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Chinese ex-Citadel analyst quit. Spent 4 months building this instead. $1,800 became $154,000. One trade. Fully onchain. 8,500% return. Polymarket wallet public - go verify yourself. Wallet: The edge isn't a feeling. It's 35,000 simulations saying the price is wrong. $270k total extracted from the market. Always opposite the... consensus. He plugs into OTC desk flow, closed arbitrage feeds, cross-exchange imbalance data. The model doesn't react to price. It reacts to probability collapse. April 27 - everyone was certain. He was the only one running the actual math. Entered at 2.2% implied odds. Pure structure. Zero emotion. AI logic + private data + simulation depth = edge that doesn't dry up. Save the post and read the full breakdown. Copy trades in real time here:show more

st1ne

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24,988 views • 4 months ago •via X (Twitter)

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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:

cvxv666

282,748 views • 4 months ago

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:

cvxv666

203,703 views • 4 months ago

A 33-year-old quant from Hong Kong built a perfect BTC price simulation engine with a swarm of agents. 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: Humans can’t process dozens of gigabytes of data in seconds - but Claude can. Closed order book feeds from CEXs, live data from OTC trading desks, Pyth oracles - AI agent gathers all of it in one iteration. His algorithm instantly detects any mispricing in crypto markets and enters trade immediately. $369,000 all-time profit. Constantly fading the crowd because his simulation reads the market better than everyone else. 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 the full guide to build the same bot? Save the post and read the article. Want to start copying his trades right now? Use this TG copy-trading bot (US users can actually trade here, unlike the main Polymarket site):

A 33-year-old quant from Hong Kong built a perfect BTC price simulation engine with a swarm of agents. 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: Humans can’t process dozens of gigabytes of data in seconds - but Claude can. Closed order book feeds from CEXs, live data from OTC trading desks, Pyth oracles - AI agent gathers all of it in one iteration. His algorithm instantly detects any mispricing in crypto markets and enters trade immediately. $369,000 all-time profit. Constantly fading the crowd because his simulation reads the market better than everyone else. 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 the full guide to build the same bot? Save the post and read the article. Want to start copying his trades right now? Use this TG copy-trading bot (US users can actually trade here, unlike the main Polymarket site):

cvxv666

83,208 views • 4 months ago

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:

cvxv666

166,136 views • 4 months ago

Built a scanner that became my lifechanger. 500 lines of C++ found a wallet turning -$19K into $343K. The script tracks Polymarket wallets in real time. Flags anomalies. Dumps the data into my terminal. PurpleThunderBicycleMountain broke every threshold I coded. Expected arbitrage when I pulled the logs. Some bot buying both sides. Farming the spread. Standard stuff. → Wallet: Not what I found. This wallet picks one direction. Bets heavy. Walks away right almost every single time. The code showed me what he sees. BTC spikes on Binance. My terminal pings. Polymarket still shows old odds. 30 second delay. He buys YES at 25 cents while the market thinks it is 50/50. One ETH trade made my scanner light up red. Price dumped on spot. He loaded NO at 1.5 cents. Kept buying up to 15 cents. Window closed down. Every share paid $1. 785% return. Fifteen minutes. I had to run the calculation twice. $7,000 average position. $69 million volume. Dozens of trades per day. From a wallet three weeks old. I wrote this terminal to find edges. Spent months on the codebase. Did not expect it to find someone trading 30 seconds into the future. The lag is still there. My scanner is still running. The wallet is still printing. Sometimes the best trade is the code you write to find the trade.

Built a scanner that became my lifechanger. 500 lines of C++ found a wallet turning -$19K into $343K. The script tracks Polymarket wallets in real time. Flags anomalies. Dumps the data into my terminal. PurpleThunderBicycleMountain broke every threshold I coded. Expected arbitrage when I pulled the logs. Some bot buying both sides. Farming the spread. Standard stuff. → Wallet: Not what I found. This wallet picks one direction. Bets heavy. Walks away right almost every single time. The code showed me what he sees. BTC spikes on Binance. My terminal pings. Polymarket still shows old odds. 30 second delay. He buys YES at 25 cents while the market thinks it is 50/50. One ETH trade made my scanner light up red. Price dumped on spot. He loaded NO at 1.5 cents. Kept buying up to 15 cents. Window closed down. Every share paid $1. 785% return. Fifteen minutes. I had to run the calculation twice. $7,000 average position. $69 million volume. Dozens of trades per day. From a wallet three weeks old. I wrote this terminal to find edges. Spent months on the codebase. Did not expect it to find someone trading 30 seconds into the future. The lag is still there. My scanner is still running. The wallet is still printing. Sometimes the best trade is the code you write to find the trade.

Marlow

28,050 views • 8 months ago

this is legitimately brilliant trying it today because if this actually works the way he describes I'm completely changing how I trade on prediction markets like Polymarket i just gone through The Smart Ape 🔥's bot, he just spent weeks building a free tool that connects Polymarket odds to real-time news because he was tired of manually tracking everything. the insight here gathered is perfect: - top traders on Polymarket aren't running sophisticated bots. - they're just faster at spotting when the market price diverges from reality. - markets stay mispriced for HOURS after major news drops. 10-30% off sometimes he built polymarketnews(dot)xyz and it's actually insane: - AI scrapes every major publisher - flags bullish/bearish news with green/red markers directly on the price chart - updates in minutes. for instance, the Iran Khamenei market example, the news drops suggesting power consolidation, market doesn't react for hours, then crashes 40% I've been saying this forever, information asymmetry is the only real edge in prediction markets and he just made it for free absolute gold here i genuinely think this is one of those tools that becomes essential infrastructure for anyone serious about prediction markets. the edge isn't the bot it's the speed of information and he just leveled the playing field

this is legitimately brilliant trying it today because if this actually works the way he describes I'm completely changing how I trade on prediction markets like Polymarket i just gone through The Smart Ape 🔥's bot, he just spent weeks building a free tool that connects Polymarket odds to real-time news because he was tired of manually tracking everything. the insight here gathered is perfect: - top traders on Polymarket aren't running sophisticated bots. - they're just faster at spotting when the market price diverges from reality. - markets stay mispriced for HOURS after major news drops. 10-30% off sometimes he built polymarketnews(dot)xyz and it's actually insane: - AI scrapes every major publisher - flags bullish/bearish news with green/red markers directly on the price chart - updates in minutes. for instance, the Iran Khamenei market example, the news drops suggesting power consolidation, market doesn't react for hours, then crashes 40% I've been saying this forever, information asymmetry is the only real edge in prediction markets and he just made it for free absolute gold here i genuinely think this is one of those tools that becomes essential infrastructure for anyone serious about prediction markets. the edge isn't the bot it's the speed of information and he just leveled the playing field

arndxt

105,303 views • 8 months ago

a $40/month server beat a room full of analysts to the same trade by five and a half hours market opens at 9:30. his position was already in at 4am the system is a neural net trained on 11 years of tick data. it flagged the setup before the candle that "confirmed" it had even started forming this is the part retail misunderstands about ML in markets it isn't prediction in the mystical sense. it's pattern classification at a speed and scale human eyes physically cannot match the mechanics: 847,000 labeled historical setups as training data 4,200 data points per second ingested live each new state scored against every pattern the net has ever seen, in milliseconds the model isn't asking "where is price going" it's asking "how closely does the current microstructure match the conditions that preceded a move in my training set" that's a classification problem, and classification is what neural nets do better than anything else output: 3-4 candidate trades a day. he takes the top 2 by confidence score last 90 days: 71% win rate at 2.3 average risk-reward the edge isn't the architecture. the architecture is public pytorch is free, the papers are on arxiv, the network is a few hundred lines the edge is the labeling. what you feed it and how you tag the setups is the entire game retail feeds a model price and time and gets noise a desk feeds it order flow, volatility state, cross-asset context, each example hand-labeled by outcome same network. different training data. that's the whole difference retail watches the news at the open and reacts this system scored every pattern before sunrise and already decided you're not losing because your analysis is wrong you're losing to something that doesn't sleep, doesn't panic, and doesn't second-guess a probability it already computed the dataset was free. the framework was free. the compute was $40 a month the edge was never behind a paywall. it was sitting in a format almost nobody bothered to train on full breakdown in the article below

a $40/month server beat a room full of analysts to the same trade by five and a half hours market opens at 9:30. his position was already in at 4am the system is a neural net trained on 11 years of tick data. it flagged the setup before the candle that "confirmed" it had even started forming this is the part retail misunderstands about ML in markets it isn't prediction in the mystical sense. it's pattern classification at a speed and scale human eyes physically cannot match the mechanics: 847,000 labeled historical setups as training data 4,200 data points per second ingested live each new state scored against every pattern the net has ever seen, in milliseconds the model isn't asking "where is price going" it's asking "how closely does the current microstructure match the conditions that preceded a move in my training set" that's a classification problem, and classification is what neural nets do better than anything else output: 3-4 candidate trades a day. he takes the top 2 by confidence score last 90 days: 71% win rate at 2.3 average risk-reward the edge isn't the architecture. the architecture is public pytorch is free, the papers are on arxiv, the network is a few hundred lines the edge is the labeling. what you feed it and how you tag the setups is the entire game retail feeds a model price and time and gets noise a desk feeds it order flow, volatility state, cross-asset context, each example hand-labeled by outcome same network. different training data. that's the whole difference retail watches the news at the open and reacts this system scored every pattern before sunrise and already decided you're not losing because your analysis is wrong you're losing to something that doesn't sleep, doesn't panic, and doesn't second-guess a probability it already computed the dataset was free. the framework was free. the compute was $40 a month the edge was never behind a paywall. it was sitting in a format almost nobody bothered to train on full breakdown in the article below

delost

20,942 views • 2 months ago

I built a bot that arbitrages the gap between weather models and Polymarket odds it ran all night. I woke up to $9,685 and zero drawdown. it doesn't predict weather. it predicts where the market is wrong 6 forecast models. one engine. pure spread extraction no gut feeling. no manual trades. no emotion just forecast spread arb running 24/7 on VPS temp delta +0.6°C - bot sees it. market doesn't. trade fired. snowfall consensus 14" Chicago, odds still at yesterday's number. trade fired. 78 trades today. 73.1% win rate. sharpe 12.96 what runs under the hood: → ingests ECMWF, GFS, HRRR, NAM, UKMO, CMC every cycle → cross-checks forecasts in 142ms → detects when models disagree with Polymarket pricing → fires position before odds reprice → exits on convergence cyclone contracts, frost events, heat index, rain - doesn't matter the lag is always there. the bot is always first this isn't weather forecasting. it's taxing slow odds on polymarket

I built a bot that arbitrages the gap between weather models and Polymarket odds it ran all night. I woke up to $9,685 and zero drawdown. it doesn't predict weather. it predicts where the market is wrong 6 forecast models. one engine. pure spread extraction no gut feeling. no manual trades. no emotion just forecast spread arb running 24/7 on VPS temp delta +0.6°C - bot sees it. market doesn't. trade fired. snowfall consensus 14" Chicago, odds still at yesterday's number. trade fired. 78 trades today. 73.1% win rate. sharpe 12.96 what runs under the hood: → ingests ECMWF, GFS, HRRR, NAM, UKMO, CMC every cycle → cross-checks forecasts in 142ms → detects when models disagree with Polymarket pricing → fires position before odds reprice → exits on convergence cyclone contracts, frost events, heat index, rain - doesn't matter the lag is always there. the bot is always first this isn't weather forecasting. it's taxing slow odds on polymarket

Hanako

43,461 views • 6 months ago

A 35-year-old marketer from Hong Kong quit his job and got deeply into AI. Using Claude, he made $360,000 in just one month. He built a perfect BTC price simulation engine with MiroFish. Claude as algorithm’s brain + MiroFish simulation engine allowed him to earn $5,000-$15,000 in profit per trade. He left a funny easter egg about his previous profession in his Polymarket nickname - he called himself Marketing101. His algorithm instantly detects any mispricing in crypto markets and enters trade immediately. $366k 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. This isn’t "guessing where the chart will go" This is engineered money. Pure fusion of AI + MiroFish + insane math on exclusive data. Giving This Free for 24 hours. To get it: 1. Comment what ever think about it. ( Mandatory ) 2. Like and Retweet this post 3. Follow me Marry Evan

A 35-year-old marketer from Hong Kong quit his job and got deeply into AI. Using Claude, he made $360,000 in just one month. He built a perfect BTC price simulation engine with MiroFish. Claude as algorithm’s brain + MiroFish simulation engine allowed him to earn $5,000-$15,000 in profit per trade. He left a funny easter egg about his previous profession in his Polymarket nickname - he called himself Marketing101. His algorithm instantly detects any mispricing in crypto markets and enters trade immediately. $366k 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. This isn’t "guessing where the chart will go" This is engineered money. Pure fusion of AI + MiroFish + insane math on exclusive data. Giving This Free for 24 hours. To get it: 1. Comment what ever think about it. ( Mandatory ) 2. Like and Retweet this post 3. Follow me Marry Evan

Marry Evan

22,927 views • 4 months ago

PREDICTION MARKET RESEARCH JUST GOT KILLED BY ONE .MD FILE. The .md file in the video plugs any AI agent into 1,800 live data sources -> Polymarket orderbooks, satellite imagery, vessel tracking, NOAA weather, SEC filings, sports lines, and the top 100 KOL wallets. It's pref.trade. No APIs, no scraping, no signup and no card. An agent with this installed doesn't ask "What's the price". It pulls the orderbook depth on Polymarket, cross-references vessel positions in the Strait of Hormuz, scans the latest SEC filings on the names mentioned, and watches what the top 100 KOL wallets did in the last 4 hours. Before it makes a single call. The numbers are insane: > $0 in API fees. > $0 in data subscriptions. > 670+ capabilities behind a single endpoint. Every datapoint with full provenance back to the source. The mechanism is wild too: It's called Preference. An MCP server that gives any AI agent structured access to prediction markets -> Polymarket, Kalshi, Hyperliquid, dFlow AND the real-world signals that price them. Your agent asks one question, gets the full picture before it acts. It goes way past Polymarket: Smart-money mirroring on the top 100 wallets in real time. Cross-venue arb scanners and event-driven agents that watch tanker traffic in the Strait of Hormuz and trade oil-linked markets. Backtesting pipelines over historical data plus the world signals that moved each market. The model was never the bottleneck. The data was. One agent, one .md file and Live world data on tap. -> Retail still has 12 CoinGecko tabs open. Agents already have the orderbook. Full info and guide at Don't forget to save.

PREDICTION MARKET RESEARCH JUST GOT KILLED BY ONE .MD FILE. The .md file in the video plugs any AI agent into 1,800 live data sources -> Polymarket orderbooks, satellite imagery, vessel tracking, NOAA weather, SEC filings, sports lines, and the top 100 KOL wallets. It's pref.trade. No APIs, no scraping, no signup and no card. An agent with this installed doesn't ask "What's the price". It pulls the orderbook depth on Polymarket, cross-references vessel positions in the Strait of Hormuz, scans the latest SEC filings on the names mentioned, and watches what the top 100 KOL wallets did in the last 4 hours. Before it makes a single call. The numbers are insane: > $0 in API fees. > $0 in data subscriptions. > 670+ capabilities behind a single endpoint. Every datapoint with full provenance back to the source. The mechanism is wild too: It's called Preference. An MCP server that gives any AI agent structured access to prediction markets -> Polymarket, Kalshi, Hyperliquid, dFlow AND the real-world signals that price them. Your agent asks one question, gets the full picture before it acts. It goes way past Polymarket: Smart-money mirroring on the top 100 wallets in real time. Cross-venue arb scanners and event-driven agents that watch tanker traffic in the Strait of Hormuz and trade oil-linked markets. Backtesting pipelines over historical data plus the world signals that moved each market. The model was never the bottleneck. The data was. One agent, one .md file and Live world data on tap. -> Retail still has 12 CoinGecko tabs open. Agents already have the orderbook. Full info and guide at Don't forget to save.

slash1s

61,850 views • 4 months ago

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. 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. You only need Claude + laptop + 1 hour/day. Giving This Free for 24 hours. To get it: 1. Comment the word 'Claude' 2. Like and Retweet this post 3. Follow me Marry Evan

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. 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. You only need Claude + laptop + 1 hour/day. Giving This Free for 24 hours. To get it: 1. Comment the word 'Claude' 2. Like and Retweet this post 3. Follow me Marry Evan

Marry Evan

63,387 views • 4 months ago

This guy built a trading bot on Polymarket with Claude Result: +$187,955 in 3 months His bot trades the microstructure of short-term crypto Up/Down markets using a strategy with 6 core elements: 1. At the start of each new 5-minute market, it gets the starting BTC price and compares it with the price at the end of the interval 2. Then it uses an external data source and constantly estimates the probability of Up or Down 3. For the calculation, it uses volatility, short-term momentum, price change speed, trading volume, and order imbalance 4. After that, the algorithm compares its own probability estimate with the price on Polymarket and buys the undervalued outcome 5. If BTC reverses, the model starts seeing the opposite outcome as more likely and buys it 6. By the end of the market, it holds a certain amount of both Up and Down, but one side is overweighted, and the final imbalance becomes its directional position His Polymarket username: 0xAAAAA Using this strategy and clean execution, he turned $8.6k into $188k His best trades: $573.85 -> $2,400.00 (+318.23%) $801.35 -> $2,400.00 (+199.49%) $927.26 -> $2,600.00 (+180.39%)

This guy built a trading bot on Polymarket with Claude Result: +$187,955 in 3 months His bot trades the microstructure of short-term crypto Up/Down markets using a strategy with 6 core elements: 1. At the start of each new 5-minute market, it gets the starting BTC price and compares it with the price at the end of the interval 2. Then it uses an external data source and constantly estimates the probability of Up or Down 3. For the calculation, it uses volatility, short-term momentum, price change speed, trading volume, and order imbalance 4. After that, the algorithm compares its own probability estimate with the price on Polymarket and buys the undervalued outcome 5. If BTC reverses, the model starts seeing the opposite outcome as more likely and buys it 6. By the end of the market, it holds a certain amount of both Up and Down, but one side is overweighted, and the final imbalance becomes its directional position His Polymarket username: 0xAAAAA Using this strategy and clean execution, he turned $8.6k into $188k His best trades: $573.85 -> $2,400.00 (+318.23%) $801.35 -> $2,400.00 (+199.49%) $927.26 -> $2,600.00 (+180.39%)

VALIX

13,971 views • 1 month ago

Citadel quant quit and walked out with one thing fund never lets leave the building: 120-year-old math that sees a market crash before the chart does. Every big desk runs it. None of them explain it. He turned it into an HMM bot running BTC 5min markets and made $570,000. It switches strategy the second the regime flips and cuts everything the moment panic spikes. His wallet: Full breakdown below. Here's what they actually see. You look at a Bitcoin chart and see a price. A quant sees three states: bull, bear, sideways. The market's always in one. The only question that pays is which one comes next. That's the math. It's called a Markov chain, and it runs on one rule: where price goes next depends only on where it is now. You count how often each state flips to another and drop it into a grid. That grid is a map of the market. Now the part that feels illegal. Want the odds of a crash twelve steps out? You multiply that grid by itself twelve times. One line of math, and you've got the probability of every future state. Then it acts: run the trend when calm, flip to mean reversion in chop, cut everything when panic odds spike. It doesn't predict the future. It gives you the odds of every version of it, then sizes the bet to match. That's the edge. Renaissance ran 66% a year for 30 years on math like this. You can build the basic version in a weekend. Bookmark & read this before it gets buried.

Citadel quant quit and walked out with one thing fund never lets leave the building: 120-year-old math that sees a market crash before the chart does. Every big desk runs it. None of them explain it. He turned it into an HMM bot running BTC 5min markets and made $570,000. It switches strategy the second the regime flips and cuts everything the moment panic spikes. His wallet: Full breakdown below. Here's what they actually see. You look at a Bitcoin chart and see a price. A quant sees three states: bull, bear, sideways. The market's always in one. The only question that pays is which one comes next. That's the math. It's called a Markov chain, and it runs on one rule: where price goes next depends only on where it is now. You count how often each state flips to another and drop it into a grid. That grid is a map of the market. Now the part that feels illegal. Want the odds of a crash twelve steps out? You multiply that grid by itself twelve times. One line of math, and you've got the probability of every future state. Then it acts: run the trend when calm, flip to mean reversion in chop, cut everything when panic odds spike. It doesn't predict the future. It gives you the odds of every version of it, then sizes the bet to match. That's the edge. Renaissance ran 66% a year for 30 years on math like this. You can build the basic version in a weekend. Bookmark & read this before it gets buried.

cvxv666

93,826 views • 2 months ago

a quant who started as a technical trader explained what changed everything for him he stopped trying to predict where price goes he started measuring the probability of each market state and betting only when the math was asymmetric that shift took him from drawing trendlines to writing models at 22 the realization was simple but brutal: technical analysis gives you a narrative quantitative analysis gives you a number one feels right the other is testable, repeatable, and either works or doesn't across 10,000 trades the setup on his desk tells the whole story no TradingView. no candlestick charts. just code, data, and a terminal he didn't go to MIT he didn't intern at Goldman he learned Python, statistics, and probability theory on his own and built something that actually worked > the math: free in any stats textbook > the data: free on Yahoo Finance, FRED, exchange APIs > the code: Python, 200 lines, running on a laptop > the barrier: not intelligence. just knowing this path exists most people spend years staring at indicators from the 1970s wondering why they can't find consistency the answer was never a better indicator it was a completely different framework one that treats trading as a math problem, not a prediction game full breakdown in the video below

a quant who started as a technical trader explained what changed everything for him he stopped trying to predict where price goes he started measuring the probability of each market state and betting only when the math was asymmetric that shift took him from drawing trendlines to writing models at 22 the realization was simple but brutal: technical analysis gives you a narrative quantitative analysis gives you a number one feels right the other is testable, repeatable, and either works or doesn't across 10,000 trades the setup on his desk tells the whole story no TradingView. no candlestick charts. just code, data, and a terminal he didn't go to MIT he didn't intern at Goldman he learned Python, statistics, and probability theory on his own and built something that actually worked > the math: free in any stats textbook > the data: free on Yahoo Finance, FRED, exchange APIs > the code: Python, 200 lines, running on a laptop > the barrier: not intelligence. just knowing this path exists most people spend years staring at indicators from the 1970s wondering why they can't find consistency the answer was never a better indicator it was a completely different framework one that treats trading as a math problem, not a prediction game full breakdown in the video below

delost

112,271 views • 3 months ago

Anthropic released an update for Claude, and one student turned $1,400 into $238,000 in 11 days. His wallet: 0xdE17 He’s not a trader. Not a developer. Just a student with a laptop and access to Claude. When Anthropic updated Claude’s skills architecture, he spent two nights reading the documentation and built a bot from scratch. The result: $1,430 → $238,006 in 11 days 366 trades 62% win rate Largest single win: $52,700 How it works: The bot scans Polymarket every few seconds looking for markets where the price deviates from fair value by more than 8%. That’s the edge. Most people never notice it. The bot always does. The strategy is simple: The market prices an event at 30¢ The real probability based on data is closer to 55¢ The bot enters, waits, and exits as the market reprices It’s not luck. It’s attention arbitrage. The biggest trade was a bet that Trump would sign a crypto executive order in March. The market priced it at 28¢. The bot entered with $16,000. Exited at 81¢. In 11 days, he went through a journey most traders never experience in years. Now the wallet is public, and with this terminal you can copy the trades in real time: 0xde17f7144fbd0eddb2679132c10ff5e74b120988 Copytrade → People keep asking him: “How much starting capital do you need?” He answered: “I had $1,400 and a sleepless night.” Anthropic built the tool. He simply wasn’t afraid to use it.

Anthropic released an update for Claude, and one student turned $1,400 into $238,000 in 11 days. His wallet: 0xdE17 He’s not a trader. Not a developer. Just a student with a laptop and access to Claude. When Anthropic updated Claude’s skills architecture, he spent two nights reading the documentation and built a bot from scratch. The result: $1,430 → $238,006 in 11 days 366 trades 62% win rate Largest single win: $52,700 How it works: The bot scans Polymarket every few seconds looking for markets where the price deviates from fair value by more than 8%. That’s the edge. Most people never notice it. The bot always does. The strategy is simple: The market prices an event at 30¢ The real probability based on data is closer to 55¢ The bot enters, waits, and exits as the market reprices It’s not luck. It’s attention arbitrage. The biggest trade was a bet that Trump would sign a crypto executive order in March. The market priced it at 28¢. The bot entered with $16,000. Exited at 81¢. In 11 days, he went through a journey most traders never experience in years. Now the wallet is public, and with this terminal you can copy the trades in real time: 0xde17f7144fbd0eddb2679132c10ff5e74b120988 Copytrade → People keep asking him: “How much starting capital do you need?” He answered: “I had $1,400 and a sleepless night.” Anthropic built the tool. He simply wasn’t afraid to use it.

Discover

114,291 views • 6 months ago

Hermes AI trading agent + math from this article = $440,000 profit on Polymarket in just 20 days. Zero profile views. This guy made almost $500k and everyone is acting like it’s completely normal. 85% win rate = he’s not guessing the future, he’s farming pure mathematical edge. Wallet of the agent: 850 green trades out of every 1,000. At his size and ROI he makes 11x more on winners than he loses. This is the real secret of any top PnL trader on Polymarket: stop guessing and and just exploit the math. Save this post so you don’t forget to read the article. Or take action right now and copy every trade this agent makes using this TG bot:

cvxv666

59,902 views • 5 months ago

Quant on Polymarket turned $313 into $296,000 in one month - and it never predicted Bitcoin's direction once. 65% win rate on 15-minute Up/Down markets. The edge wasn't the forecast. It was the order book. Wallet proof: It's the one thing retail never sees and bots live on: full bid/ask depth on any BTC/ETH/SOL Up/Down market, at any second in its history, down to 300ms - Binance depth beside it, replayable tick-by-tick on real fills. I've been pulling it from PolyHistorical Here's why it matters. Bloomberg ran the numbers: the top 1% of wallets, mostly bots, took 80%+ of all profits. Retail lost $131M net. Same predictions - better data. What that data shows: pull the depth on a BTC 5-minute market and watch the last minute. Resting bids at T-60 sit around $1,210. At T-10, $240. At T-3, $90. 95% of the liquidity you think you can hit vanishes before resolution. A $500 buy at T-30 eats ~4.2¢ of slippage - half the edge, gone. One tested pattern: when depth leans 65/35 while price sits flat, it reverts within 60s 73% of the time. Median lag from depth to price: 11 seconds. 312 signals in 30 days. The depth wasn't lagging. It was waiting. That's the whole game here - not calling the candle, but seeing depth shift before price does. This wallet did exactly that. Every level, every 300ms, 13,000+ resolved markets, free to replay.

Quant on Polymarket turned $313 into $296,000 in one month - and it never predicted Bitcoin's direction once. 65% win rate on 15-minute Up/Down markets. The edge wasn't the forecast. It was the order book. Wallet proof: It's the one thing retail never sees and bots live on: full bid/ask depth on any BTC/ETH/SOL Up/Down market, at any second in its history, down to 300ms - Binance depth beside it, replayable tick-by-tick on real fills. I've been pulling it from PolyHistorical Here's why it matters. Bloomberg ran the numbers: the top 1% of wallets, mostly bots, took 80%+ of all profits. Retail lost $131M net. Same predictions - better data. What that data shows: pull the depth on a BTC 5-minute market and watch the last minute. Resting bids at T-60 sit around $1,210. At T-10, $240. At T-3, $90. 95% of the liquidity you think you can hit vanishes before resolution. A $500 buy at T-30 eats ~4.2¢ of slippage - half the edge, gone. One tested pattern: when depth leans 65/35 while price sits flat, it reverts within 60s 73% of the time. Median lag from depth to price: 11 seconds. 312 signals in 30 days. The depth wasn't lagging. It was waiting. That's the whole game here - not calling the candle, but seeing depth shift before price does. This wallet did exactly that. Every level, every 300ms, 13,000+ resolved markets, free to replay.

cvxv666

23,228 views • 3 months ago

THIS WALLET STACKED $230K ON BTC UP/DOWN BETS. THE BLUEPRINT TO AUTOMATE THE SAME EDGE WITH CLAUDE The wallet is $230K all-time, every position a Bitcoin or Ethereum Up or Down market It never guesses direction. It enters only when the math and the market disagree THE STRATEGY: BTC moves are not fully random. When the market enters a committed directional state, continuation is measurable. That is Markov persistence Entry signal: > Δ = p̂ − q ≥ ε Model probability minus market price. Enter only on a 5% gap or more Persistence filter: > p(j*,j*) ≥ 0.87 Only trade states with 0.87 persistence or higher. Below that, skip. This is what holds the win rate above 65% with zero directional guessing Payout: > r = (1 − q) / q At q = 0.647 that is +54.5% a win. At q = 0.441, +126.7%. Lower entry price, bigger asymmetry Sizing: > f* = p − (1−p)/b Kelly. At p = 0.87, b = 0.647, f* ≈ 0.71. Size to the edge, never to gut HOW TO BUILD IT WITH CLAUDE: What separates this from a static bot: Claude reads its own trade journal every night and rewrites its own thresholds 1. Take an open-source Polymarket bot repo as your base logic. Feed it to Claude and have it migrate to CLOB v2: py_clob_client_v2, Safe wallet support, fee-aware evaluation 2. Hard-code the filters. Enter only when Δ ≥ 0.05 and p(j*,j*) ≥ 0.87. Apply Kelly on every fill. 3. Run DRY_RUN first. Log every signal, entry price, Markov state, and simulated P/L. No real money until the numbers hold for days 4. The nightly loop. Claude reads the journal, finds which persistence states actually won, adjusts MIN_PROB and MIN_EDGE, ships tomorrow's rules. The agent is sharper after 50 to 100 trades THE SETUP: Claude Opus as the brain. An open-source repo as the starting logic. A Polygon wallet with $50 to $100. Telegram for the morning report Start at $1 to $2 per trade while it learns. Scale only when the dry runs and the live fills line up 17,000 trades compound a thin edge into six figures. The model finds the edge. The nightly loop keeps it sharp Bookmark before you point a bot at your first window

THIS WALLET STACKED $230K ON BTC UP/DOWN BETS. THE BLUEPRINT TO AUTOMATE THE SAME EDGE WITH CLAUDE The wallet is $230K all-time, every position a Bitcoin or Ethereum Up or Down market It never guesses direction. It enters only when the math and the market disagree THE STRATEGY: BTC moves are not fully random. When the market enters a committed directional state, continuation is measurable. That is Markov persistence Entry signal: > Δ = p̂ − q ≥ ε Model probability minus market price. Enter only on a 5% gap or more Persistence filter: > p(j,j) ≥ 0.87 Only trade states with 0.87 persistence or higher. Below that, skip. This is what holds the win rate above 65% with zero directional guessing Payout: > r = (1 − q) / q At q = 0.647 that is +54.5% a win. At q = 0.441, +126.7%. Lower entry price, bigger asymmetry Sizing: > f* = p − (1−p)/b Kelly. At p = 0.87, b = 0.647, f* ≈ 0.71. Size to the edge, never to gut HOW TO BUILD IT WITH CLAUDE: What separates this from a static bot: Claude reads its own trade journal every night and rewrites its own thresholds 1. Take an open-source Polymarket bot repo as your base logic. Feed it to Claude and have it migrate to CLOB v2: py_clob_client_v2, Safe wallet support, fee-aware evaluation 2. Hard-code the filters. Enter only when Δ ≥ 0.05 and p(j,j) ≥ 0.87. Apply Kelly on every fill. 3. Run DRY_RUN first. Log every signal, entry price, Markov state, and simulated P/L. No real money until the numbers hold for days 4. The nightly loop. Claude reads the journal, finds which persistence states actually won, adjusts MIN_PROB and MIN_EDGE, ships tomorrow's rules. The agent is sharper after 50 to 100 trades THE SETUP: Claude Opus as the brain. An open-source repo as the starting logic. A Polygon wallet with $50 to $100. Telegram for the morning report Start at $1 to $2 per trade while it learns. Scale only when the dry runs and the live fills line up 17,000 trades compound a thin edge into six figures. The model finds the edge. The nightly loop keeps it sharp Bookmark before you point a bot at your first window

Yarchi

22,966 views • 4 months ago

Someone trained a swarm model on 3 years of NBA data and let it loose on Polymarket The result: $1.49M. He didn't build a better model. He built a better crowd. Here's how the system actually works. He takes MiroFish - an open-source engine that simulates thousands of AI agents and feeds it raw sports data. The actual building blocks: > Player stat vectors: points, rebounds, assists, eFG%, usage rate across 3 full seasons > Team form tensors: last 10 games, home/away splits, pace-of-play, defensive rating > Matchup history: head-to-head records, positional mismatches, referee tendencies > Injury probability models: medical staff reports weighted by recovery timelines > Line movement tracking: where the sharp money flows before tip-off Check how this wallet works: MiroFish generates 4,096 agents - analysts, bettors, insiders, oddsmakers - each with different reasoning. They argue, form clusters, shift opinions. Consensus emerges. He pipes that consensus into a 12-layer transformer trained on the full history of his 16,695 predictions. The model compares MiroFish output against live Polymarket odds. When the gap exceeds his Kelly criterion threshold, it enters. Lakers at 40 cents. MiroFish said 62%. One position: $190,823. The edge isn't data. Every sharp has data. The edge is simulating how 4,000 fake humans process it - before the real crowd does.

Someone trained a swarm model on 3 years of NBA data and let it loose on Polymarket The result: $1.49M. He didn't build a better model. He built a better crowd. Here's how the system actually works. He takes MiroFish - an open-source engine that simulates thousands of AI agents and feeds it raw sports data. The actual building blocks: > Player stat vectors: points, rebounds, assists, eFG%, usage rate across 3 full seasons > Team form tensors: last 10 games, home/away splits, pace-of-play, defensive rating > Matchup history: head-to-head records, positional mismatches, referee tendencies > Injury probability models: medical staff reports weighted by recovery timelines > Line movement tracking: where the sharp money flows before tip-off Check how this wallet works: MiroFish generates 4,096 agents - analysts, bettors, insiders, oddsmakers - each with different reasoning. They argue, form clusters, shift opinions. Consensus emerges. He pipes that consensus into a 12-layer transformer trained on the full history of his 16,695 predictions. The model compares MiroFish output against live Polymarket odds. When the gap exceeds his Kelly criterion threshold, it enters. Lakers at 40 cents. MiroFish said 62%. One position: $190,823. The edge isn't data. Every sharp has data. The edge is simulating how 4,000 fake humans process it - before the real crowd does.

BuBBliK

504,611 views • 6 months ago

This guy’s trading bot uses $4 sized buys and has already made $136,000 on Polymarket His bot trades short-term crypto Up/Down markets and combines late-resolution sniping, grid accumulation, and partial complete-set arbitrage His strategy has 5 parts: 1. At the start of each market, it records the asset price and constantly pulls real-time data from external sources 2. Then it evaluates price direction, volatility, time remaining, and liquidity on Polymarket 3. Based on that, it calculates its own probability for the Up or Down outcome 4. It buys the undervalued outcome when it sees a mispricing, then builds the opposite side if Up + Down is below $1 5. Before the market ends, it increases one side if that side becomes the clear favorite This guy’s Polymarket account: Using this strategy and clean execution, he captures a consistent edge and repeats it thousands of times, growing his capital

This guy’s trading bot uses $4 sized buys and has already made $136,000 on Polymarket His bot trades short-term crypto Up/Down markets and combines late-resolution sniping, grid accumulation, and partial complete-set arbitrage His strategy has 5 parts: 1. At the start of each market, it records the asset price and constantly pulls real-time data from external sources 2. Then it evaluates price direction, volatility, time remaining, and liquidity on Polymarket 3. Based on that, it calculates its own probability for the Up or Down outcome 4. It buys the undervalued outcome when it sees a mispricing, then builds the opposite side if Up + Down is below $1 5. Before the market ends, it increases one side if that side becomes the clear favorite This guy’s Polymarket account: Using this strategy and clean execution, he captures a consistent edge and repeats it thousands of times, growing his capital

VALIX

36,334 views • 2 months ago