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cvxv666

@antpalkin • 8,261 subscribers

e-beggar since 2021 | now looking for edge on @Polymarket

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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.

2,380,062 görüntüleme

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.

314,074 görüntüleme

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Jane Street made $39.6 billion last year with just 3,500 people. That's $11.3M per employee - 7x Goldman. They didn't do it with more humans. They spent $6 billion on AI and 4,032 GPUs in a Texas data center to make each quant 10x faster. There's now a tool that lets anyone test same tradings strategys in 90 seconds - no coding, no finance degree, just plain English -> Here's what's happening inside the top firms: Man Group ($150B) built an AI on Claude that writes and tests strategies on its own - hundreds a week. A human team tests 20 in a quarter. Bridgewater runs a $2B AI fund making "alpha uncorrelated to what our humans do" The edge was never the idea. It was speed. They test 100 strategies for every 1 you test by hand. Horizon hands that exact speed to regular people. Plain English in. Tested system out. Save this. Re-read it when the waitlist is closed.

Jane Street made $39.6 billion last year with just 3,500 people. That's $11.3M per employee - 7x Goldman. They didn't do it with more humans. They spent $6 billion on AI and 4,032 GPUs in a Texas data center to make each quant 10x faster. There's now a tool that lets anyone test same tradings strategys in 90 seconds - no coding, no finance degree, just plain English -> Here's what's happening inside the top firms: Man Group ($150B) built an AI on Claude that writes and tests strategies on its own - hundreds a week. A human team tests 20 in a quarter. Bridgewater runs a $2B AI fund making "alpha uncorrelated to what our humans do" The edge was never the idea. It was speed. They test 100 strategies for every 1 you test by hand. Horizon hands that exact speed to regular people. Plain English in. Tested system out. Save this. Re-read it when the waitlist is closed.

334,464 görüntüleme • 10 gün önce

Quant at Jane Street kills 97 out of every 100 strategies it builds. That body count is the edge. Not the 3 survivors. The 97 corpses. The faster you falsify garbage, the faster you reach the one idea that isn't. Retail runs this backwards - finds one setup, gets emotionally married to it, and rides it down 40% over six months defending it like a religion. Run the kill-loop yourself with Horizon -> Type an idea in plain English. Horizon parses it into entry/exit logic, position sizing, risk rules. Backtests 5 years of tick data in ~12 seconds. Runs Monte Carlo across thousands of simulated paths. Deflates Sharpe ratio for the number of trials so luck can't sneak through. Spits out a cold verdict: dead or alive. Kill it. Type the next. 50 ideas before dinner. That loop cost $25K/year and a quant desk. Now it's a sentence and 12 seconds. The edge was never having ideas. It was murdering them at scale. Save this. Test 50. Keep 2. Kill the rest without mercy

Quant at Jane Street kills 97 out of every 100 strategies it builds. That body count is the edge. Not the 3 survivors. The 97 corpses. The faster you falsify garbage, the faster you reach the one idea that isn't. Retail runs this backwards - finds one setup, gets emotionally married to it, and rides it down 40% over six months defending it like a religion. Run the kill-loop yourself with Horizon -> Type an idea in plain English. Horizon parses it into entry/exit logic, position sizing, risk rules. Backtests 5 years of tick data in ~12 seconds. Runs Monte Carlo across thousands of simulated paths. Deflates Sharpe ratio for the number of trials so luck can't sneak through. Spits out a cold verdict: dead or alive. Kill it. Type the next. 50 ideas before dinner. That loop cost $25K/year and a quant desk. Now it's a sentence and 12 seconds. The edge was never having ideas. It was murdering them at scale. Save this. Test 50. Keep 2. Kill the rest without mercy

80,014 görüntüleme • 4 gün önce

A blackjack dealer in Macau got blacklisted from the VIP rooms last spring for counting cards. By August he couldn't get a floor job at any property in Cotai. So he deposit $500, ran a Hermes trading agent on Polymarket and pulled in $881,319 over the next 14 months. His wallet: The casinos taught him one thing - count, size your bet to your edge, walk away when the edge is gone. So he makes 5 trades a day. Not 50. Not 500. Five. And waits for the rest. Here's the actual stack. Claude Opus 4.7 reads the order book nightly, scores every threshold market by Markov persistence x Kelly edge, and surfaces the 2-3 mispriced ones. Hermes Agent by NousResearch executes. A $10/mo Hetzner VPS runs it 24/7. Telegram pings on every fill. Total cost: $10/month. Setup: 30 minutes. No coding. One trade in April: Will Bitcoin reach $90,000? Market said 1.2¢. He put $3,088 on Yes. It hit. +$123,196. A 3,988% return on a single position. The real edge is the nightly self-learning loop. Every midnight, Opus reads the day's trade journal and rewrites MIN_PROB and MIN_EDGE in the .env file. Last week the threshold was 0.87. This week 0.89. Next week maybe 0.91. His version of the bot has rewritten itself 412 times in 14 months. The Macau syndicate couldn't ban him from Polymarket. The bot doesn't sit at a table. It doesn't show a passport. It just hunts the tails. Save this post - if you want to build something of your own based on Hermes. Or just start copying algorithm that has improved itself 412 times:

A blackjack dealer in Macau got blacklisted from the VIP rooms last spring for counting cards. By August he couldn't get a floor job at any property in Cotai. So he deposit $500, ran a Hermes trading agent on Polymarket and pulled in $881,319 over the next 14 months. His wallet: The casinos taught him one thing - count, size your bet to your edge, walk away when the edge is gone. So he makes 5 trades a day. Not 50. Not 500. Five. And waits for the rest. Here's the actual stack. Claude Opus 4.7 reads the order book nightly, scores every threshold market by Markov persistence x Kelly edge, and surfaces the 2-3 mispriced ones. Hermes Agent by NousResearch executes. A $10/mo Hetzner VPS runs it 24/7. Telegram pings on every fill. Total cost: $10/month. Setup: 30 minutes. No coding. One trade in April: Will Bitcoin reach $90,000? Market said 1.2¢. He put $3,088 on Yes. It hit. +$123,196. A 3,988% return on a single position. The real edge is the nightly self-learning loop. Every midnight, Opus reads the day's trade journal and rewrites MIN_PROB and MIN_EDGE in the .env file. Last week the threshold was 0.87. This week 0.89. Next week maybe 0.91. His version of the bot has rewritten itself 412 times in 14 months. The Macau syndicate couldn't ban him from Polymarket. The bot doesn't sit at a table. It doesn't show a passport. It just hunts the tails. Save this post - if you want to build something of your own based on Hermes. Or just start copying algorithm that has improved itself 412 times:

207,158 görüntüleme • 15 gün önce

Chinese student received a $4M investment the very next day after building his MiroFish simulation system. Now you can simulate anything. Build a virtual world, tweak the parameters, and watch how things plays out in every possible scenario. Catch every weakness and surprise twist before it even happens. Infinite runs. Infinite data. SPX reaction to news? Bro already simulated it and printed $200k, see quoted post. Trump does something dumb -> load the data, run the sim, see exactly how voters lose their minds. You can literally simulate the entire universe with this thing. The process is simple: simulate -> analyze -> improve -> repeat. Full guide + pipeline in quoted post, if you want to run a similar simulation on your own data.

Chinese student received a $4M investment the very next day after building his MiroFish simulation system. Now you can simulate anything. Build a virtual world, tweak the parameters, and watch how things plays out in every possible scenario. Catch every weakness and surprise twist before it even happens. Infinite runs. Infinite data. SPX reaction to news? Bro already simulated it and printed $200k, see quoted post. Trump does something dumb -> load the data, run the sim, see exactly how voters lose their minds. You can literally simulate the entire universe with this thing. The process is simple: simulate -> analyze -> improve -> repeat. Full guide + pipeline in quoted post, if you want to run a similar simulation on your own data.

1,143,844 görüntüleme • 2 ay önce

A 29-year-old sales consultant from Oklahoma quit his job thanks to AI - now he makes his director’s entire annual salary in just two weeks. $306,000 in profit over the past month. He replaced an entire team of quants with Claude and a swarm of agents - and built his own ETH price simulation engine. His wallet: Each of the 6 agents validates its own trading decision, and thanks to their precision, he’s pulling in at least $15,000 a day. The agent system coverage speed is far higher than any top-tier trading team. They collect data 24/7 and run simulations using that data in the MiroFish engine - completely autonomously. They remember every pattern, every market reaction, every trading signal. This is a new milestone in algo trading. 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. Save this post if you actually want to learn how to build something like this. Or just skip homework and start copying every one of his trades right now - that’s the easiest and most profitable route I’m on:

A 29-year-old sales consultant from Oklahoma quit his job thanks to AI - now he makes his director’s entire annual salary in just two weeks. $306,000 in profit over the past month. He replaced an entire team of quants with Claude and a swarm of agents - and built his own ETH price simulation engine. His wallet: Each of the 6 agents validates its own trading decision, and thanks to their precision, he’s pulling in at least $15,000 a day. The agent system coverage speed is far higher than any top-tier trading team. They collect data 24/7 and run simulations using that data in the MiroFish engine - completely autonomously. They remember every pattern, every market reaction, every trading signal. This is a new milestone in algo trading. 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. Save this post if you actually want to learn how to build something like this. Or just skip homework and start copying every one of his trades right now - that’s the easiest and most profitable route I’m on:

335,941 görüntüleme • 1 ay önce

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:

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:

338,726 görüntüleme • 1 ay önce

A 67-year-old grandfather in Vermont built a trading bot during retirement - it earned him $290,000 in a single year without losing a single trade. 168 trades. 100% win rate. Zero drawdown across 365 days. The strategy is so safe it's basically a bond ladder - but with AI doing the probability math instead of credit ratings. His wallet: Here's how it actually works: He only takes bets the model is >85% sure of. Everything else? Killed. 188 events scanned per day. ~12 pass the filter. ~1 actually deploy. AI algo waits. Most days he doesn't trade at all. The probability model is stolen from weather forecasting: 31 models vote on every outcome. 28 out of 31 saying "yes" = 90% conviction. Below 26 = automatic reject. That's the entire edge. Polymarket is full of 87-92¢ markets that almost always settle at $1. Most traders ignore them - upside per dollar looks tiny. The math: edge = model_p − market_p kelly = edge / (1 − token_price) size = bankroll x kelly x 0.15 The stack runs free: Polymarket Gamma API for discovery, ClickHouse + Redpanda for the pipeline, paper mode validation before live capital. Brier score 0.041 across all 168 predictions. Anything under 0.10 is institutional-grade. He's printing the academic numbers. Most boring account on Polymarket. Also the most profitable - so save this post. And if you’ve been looking for the most safest strategy to copy - you’ve definitely found it. Get started:

A 67-year-old grandfather in Vermont built a trading bot during retirement - it earned him $290,000 in a single year without losing a single trade. 168 trades. 100% win rate. Zero drawdown across 365 days. The strategy is so safe it's basically a bond ladder - but with AI doing the probability math instead of credit ratings. His wallet: Here's how it actually works: He only takes bets the model is >85% sure of. Everything else? Killed. 188 events scanned per day. ~12 pass the filter. ~1 actually deploy. AI algo waits. Most days he doesn't trade at all. The probability model is stolen from weather forecasting: 31 models vote on every outcome. 28 out of 31 saying "yes" = 90% conviction. Below 26 = automatic reject. That's the entire edge. Polymarket is full of 87-92¢ markets that almost always settle at $1. Most traders ignore them - upside per dollar looks tiny. The math: edge = model_p − market_p kelly = edge / (1 − token_price) size = bankroll x kelly x 0.15 The stack runs free: Polymarket Gamma API for discovery, ClickHouse + Redpanda for the pipeline, paper mode validation before live capital. Brier score 0.041 across all 168 predictions. Anything under 0.10 is institutional-grade. He's printing the academic numbers. Most boring account on Polymarket. Also the most profitable - so save this post. And if you’ve been looking for the most safest strategy to copy - you’ve definitely found it. Get started:

112,738 görüntüleme • 17 gün önce

Trump's crypto advisor aka "Czar" David Sacks is insider trading on Polymarket. He knows in advance when Trump will say something related to crypto. $187k profit. 90% win rate in the mentions category. He makes $30-50k from each of Trump's public appearances. His profile: Peak boomer hobby - fun and profitable. Longest win streak: 51 in a row. Bookmark his wallet: if this guy bets that Trump will say something, then Trump will definitely say it. Pro tip: skip his NBA trades - dude yolo's on his favorit team (they are losers)

680,261 görüntüleme • 3 ay önce

This Chinese engineer wins almost 90% of his trades. He extracted $60,000 profit in only TWO DAYS. He doesn’t even look at charts or guess the future - Claude + his 6-layer agent system does all the work. Edge is literally baked into the numbers and math, so this dude prints money with almost zero risk. His wallet: Right now in prediction markets you can make $5M a year with just AI and the will to build. Big institutions and billion-dollar capital haven’t entered yet - reputational risks are too high and space is still too young. That’s why an ordinary student can take professional-level experience and apply it on Polymarket. Out of 1,000 trades, he won 900. Pure inefficiency that he exploits. Save this post so you can read the article and understand how everything works. Or just start right now - copy every trade of this Chinese genius in two clicks:

This Chinese engineer wins almost 90% of his trades. He extracted $60,000 profit in only TWO DAYS. He doesn’t even look at charts or guess the future - Claude + his 6-layer agent system does all the work. Edge is literally baked into the numbers and math, so this dude prints money with almost zero risk. His wallet: Right now in prediction markets you can make $5M a year with just AI and the will to build. Big institutions and billion-dollar capital haven’t entered yet - reputational risks are too high and space is still too young. That’s why an ordinary student can take professional-level experience and apply it on Polymarket. Out of 1,000 trades, he won 900. Pure inefficiency that he exploits. Save this post so you can read the article and understand how everything works. Or just start right now - copy every trade of this Chinese genius in two clicks:

217,341 görüntüleme • 1 ay önce

You could literally: > Open a Polymarket account > Deposit $20 > Copy one Chinese quant's wallet > Let his BTC simulation pick trade > Sleep through the 7,500% profit bet > Wake up with $166,000 Why aren't people doing this?!

You could literally: > Open a Polymarket account > Deposit $20 > Copy one Chinese quant's wallet > Let his BTC simulation pick trade > Sleep through the 7,500% profit bet > Wake up with $166,000 Why aren't people doing this?!

236,579 görüntüleme • 1 ay önce

Jane Street pays quants $500K+ to build what Nous Research just open-sourced for free. Hermes Agent - open-source, self-hosted, deploys in 30 minutes on a $5/month VPS. Kelly Criterion sizing, Expected Value scoring, 3 forecast sources across 20 cities, self-calibrating, TG alerts. All out of the box. No code required. Algorithms like these generate $100,000–$150,000 per quarter Wallet proof: This trader turned $300 into $123K trading weather. Every trade verifiable on-chain, every PnL public. The "retail can't compete with institutions" narrative is dead. You just need a terminal for copy every trade of such agents, i'm use this one:

Jane Street pays quants $500K+ to build what Nous Research just open-sourced for free. Hermes Agent - open-source, self-hosted, deploys in 30 minutes on a $5/month VPS. Kelly Criterion sizing, Expected Value scoring, 3 forecast sources across 20 cities, self-calibrating, TG alerts. All out of the box. No code required. Algorithms like these generate $100,000–$150,000 per quarter Wallet proof: This trader turned $300 into $123K trading weather. Every trade verifiable on-chain, every PnL public. The "retail can't compete with institutions" narrative is dead. You just need a terminal for copy every trade of such agents, i'm use this one:

275,084 görüntüleme • 1 ay önce

A 23-year-old realtor from Nebraska lost his job and started studying Claude. The result? He made $22,000 in a single day. His Polymarket algorithm generated $249,000 in profit over the past month. Wallet proof: Dude spent around 250 hours teaching his Claude to collect data and run simulations through MiroFish. Now the bot runs on full autopilot - the perfect machine for extracting mathematical inefficiencies in BTC markets. He doesn’t need to predict the future - he simply calculates the perfect moment to buy both the UP and DOWN sides for a total of less than $1. The crowd reacts to price direction quickly - but he’s even faster. Thanks to data from private order books like Kraken and closed OTC BTC desks, he’s always one step ahead. This isn’t "guessing where the chart will go" This is engineered money. Pure fusion of AI + MiroFish + insane math on exclusive data. Want to build your own algo? Save this post and read the article. Alternatively, if you prefer not to miss his next profitable trades, you can start copying every single one of them right now with this TG bot:

A 23-year-old realtor from Nebraska lost his job and started studying Claude. The result? He made $22,000 in a single day. His Polymarket algorithm generated $249,000 in profit over the past month. Wallet proof: Dude spent around 250 hours teaching his Claude to collect data and run simulations through MiroFish. Now the bot runs on full autopilot - the perfect machine for extracting mathematical inefficiencies in BTC markets. He doesn’t need to predict the future - he simply calculates the perfect moment to buy both the UP and DOWN sides for a total of less than $1. The crowd reacts to price direction quickly - but he’s even faster. Thanks to data from private order books like Kraken and closed OTC BTC desks, he’s always one step ahead. This isn’t "guessing where the chart will go" This is engineered money. Pure fusion of AI + MiroFish + insane math on exclusive data. Want to build your own algo? Save this post and read the article. Alternatively, if you prefer not to miss his next profitable trades, you can start copying every single one of them right now with this TG bot:

164,720 görüntüleme • 1 ay önce

Chinese quant built a perfect BTC price simulation engine with MiroFish In a single trade, he turned $2,000 into $166,000. 7,500% profit. All proof onchain - every single one of his trades is publicly visible on Polymarket. His wallet: His algorithm instantly detects any mispricing in crypto markets and enters trade immediately. $350k all-time profit. Constantly fading the crowd because his simulation reads the market better than everyone else. He’s using closed order book data + private OTC desks. Already elite alpha. Then the real magic happens: 10,000 simulation cycles of how the market will react. On April 24, he was only one who knew the market was wrong. He entered a trade with just a 1.3% implied probability of execution. This isn’t "guessing where the chart will go" This is engineered money. Pure fusion of AI + MiroFish + insane math on exclusive data. Want to learn how to build something like this? Save the post and read the article. If you don’t want to miss his next 75x trade, starting copy every one of his trades right now using this TG bot:

Chinese quant built a perfect BTC price simulation engine with MiroFish In a single trade, he turned $2,000 into $166,000. 7,500% profit. All proof onchain - every single one of his trades is publicly visible on Polymarket. His wallet: His algorithm instantly detects any mispricing in crypto markets and enters trade immediately. $350k all-time profit. Constantly fading the crowd because his simulation reads the market better than everyone else. He’s using closed order book data + private OTC desks. Already elite alpha. Then the real magic happens: 10,000 simulation cycles of how the market will react. On April 24, he was only one who knew the market was wrong. He entered a trade with just a 1.3% implied probability of execution. This isn’t "guessing where the chart will go" This is engineered money. Pure fusion of AI + MiroFish + insane math on exclusive data. Want to learn how to build something like this? Save the post and read the article. If you don’t want to miss his next 75x trade, starting copy every one of his trades right now using this TG bot:

201,191 görüntüleme • 1 ay önce

This Chinese quant made $500,000 trading oil on Polymarket - and now trying to hide. Previously his profile was called bin8888. Now he’s switched to hidden mode and is just "Anon" But I saved his profile: His Claude + MiroFish trading engine is so good that he doesn’t want anyone watching him. Claude gathers the data for the simulation. OSINT parser scrapes every Iran/Hormuz headline. MiroFish simulates how every single piece of data affects the oil price. Result: an algo that’s been perfectly calling oil moves for two straight months. This guy knows in advance what others only see after the chart moves. And unlike top futures traders, every one of his trades is visible on-chain. His knowledge and algorithm are completely open for us to use. I’m copying every new oil trade he makes with this bot (US users can actually trade here, unlike the main Polymarket site):

184,051 görüntüleme • 1 ay önce

Chinese engineer made $600,000 in ONE MONTH trading BTC markets on Polymarket. Right tools + 6-layer execution stack, zero risk and pure math edge farming. He wins with an 85% probability - earn roughly $150,000 per week. Every week. His wallet: ~$7,000,000 a year. Not a bad return for simply finding the right information and feeding it to Claude. While some people are still using Claude as a regular chatbot, the real smart ones are making money. Claude helped me fully reverse-engineer his strategy - now you can build the same thing. There’s a complete professional-grade pipeline here, Jane Street quant level. You can keep scrolling and coping - or save this post, read article and build the same algo bot. Or just be smart and start copying his trades right now with this TG bot:

Chinese engineer made $600,000 in ONE MONTH trading BTC markets on Polymarket. Right tools + 6-layer execution stack, zero risk and pure math edge farming. He wins with an 85% probability - earn roughly $150,000 per week. Every week. His wallet: ~$7,000,000 a year. Not a bad return for simply finding the right information and feeding it to Claude. While some people are still using Claude as a regular chatbot, the real smart ones are making money. Claude helped me fully reverse-engineer his strategy - now you can build the same thing. There’s a complete professional-grade pipeline here, Jane Street quant level. You can keep scrolling and coping - or save this post, read article and build the same algo bot. Or just be smart and start copying his trades right now with this TG bot:

154,140 görüntüleme • 1 ay önce

I ran a backtest of a trader’s strategy that generated $387,000 in profit using Claude + Nautilus via PyPI. Result shocked me - mechanics are understandable to anyone. The real alpha is in the numbers under the hood. That’s what lets you pull $30k a week with pure math. I simulated every single one of his trades and broke down every transaction. This guy wallet: I reverse-engineered all his arbitrage calibrations, mean-reversion logic and mapped out the entire lifecycle of his bot. 3,789 markets. 12,441 fills. 87.3% win rate. Sharpe ratio 4.21. Broker simulator on nautilus-core, 41.8 GB of parquet data in DuckDB. Every trade is a perfect cycle. Every dollar earned is pure exploitation of inefficiency. He doesn’t predict the future - 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:

I ran a backtest of a trader’s strategy that generated $387,000 in profit using Claude + Nautilus via PyPI. Result shocked me - mechanics are understandable to anyone. The real alpha is in the numbers under the hood. That’s what lets you pull $30k a week with pure math. I simulated every single one of his trades and broke down every transaction. This guy wallet: I reverse-engineered all his arbitrage calibrations, mean-reversion logic and mapped out the entire lifecycle of his bot. 3,789 markets. 12,441 fills. 87.3% win rate. Sharpe ratio 4.21. Broker simulator on nautilus-core, 41.8 GB of parquet data in DuckDB. Every trade is a perfect cycle. Every dollar earned is pure exploitation of inefficiency. He doesn’t predict the future - 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:

163,725 görüntüleme • 1 ay önce

A former Citadel quant quit his $400k job, vanished from LinkedIn, and reappeared as an anonymous wallet on Polymarket making $7,500 a day. Unlike his old 9-5, this time he automated the whole thing with AI. Now he’s printing $50K every single week on complete autopilot. His wallet: No name, no Twitter, no Discord. Just a Polygon wallet quietly grinding crypto binaries 24/7. Here's the math: Polymarket binaries have one property no other market gives you: UP and DOWN on the same window must sum to $1.00, because one resolves at $1 and the other at $0. That's a deterministic anchor. Complete-set arbitrage: if UP + DOWN 0.05% but the token price hasn't adjusted. Fair probability: fair_prob = 0.5 + (|Δ_btc| / time_decay) × 5.0 Requires edge >2% + 10-min trend agreement. DIRECTIONAL fires in the final 30 seconds when composite confidence ≥0.45 and BTC confirms by >0.03%. This is what triggered the x88.5 SOL trade - late window confirmation against an underpriced token. MAKER posts limit orders 2¢ below the ask to earn the 20% maker rebate. That generates the 500+ daily fills. Position sizing is Kelly, capped at 25% of bankroll: kelly = edge / (1 − token_price) 5-min binaries approximate a random walk. Naive base WR = 50%, breakeven after fees ~53%. This wallet's WR is 78% across 10,729 fills — the filters are doing their job. Stack: Java 21 microservices, ClickHouse + Redpanda pipeline, paper mode validation before any live capital. Built to outrun a 2.7-second window. You don't need a name when the wallet does the talking. And most importantly, you can easily copy the public wallet using a bot: Save this - every number, formula and engine in this post is verifiable onchain.

A former Citadel quant quit his $400k job, vanished from LinkedIn, and reappeared as an anonymous wallet on Polymarket making $7,500 a day. Unlike his old 9-5, this time he automated the whole thing with AI. Now he’s printing $50K every single week on complete autopilot. His wallet: No name, no Twitter, no Discord. Just a Polygon wallet quietly grinding crypto binaries 24/7. Here's the math: Polymarket binaries have one property no other market gives you: UP and DOWN on the same window must sum to $1.00, because one resolves at $1 and the other at $0. That's a deterministic anchor. Complete-set arbitrage: if UP + DOWN 0.05% but the token price hasn't adjusted. Fair probability: fair_prob = 0.5 + (|Δ_btc| / time_decay) × 5.0 Requires edge >2% + 10-min trend agreement. DIRECTIONAL fires in the final 30 seconds when composite confidence ≥0.45 and BTC confirms by >0.03%. This is what triggered the x88.5 SOL trade - late window confirmation against an underpriced token. MAKER posts limit orders 2¢ below the ask to earn the 20% maker rebate. That generates the 500+ daily fills. Position sizing is Kelly, capped at 25% of bankroll: kelly = edge / (1 − token_price) 5-min binaries approximate a random walk. Naive base WR = 50%, breakeven after fees ~53%. This wallet's WR is 78% across 10,729 fills — the filters are doing their job. Stack: Java 21 microservices, ClickHouse + Redpanda pipeline, paper mode validation before any live capital. Built to outrun a 2.7-second window. You don't need a name when the wallet does the talking. And most importantly, you can easily copy the public wallet using a bot: Save this - every number, formula and engine in this post is verifiable onchain.

63,979 görüntüleme • 18 gün önce

A 33-year-old IT engineer got hooked on meteorology - and with Claude, this hobby turned into $87,000 profit. Claude as algorithm’s brain + MiroFish simulation engine allowed him to earn $5,000-$6,000 per month. Completely passive. His Polymarket profile is called automatedAItradingBot: Even his username and bio say it all: "Meteorologist. IT engineer. Automated bot testing" Every 5 minutes bot pulls fresh data from Open-Meteo API, runs it through a Mirofish simulation, then compares the result with the current odds on Polymarket. Any difference is pure profit. Kelly Criterion sizing, Expected Value scoring, 3 forecast sources across 20 cities, self-calibrating, TG alerts. Claude with the latest Opus 4.7 handles the entire process. End result? This Claude + Mirofish setup prints over $100k/year on autopilot. Bookmark this post + read if you want to build something like this yourself. But you don’t have to - you can copy every single trade this algorithm makes with 0ms delay using this TG bot:

101,408 görüntüleme • 1 ay önce

Student from Hong Kong hacked Polymarket trading algorithm using Chinese AI model Qwen3-Coder. Almost $2,000,000 extracted in March. Zero drama with censorship, Claude token prices, or TOS. Pure GodMode from Chinese open-source AI. 4 wallets. $1.7M profit in 30 days. All trading the same crypto Up/Down markets. On-chain proofs: 1st wallet: 2nd wallet: 3rd wallet: 4th wallet: All wallets went live March 2. Same markets. Same insane logic. Meanwhile the rest of the timeline is crying trying to make censored Claude create something. Open-source code for a leading Chinese coding model was available online. It can be run for free - using your own hardware. Qwen3 on GitHub: Chinese LLM industry is about to make everyone seriously rethink AI prices and subscriptions. These wallets are perfect for reverse-engineering. Bonus: even your Claude can explain exactly how they work. Save the post or you’ll lose the wallet addresses.

Student from Hong Kong hacked Polymarket trading algorithm using Chinese AI model Qwen3-Coder. Almost $2,000,000 extracted in March. Zero drama with censorship, Claude token prices, or TOS. Pure GodMode from Chinese open-source AI. 4 wallets. $1.7M profit in 30 days. All trading the same crypto Up/Down markets. On-chain proofs: 1st wallet: 2nd wallet: 3rd wallet: 4th wallet: All wallets went live March 2. Same markets. Same insane logic. Meanwhile the rest of the timeline is crying trying to make censored Claude create something. Open-source code for a leading Chinese coding model was available online. It can be run for free - using your own hardware. Qwen3 on GitHub: Chinese LLM industry is about to make everyone seriously rethink AI prices and subscriptions. These wallets are perfect for reverse-engineering. Bonus: even your Claude can explain exactly how they work. Save the post or you’ll lose the wallet addresses.

194,351 görüntüleme • 2 ay önce

This guy from Ohio made over $1,000,000 by doing just one thing - he built an AI trading bot for crypto markets. His algo has been printing money non-stop for TWO FULL YEARS. Not luck. Not fake. Just pure consistent alpha. I reverse-engineered the whole thing brick by brick. His wallet: Same trader. Same playbook. Five times. $34 -> $4,113 - ETH UP on Nov 25 (x119.7) $252 -> $22,202 - ETH UP on Feb 7 (x88.0) $46 -> $4,048 - ETH UP on Aug 15, NO side (x87.8) $138 -> $7,148 - SOL DOWN in September (x51.5) $63 -> $3,259 - ETH DOWN on May 16 (x51.1) $1,003,045 total profit. 3,210 trades. 78% win rate. I had to know if he was just lucky. So I rebuilt his entire pipeline using Claude + Horizon + a PolyBench fork running on Nautilus-core. 7 stages: Event Ingest -> CLOB Snap -> News Fetch -> AI Infer -> EV+ Gate -> Size -> Execute. CLOB depth at entry: $21K. Slippage budget: 0.6¢. Realized fill: 0.4¢. DuckDB parquet, 41.8 GB of point-in-time market state. He doesn’t predict ETH price. He reads the gap between what his model knows and what the crowd hasn’t priced in yet. Every dollar he made is someone else paying for not seeing the mispricing in time. Save this article if you want to learn how to build it. Or just copy the trades of the guy who has been trading perfectly for two years straight. Use this bot:

This guy from Ohio made over $1,000,000 by doing just one thing - he built an AI trading bot for crypto markets. His algo has been printing money non-stop for TWO FULL YEARS. Not luck. Not fake. Just pure consistent alpha. I reverse-engineered the whole thing brick by brick. His wallet: Same trader. Same playbook. Five times. $34 -> $4,113 - ETH UP on Nov 25 (x119.7) $252 -> $22,202 - ETH UP on Feb 7 (x88.0) $46 -> $4,048 - ETH UP on Aug 15, NO side (x87.8) $138 -> $7,148 - SOL DOWN in September (x51.5) $63 -> $3,259 - ETH DOWN on May 16 (x51.1) $1,003,045 total profit. 3,210 trades. 78% win rate. I had to know if he was just lucky. So I rebuilt his entire pipeline using Claude + Horizon + a PolyBench fork running on Nautilus-core. 7 stages: Event Ingest -> CLOB Snap -> News Fetch -> AI Infer -> EV+ Gate -> Size -> Execute. CLOB depth at entry: $21K. Slippage budget: 0.6¢. Realized fill: 0.4¢. DuckDB parquet, 41.8 GB of point-in-time market state. He doesn’t predict ETH price. He reads the gap between what his model knows and what the crowd hasn’t priced in yet. Every dollar he made is someone else paying for not seeing the mispricing in time. Save this article if you want to learn how to build it. Or just copy the trades of the guy who has been trading perfectly for two years straight. Use this bot:

69,947 görüntüleme • 23 gün önce