Simple logic, a low entry budget and high ROI -that’s why weather bots are so clean. Onchain proof these bots exist: 1st bot: 2nd bot: I verified their profitability by myself copying every trade - each bot's win rate over time ranges from 80 to 90%. I grew my starting capital by +40% in just one week. You can copy their trades and see for yourself in two clicks through this bot: The alpha is simple: you're not trading weather. You're trading other people's ignorance. Gap between what the crowd prices and what 51 ensemble models say. Polymarket asks: "Will Atlanta hit 95°F tomorrow?" Normies bet on vibes. You bet on math. The core tool: Open-Meteo API. Free. No key needed. 51-model ensemble. Clean JSON. Cooked and ready. Update every 30 min. Hardcode your city coordinates - don't waste time on geocoding at runtime. This single endpoint beats most paid tools for what Polymarket actually needs. The edge in one sentence: Market is heavy on 16°C. Your 51-model ensemble points at 19°C. That's your trade. Find that gap systematically across every city market, every day - and you have a scanner. That's what separates consistent traders from gamblers. How to start: - Week 1: Open-Meteo + tropicaltidbits. Pick one city market. Track model vs market price daily. Don't trade yet — just watch where you'd have been right. - Weeks 2–3: Automate the pull. Log ensemble divergences. Build the scanner. - Week 4: Now you have an edge. Trade it. Most people want to skip to week 4. That's exactly why most people lose. Now you have the algorithm framework plus a complete guide to get started. All that's left is to actually do it. Bookmark this post so you can come back to it when you start building the bot.

Claude and a free weather API will earn you $100k+. Success rate for beginners: 80%. Complete guide and algorithm for building Polymarket weather trading bot. Simple logic, a low entry budget and high ROI -that’s why weather bots are so clean. Onchain proof these bots exist: 1st bot: 2nd bot: I verified their profitability by myself copying every trade - each bot's win rate over time ranges from 80 to 90%. I grew my starting capital by +40% in just one week. You can copy their trades and see for yourself in two clicks through this bot: The alpha is simple: you're not trading weather. You're trading other people's ignorance. Gap between what the crowd prices and what 51 ensemble models say. Polymarket asks: "Will Atlanta hit 95°F tomorrow?" Normies bet on vibes. You bet on math. The core tool: Open-Meteo API. Free. No key needed. 51-model ensemble. Clean JSON. Cooked and ready. Update every 30 min. Hardcode your city coordinates - don't waste time on geocoding at runtime. This single endpoint beats most paid tools for what Polymarket actually needs. The edge in one sentence: Market is heavy on 16°C. Your 51-model ensemble points at 19°C. That's your trade. Find that gap systematically across every city market, every day - and you have a scanner. That's what separates consistent traders from gamblers. How to start: - Week 1: Open-Meteo + tropicaltidbits. Pick one city market. Track model vs market price daily. Don't trade yet — just watch where you'd have been right. - Weeks 2–3: Automate the pull. Log ensemble divergences. Build the scanner. - Week 4: Now you have an edge. Trade it. Most people want to skip to week 4. That's exactly why most people lose. Now you have the algorithm framework plus a complete guide to get started. All that's left is to actually do it. Bookmark this post so you can come back to it when you start building the bot.

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Grok Bot by Elon Musk just replaced a $294,000 Wall Street research desk. Six AI agents, $200 a month, doing the work BlackRock pays people six figures for. The guy who built it published every prompt. What that desk cost before the bots: > $27,000 a year for the Bloomberg terminal > $22,000 for Refinitiv > $50,000 for sell-side research > $15,000 for AlphaSense > $180,000 for the junior analyst who reads all of it until 2am so somebody senior can trade on it before the open $294,000 a year. The agents cost $2,400. Same brief, 122 times cheaper, and it is there before the open. Six agents split that desk. Each one gets its own computer in the cloud, and they all write into the same vault. > FILINGS reads every 10-K, 10-Q and 8-K on a 100-ticker watchlist overnight and flags the ugly parts: going concern language, auditor changes, restatements > EARNINGS reads the call transcript within 24 hours and tells you if the CFO got quieter than he was last quarter > SECTOR does one pass per sector and picks up the rule change nobody read > INSIDER catches Form 4 buys over $1 million and new positions from Two Sigma, Third Point and D.E. Shaw the day the 13Fs land > CHATTER counts mentions on X and flags any ticker three standard deviations louder than its own 30-day normal > CHIEF OF STAFF reads the other five at 5:30am, bins anything only one of them flagged, and emails you the ranked brief at 6 One analyst covers 30 names. Six agents cover 3,000 and finish before the open. You show them the job once. They repeat it every night with your laptop shut. Every research floor on Wall Street was priced on reading being slow and people being expensive. Both of those stopped being true this month. So you wake up, read for five minutes, and know what moved on every name you hold. That used to be somebody's entire job, and he got a bonus for it. The article below is the step by step guide to building the whole AI trading machine. Save & read it, you will want it open while you build.

cvxv666

809,002 views • 15 days ago

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Grok Bot by Elon Musk is about to become the first AI agent trading on chain in public. One wallet, $1,000 in it, and an address anyone can open. It built me a memecoin research desk and then automated itself out of my hands. 7 agents, no people, running while i sleep and rewriting their own rules by morning. > SCOUT sits on pumpfun and catches every deploy the second it lands > HYPE reads mention velocity straight off X, the feed nobody outside xAI gets > CHATTER lives in the pump and fomo comment rooms and scores every caller, who moves price and who shows up after the move > FORENSICS traces the funding chains, so five buyers that are really one guy get labeled as one guy > SAFETY runs the CA check before the desk is allowed to want anything, mint authority, freeze authority, LP lock, sell tax > TRADER writes the exit before it takes the entry, every single time Chief of Staff never trades. It reads the five briefs, scores the call and sizes it. SAFETY can kill any of them at any score, and a kill does not get appealed. Every night it reads its own losing trades and rewrites the scoring rules by morning. I see the diff. I do not write it. No screenshots, no PnL flex out of a private account. One address, every fill, every mistake, in public. It will lose money on some of these, and it will be on chain inside the same minute. I am not going to soften it later. A desk like this used to mean huge salaries, an office and somebody watching the screens at 3am. Mine is a subscription and a wallet. The address goes live by 22:00 UTC. Thank you to the xAI team for the belief and the unlimited Grok Bot tier. You handed me the whole thing and never once asked what I was going to do with it. Thank you to everyone here. This is happening because you kept telling me to stop planning it. I think we are about to run the boldest experiment modern finance has ever been allowed to watch live. God bless us.

cvxv666

95,530 views • 11 days ago

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BlackRock runs on 20,000 people. Elon's Grok Bot runs the same shape for $300 a month, and it hires its own staff. You do not get an assistant. You get a company that hires. It does not throw ten agents at your problem and hand you the pile. It makes one agent that makes 10, and those ten make a 100. > LAYER ONE is one agent, the chief of staff, and it never touches the market > LAYER TWO is six desk heads, one job each, every one on its own computer with its own logins > LAYER THREE is whatever those six decide they need, spun up on the spot and shut down when the work is done Nobody writes a task list. You hand out job titles and the org fills itself in underneath. The swarm is never the same twice. Agents get spun up for one job, finish it, and are gone before I ever read their names. Not one of them sees the whole picture. The answer only exists after they hand off to each other. Wall Street cannot copy that. You cannot hire a hundred people for eleven minutes. BlackRock holds that shape together with a risk system called Aladdin. Mine holds it together with one agent that is only allowed to say no. I gave it $1,000 and told it to grow the money or get deleted. 15 hours later it was holding $3,900, on an address anyone can open and read. I was asleep for most of it, and I have still not written a line of code. The whole thing runs with my laptop shut, because none of it lives on my laptop. Setup is one evening. Create the chief, hand out the titles, run one trade on your screen while they watch, connect Telegram. Ten years ago a machine this shape had its name on a tower. Mine has a name I typed into a box. Save this while the whole thing still fits on one screen.

cvxv666

45,488 views • 6 days ago

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A 35-year-old accountant from New Orleans left his job and spent a full month in isolation with Claude. The result? He made $45,000 in a single day. 300 hours of meticulous work - and the perfect BTC trading algorithm was ready. If he keeps cooking like this, he’s hitting over $1,000,000 in a single month. His wallet: He selected username nsh91qaz - an ironic nod to his 1991 birth year, an age when most people believe it’s too late to change their lives. But he changed anyway. I ran a backtest of his strategy using Claude + Nautilus via PyPI. Results genuinely shocked me - mechanics are understandable to pretty much anyone. The real alpha is in the numbers under the hood. That’s what lets you pull $45k per day with pure math. I simulated every single one of his trades and broke down every transaction: 75 markets, 72 fills, 85.1% win rate, Sharpe ratio 4.21. All run on the Nautilus-core broker simulator with 41.8 GB of parquet data in DuckDB. Every trade is a perfect cycle. Every dollar earned is pure exploitation of market inefficiency. He doesn’t predict the future - the math already knows it. He just reads the numbers right and takes the money Brier-loss ensemble: 400 trees · lr 0.03, walk-forward validation with Sharpe 4.21 ± 0.08. Save this post if you actually want to learn how to build something like this. Or just skip the homework and start copying his trades right now - that’s the easiest and most profitable route I’m on:

cvxv666

341,229 views • 4 months ago

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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

82,592 views • 29 days ago