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tried to visualize how alliswell's volatility-farming engine printed $227k on Polymarket and why this spread-capture system trades 40x per hour but most positions are under $50 this isn't about predicting outcomes it's about exploiting micro-inefficiencies in real-time order flow before they disappear ➤ the mechanics: algorithmic ladder orders that... sell at 77¢, buy back at 73-74¢ within minutes position sizes scale from $0.37 to $3k depending on spread width and book depth ➤ his biggest single win was $137k that one trade covers 500+ micro-losses. the hit rate doesn't matter when winners are asymmetric websocket feeds monitoring order book changes in milliseconds, automated position sizing that adjusts to volatility, sub-second execution when spreads dislocate most underestimate how much infrastructure this requires to run 24/7 without breaking account:show more

wincy.eth

18,729 subscribers

15,634 次观看 • 9 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

30 条评论

Pengi 的头像

Pengi9 个月前

Impressive micro-efficiency, love ladder strategy

Kyle the Writer 的头像

Kyle the Writer9 个月前

yo still didn't get how do you guys make these visualisations

wincy.eth 的头像

wincy.eth9 个月前

👀👀

PercentBet 的头像

PercentBet9 个月前

Looks better than Bloomberg Terminal 😅

wincy.eth 的头像

wincy.eth9 个月前

hah thanks

Gipp 🦅 的头像

Gipp 🦅9 个月前

bots are still showing incredible results

wincy.eth 的头像

wincy.eth9 个月前

as always u know

zoya 的头像

zoya9 个月前

This is pure infra-driven edge

Undertaker 的头像

Undertaker9 个月前

Keep sharing

wincy.eth 的头像

wincy.eth9 个月前

do you like ?

Suhaan 的头像

Suhaan9 个月前

Wow, insane speed and precision for small wins!

wincy.eth 的头像

wincy.eth9 个月前

yeah

darkzodchi 的头像

darkzodchi9 个月前

bots be winning

wincy.eth 的头像

wincy.eth9 个月前

always

PolymarketHistory 的头像

PolymarketHistory9 个月前

Amazing green terminal

wincy.eth 的头像

wincy.eth9 个月前

thx bro

Logics 的头像

Logics9 个月前

the video looks like ur hacking the pentagon

wincy.eth 的头像

wincy.eth9 个月前

lmao

Tengen 的头像

Tengen9 个月前

could watch this forever, wincy

wincy.eth 的头像

wincy.eth9 个月前

all for you my fren

Carmelo schepis 的头像

Carmelo schepis9 个月前

interesting

QFS17 的头像

QFS179 个月前

cool 👌

Kevin2K 的头像

Kevin2K9 个月前

money printing bot?

Bitcoin Hustler 的头像

Bitcoin Hustler9 个月前

micro scalping on speed and spreads brilliant execution

Nitesh (prediction arc) 的头像

Nitesh (prediction arc)9 个月前

looks great

🟢opusbt🟢 的头像

🟢opusbt🟢9 个月前

how the f someone created that😭😭😭

0xPolykid 的头像

0xPolykid9 个月前

Any tip for sub‑second execution? ⚡️

Jason傑森 🇭🇰 | 🛠️ 的头像

Jason傑森 🇭🇰 | 🛠️9 个月前

wow they just cash in quietly each day

rudy.DeFi 的头像

rudy.DeFi9 个月前

The guy is literally running on the same server as the Polymarket order book

shivi 的头像

shivi9 个月前

this sounds wild. makes you wonder about the future of trading strategies

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Daniro

53,065 次观看 • 3 个月前

$SPY Same 300 trades as my other studies. Same 80% win rate. The stop is back at -50%... but this time I sell the whole position the second it hits +20%. Starting account: $2,000 $500 every trade Win rate: 80%. My actual win rate. Take profit: all out at +20% Stop loss: -50% 300 trades Result: $2,000 turned into $11,000. Sounds fine, right? Now compare it to the exact same trades with the ladder (1/3 off at +25, +50, +75): Ladder: $47,000 All out at +20%: $11,000 Same entries. Same losers. Same stop. That's $36,000 left on the table just from getting scared on the winners. Here's why... When you sell everything at +20%, a winner pays $100 and a loser costs $250. You need to win 72% of the time just to break even. At 80% you're barely ahead, making $30 a trade. With the ladder, a winner pays $250 and a loser costs $250. You only need to win half the time to break even. Same 80% win rate, $150 a trade. Your stop protects your account. Your exits decide how much you actually make. Most traders think the problem is their entries. It's usually what they do after they're in.

$SPY Same 300 trades as my other studies. Same 80% win rate. The stop is back at -50%... but this time I sell the whole position the second it hits +20%. Starting account: $2,000 $500 every trade Win rate: 80%. My actual win rate. Take profit: all out at +20% Stop loss: -50% 300 trades Result: $2,000 turned into $11,000. Sounds fine, right? Now compare it to the exact same trades with the ladder (1/3 off at +25, +50, +75): Ladder: $47,000 All out at +20%: $11,000 Same entries. Same losers. Same stop. That's $36,000 left on the table just from getting scared on the winners. Here's why... When you sell everything at +20%, a winner pays $100 and a loser costs $250. You need to win 72% of the time just to break even. At 80% you're barely ahead, making $30 a trade. With the ladder, a winner pays $250 and a loser costs $250. You only need to win half the time to break even. Same 80% win rate, $150 a trade. Your stop protects your account. Your exits decide how much you actually make. Most traders think the problem is their entries. It's usually what they do after they're in.

Clint Awana

16,335 次观看 • 11 天前

This trader used Claude to build a Quant Bot and made +$212,121 on Polymarket 146,603 predictions in 267 days with a 42% win rate How is this account bringing in about $794 per day? The logic is simple: 1. It trades short crypto “Up / Down” markets at around 23 trades per hour 2. The bot enters markets in several steps instead of placing the entire position at once 3. It can take one outcome first, then wait for the probabilities to shift before adding the opposite side at a better moment 4. Part of the position can then become hedged, while the remaining shares stay exposed to the outcome the model still favors This trader’s Polymarket account: pspspsps5 Follow this account and trade on Polymarket through this bot: Most profitable trades: $372 → $1,650 (+$1,278 +344.1%) $24 → $1,207 (+$1,183 +4,899.9%) $403 → $1,393 (+$990 +245.8%) The real edge is in how aggressively the bot can reuse the same setup across thousands of short crypto windows without needing a high win rate

This trader used Claude to build a Quant Bot and made +$212,121 on Polymarket 146,603 predictions in 267 days with a 42% win rate How is this account bringing in about $794 per day? The logic is simple: 1. It trades short crypto “Up / Down” markets at around 23 trades per hour 2. The bot enters markets in several steps instead of placing the entire position at once 3. It can take one outcome first, then wait for the probabilities to shift before adding the opposite side at a better moment 4. Part of the position can then become hedged, while the remaining shares stay exposed to the outcome the model still favors This trader’s Polymarket account: pspspsps5 Follow this account and trade on Polymarket through this bot: Most profitable trades: $372 → $1,650 (+$1,278 +344.1%) $24 → $1,207 (+$1,183 +4,899.9%) $403 → $1,393 (+$990 +245.8%) The real edge is in how aggressively the bot can reuse the same setup across thousands of short crypto windows without needing a high win rate

Daniro

11,647 次观看 • 2 个月前

This trader turned $76 into +$4,304 with a single bet on the weather market! Account: His PnL in March: -$1,000. His PnL now: +$12,000. Best trades: $76 -> $4,304 $19 -> $1,370 $52 -> $1,016 Main strategy: buying low-probability outcomes. This approach can lead to 50 losses in a row, but weather markets are full of inefficiencies. That’s why he sticks to his strategy, and in the end it pays off. With this approach, win rate doesn’t matter. One successful 1¢ trade can generate huge profit even if the previous 49 trades were losses. Simple math. The lower the probability of the outcome, the smaller his position size. Perfect use of the Kelly Criterion allows him to avoid going negative from incorrect sizing. Result: +$10,000 in just one month! To profit from this strategy, just set up copy trading on his account:

This trader turned $76 into +$4,304 with a single bet on the weather market! Account: His PnL in March: -$1,000. His PnL now: +$12,000. Best trades: $76 -> $4,304 $19 -> $1,370 $52 -> $1,016 Main strategy: buying low-probability outcomes. This approach can lead to 50 losses in a row, but weather markets are full of inefficiencies. That’s why he sticks to his strategy, and in the end it pays off. With this approach, win rate doesn’t matter. One successful 1¢ trade can generate huge profit even if the previous 49 trades were losses. Simple math. The lower the probability of the outcome, the smaller his position size. Perfect use of the Kelly Criterion allows him to avoid going negative from incorrect sizing. Result: +$10,000 in just one month! To profit from this strategy, just set up copy trading on his account:

me_cool_off

12,213 次观看 • 6 个月前

This trader used Claude to build a Quant Bot and made +$280,122 on Polymarket 33,043 predictions in 144 days with a 51% win rate How is this account bringing in about $1,945 per day? The logic is simple: 1. It concentrates on short crypto “Up / Down” markets, averaging about 10 trades per hour 2. Rather than treating every window as a single prediction, the system appears to keep reevaluating the probabilities while the market is still open 3. It can build a directional position first, then use the opposite outcome later to reduce risk or improve the structure when conditions change This trader’s Polymarket account: Most profitable trades: $10,219 → $19,041 (+$8,822 +86.3%) $12,355 → $20,800 (+$8,445 +68.4%) $7,605 → $15,571 (+$7,966 +104.8%) The 51% win rate is only part of the picture. Most of the performance comes from how the system sizes, hedges, and restructures exposure across more than 33,000 entries

This trader used Claude to build a Quant Bot and made +$280,122 on Polymarket 33,043 predictions in 144 days with a 51% win rate How is this account bringing in about $1,945 per day? The logic is simple: 1. It concentrates on short crypto “Up / Down” markets, averaging about 10 trades per hour 2. Rather than treating every window as a single prediction, the system appears to keep reevaluating the probabilities while the market is still open 3. It can build a directional position first, then use the opposite outcome later to reduce risk or improve the structure when conditions change This trader’s Polymarket account: Most profitable trades: $10,219 → $19,041 (+$8,822 +86.3%) $12,355 → $20,800 (+$8,445 +68.4%) $7,605 → $15,571 (+$7,966 +104.8%) The 51% win rate is only part of the picture. Most of the performance comes from how the system sizes, hedges, and restructures exposure across more than 33,000 entries

Daniro

54,622 次观看 • 2 个月前

A Polymarket trader turned $272 into $14,000 on ETH and $364 into $29,000 on XRP in the same 60 days he banked $300K total 4,000 trades across ETH, SOL, XRP. Averaging $4,800 profit per day Profile: Setup looks semi-automated: human strategy, bot execution The edge: He farms safe yield on NO outcomes that are nearly impossible then uses that steady income to fund tiny asymmetric bets with massive upside Two engines running side by side: - Boring engine: buy NO at 98¢ on unlikely outcomes, collect $0.02 spread, repeat - Lottery engine: buy YES at pennies on plausible tails, occasional 50–100x payouts The boring engine covers the cost of all the lottery tickets that expire worthless. The lottery wins compound the account Most traders pick one or the other chase steady yield, or chase moonshots. He runs both at once, and that’s the entire edge Less emotional trading. More structured volatility extraction

Valentin

21,774 次观看 • 5 个月前

Large losses are devastating — it doesn't matter if you're a beginner trader or one with 10+ years of performance under your belt. Yesterday, we uploaded one of the most in-depth guides to Risk Management on the internet. Here's what we cover: → 3 key levers that control risk: size, stops, & position count → Calculating open risk & protecting your portfolio during corrections → Why tight & logical stops are the foundation of professional trading → Real-world sizing rules for swing traders and position traders → How to survive gap-downs, control drawdowns, and avoid catastrophic losses If you’re building your system or trying to stay consistent in this market, this is the only video you should dedicate time to studying this week! 🦁

Large losses are devastating — it doesn't matter if you're a beginner trader or one with 10+ years of performance under your belt. Yesterday, we uploaded one of the most in-depth guides to Risk Management on the internet. Here's what we cover: → 3 key levers that control risk: size, stops, & position count → Calculating open risk & protecting your portfolio during corrections → Why tight & logical stops are the foundation of professional trading → Real-world sizing rules for swing traders and position traders → How to survive gap-downs, control drawdowns, and avoid catastrophic losses If you’re building your system or trying to stay consistent in this market, this is the only video you should dedicate time to studying this week! 🦁

TraderLion

38,124 次观看 • 1 年前

Someone made a Claude-powered bot that made $381,000+ on Polymarket. Almost nobody noticed. But he wasn’t predicting BTC direction like everyone else. He built a market reaction engine. Wallet: What the system does: • pulls live CLOB order book data • tracks OTC liquidity shifts • runs thousands of BTC simulations in seconds • detects contracts lagging behind sentiment • enters before repricing • exits minutes later with the spread Results: • 3,464 trades • 78.6% win rate • 381k profit The real edge wasn’t predicting Bitcoin. It was reacting faster than the market could update itself. By the time most traders noticed the move, the trade was already finished. This isn’t gambling anymore. It’s latency + AI + execution.

Someone made a Claude-powered bot that made $381,000+ on Polymarket. Almost nobody noticed. But he wasn’t predicting BTC direction like everyone else. He built a market reaction engine. Wallet: What the system does: • pulls live CLOB order book data • tracks OTC liquidity shifts • runs thousands of BTC simulations in seconds • detects contracts lagging behind sentiment • enters before repricing • exits minutes later with the spread Results: • 3,464 trades • 78.6% win rate • 381k profit The real edge wasn’t predicting Bitcoin. It was reacting faster than the market could update itself. By the time most traders noticed the move, the trade was already finished. This isn’t gambling anymore. It’s latency + AI + execution.

Casey

15,758 次观看 • 5 个月前

This trader used Claude to build a Quant Bot and made +$201,747 on Polymarket 42,429 predictions in 55 days with a 47% win rate How is this account bringing in about $3,668 per day? The logic is simple: 1. It moves through short crypto “Up / Down” markets at roughly 32 trades per hour 2. It can establish one side first, wait for the probabilities to change, and add the opposite outcome later when that creates a stronger hedge 3. The bot then shifts exposure as new signals appear instead of remaining tied to its original position This trader’s Polymarket account: mo-money Most profitable trades: $1,642 → $3,531 (+$1,889 +115.1%) $773 → $2,588 (+$1,816 +235.0%) $517 → $2,203 (+$1,686 +326.2%) A 47% win rate is enough when the system keeps the stronger outcomes larger than the losing ones across tens of thousands of entries

This trader used Claude to build a Quant Bot and made +$201,747 on Polymarket 42,429 predictions in 55 days with a 47% win rate How is this account bringing in about $3,668 per day? The logic is simple: 1. It moves through short crypto “Up / Down” markets at roughly 32 trades per hour 2. It can establish one side first, wait for the probabilities to change, and add the opposite outcome later when that creates a stronger hedge 3. The bot then shifts exposure as new signals appear instead of remaining tied to its original position This trader’s Polymarket account: mo-money Most profitable trades: $1,642 → $3,531 (+$1,889 +115.1%) $773 → $2,588 (+$1,816 +235.0%) $517 → $2,203 (+$1,686 +326.2%) A 47% win rate is enough when the system keeps the stronger outcomes larger than the losing ones across tens of thousands of entries

Daniro

27,568 次观看 • 3 个月前

This trader used Claude to build a Quant Bot and made +$130,992 on Polymarket 29,721 predictions in 132 days with a 50% win rate How is this account bringing in about $992 per day? The logic is simple: 1. It focuses on short crypto “Up / Down” markets, averaging roughly 9 trades per hour 2. Instead of relying on one entry, the bot appears to build its position gradually as the probabilities change throughout each window 3. It can take exposure on one outcome first, then wait for a favorable move before adding the opposite side and locking part of the position into a hedge This trader’s Polymarket account: nagi777 Most profitable trades: $54 → $1,165 (+$1,111 +2,077.2%) $28 → $1,127 (+$1,100 +3,961.7%) $234 → $1,311 (+$1,077 +459.8%) A 50% win rate is enough for this system because the result depends on how each position is constructed and modified over time, not simply on finishing more markets on the winning side

This trader used Claude to build a Quant Bot and made +$130,992 on Polymarket 29,721 predictions in 132 days with a 50% win rate How is this account bringing in about $992 per day? The logic is simple: 1. It focuses on short crypto “Up / Down” markets, averaging roughly 9 trades per hour 2. Instead of relying on one entry, the bot appears to build its position gradually as the probabilities change throughout each window 3. It can take exposure on one outcome first, then wait for a favorable move before adding the opposite side and locking part of the position into a hedge This trader’s Polymarket account: nagi777 Most profitable trades: $54 → $1,165 (+$1,111 +2,077.2%) $28 → $1,127 (+$1,100 +3,961.7%) $234 → $1,311 (+$1,077 +459.8%) A 50% win rate is enough for this system because the result depends on how each position is constructed and modified over time, not simply on finishing more markets on the winning side

Daniro

53,229 次观看 • 2 个月前

One common reason why traders blow up is because of poor position sizing. In other words, how much do you bet on a trade. You can be right on direction 60% of the time and still lose everything if you size your positions poorly. One oversized trade can wipe out months of gains. This is why position sizing is a big part of risk management. Sandeep Rao - SEBI Reg. RA🖖 recently spoke to Tom Basso, one of the original Market Wizards, to discuss his approach to trading. I was listening to the interview and the one thing that stood out to me was how Tom's thinking on position sizing evolved over decades. He started simple: risk the same percentage of equity on every trade, inspired by Larry Hite's philosophy that every bet should be equal in terms of potential loss. But then came a silver trade with explosive volatility. Clients were calling, nervous about the wild swings. So he realized it wasn't just about the amount you could lose—it was also about the speed of movement. High volatility creates psychological stress that leads to poor decisions. So he added a second layer: volatility as a percentage of equity. Now he'd calculate both risk % and volatility %, then take the smaller of the two. Then came the third refinement: margin-to-equity ratios. Some markets have deceptively low risk and volatility but require high margin because of sudden jump risk. By incorporating all three factors, he never got caught overexposed. The result was a position sizing system that automatically scales down when markets get too volatile, protects against margin squeezes, and keeps portfolio risk in check. It's really interesting conversation. Link to the full interview is in the comments.

One common reason why traders blow up is because of poor position sizing. In other words, how much do you bet on a trade. You can be right on direction 60% of the time and still lose everything if you size your positions poorly. One oversized trade can wipe out months of gains. This is why position sizing is a big part of risk management. Sandeep Rao - SEBI Reg. RA🖖 recently spoke to Tom Basso, one of the original Market Wizards, to discuss his approach to trading. I was listening to the interview and the one thing that stood out to me was how Tom's thinking on position sizing evolved over decades. He started simple: risk the same percentage of equity on every trade, inspired by Larry Hite's philosophy that every bet should be equal in terms of potential loss. But then came a silver trade with explosive volatility. Clients were calling, nervous about the wild swings. So he realized it wasn't just about the amount you could lose—it was also about the speed of movement. High volatility creates psychological stress that leads to poor decisions. So he added a second layer: volatility as a percentage of equity. Now he'd calculate both risk % and volatility %, then take the smaller of the two. Then came the third refinement: margin-to-equity ratios. Some markets have deceptively low risk and volatility but require high margin because of sudden jump risk. By incorporating all three factors, he never got caught overexposed. The result was a position sizing system that automatically scales down when markets get too volatile, protects against margin squeezes, and keeps portfolio risk in check. It's really interesting conversation. Link to the full interview is in the comments.

Nithin Kamath

59,340 次观看 • 10 个月前

This guy used OpenAI Dots to build a Quant Execution Arbitrage system and it made $4,004 a day on Polymarket The result is already +$232,207 PnL in 58 days with about $390 per average trade, repeating the same setup 32 times every hour across BTC "Up or Down" markets Several specialized Dots agents powered by GPT-6 Astra work together as one system: 1. Bid-Ask Spread measures the immediate cost of entering Spread = Best Ask - Best Bid A wider spread makes execution more expensive The bot only enters when the available edge is large enough to survive that spread 2. All-in Execution Cost determines whether the arbitrage is actually worth taking The displayed edge is not the real edge after execution: Net Edge = Raw Edge - Spread - Slippage - Fees Slippage appears when the order consumes several price levels Fees add another cost to every completed trade If those costs consume the edge, the bot skips or cancels the remaining order This trader’s Polymarket account: Most profitable trades: $1,591 → $4,044 (+$2,453) $1,584 → $3,517 (+$1,932) $1,674 → $3,424 (+$1,750) The bot trades only the edge that remains after spread, slippage and fees

This guy used OpenAI Dots to build a Quant Execution Arbitrage system and it made $4,004 a day on Polymarket The result is already +$232,207 PnL in 58 days with about $390 per average trade, repeating the same setup 32 times every hour across BTC "Up or Down" markets Several specialized Dots agents powered by GPT-6 Astra work together as one system: 1. Bid-Ask Spread measures the immediate cost of entering Spread = Best Ask - Best Bid A wider spread makes execution more expensive The bot only enters when the available edge is large enough to survive that spread 2. All-in Execution Cost determines whether the arbitrage is actually worth taking The displayed edge is not the real edge after execution: Net Edge = Raw Edge - Spread - Slippage - Fees Slippage appears when the order consumes several price levels Fees add another cost to every completed trade If those costs consume the edge, the bot skips or cancels the remaining order This trader’s Polymarket account: Most profitable trades: $1,591 → $4,044 (+$2,453) $1,584 → $3,517 (+$1,932) $1,674 → $3,424 (+$1,750) The bot trades only the edge that remains after spread, slippage and fees

Daniro

37,610 次观看 • 28 天前

This guy used Grok Bot to build a Quant position scaling system and it made $1,375 a day The result is already +$235,199 PnL in 171 days with only $46 per average trade, repeating the same setup 25 times every hour across BTC "Up or Down" markets Several agents can split the workflow between pricing, sizing and execution: 1. Every new BTC move changes the next order > A position can begin small: First fill: $18 at 37¢ > If the signal strengthens: Second fill: $34 at 40¢ > If probability continues moving in the same direction: Third fill: $61 at 44¢ The system scales only while the estimated edge survives 2. Maker-Taker logic controls how aggressively it gets filled With enough time, the system leaves passive orders and waits for fills As the edge starts disappearing, it can switch to aggressive execution Expected Edge > Spread + Slippage + Execution Cost If that condition disappears, the next order is cancelled This trader’s Polymarket account: 101,608 predictions with a 50% win rate Most profitable trades: $2,796 → $6,360 (+$3,564) $1,630 → $3,989 (+$2,359) $1,300 → $3,602 (+$2,302) The edge comes from scaling into the position only while the signal survives and switching execution style as market conditions change

This guy used Grok Bot to build a Quant position scaling system and it made $1,375 a day The result is already +$235,199 PnL in 171 days with only $46 per average trade, repeating the same setup 25 times every hour across BTC "Up or Down" markets Several agents can split the workflow between pricing, sizing and execution: 1. Every new BTC move changes the next order > A position can begin small: First fill: $18 at 37¢ > If the signal strengthens: Second fill: $34 at 40¢ > If probability continues moving in the same direction: Third fill: $61 at 44¢ The system scales only while the estimated edge survives 2. Maker-Taker logic controls how aggressively it gets filled With enough time, the system leaves passive orders and waits for fills As the edge starts disappearing, it can switch to aggressive execution Expected Edge > Spread + Slippage + Execution Cost If that condition disappears, the next order is cancelled This trader’s Polymarket account: 101,608 predictions with a 50% win rate Most profitable trades: $2,796 → $6,360 (+$3,564) $1,630 → $3,989 (+$2,359) $1,300 → $3,602 (+$2,302) The edge comes from scaling into the position only while the signal survives and switching execution style as market conditions change

Daniro

75,779 次观看 • 1 个月前

The most dangerous misconception about Polymarket is that BTC 5m markets are just a casino. Then you come across a wallet like this: +$29,314 in a day A streak of closed trades Huge position sizes And almost zero margin for error That’s when you realize - the problem isn’t "randomness" in the market. The problem is that most people don’t understand how timing, execution, and exits actually work here. That’s exactly why I started building my own engine.

The most dangerous misconception about Polymarket is that BTC 5m markets are just a casino. Then you come across a wallet like this: +$29,314 in a day A streak of closed trades Huge position sizes And almost zero margin for error That’s when you realize - the problem isn’t "randomness" in the market. The problem is that most people don’t understand how timing, execution, and exits actually work here. That’s exactly why I started building my own engine.

Marko

32,954 次观看 • 6 个月前

This trader used Claude to build a Quant Bot and made +$237,234 on Polymarket 18,163 predictions in 111 days with a 54% win rate How is this account bringing in about $2,137 per day? The logic is simple: 1. It focuses on short crypto “Up / Down” markets, running the same model across many consecutive windows at about 7 trades per hour 2. The system appears to combine temporal arbitrage, hedged directional exposure, and active inventory rotation 3. Instead of depending on a single oversized position, it repeats this structure across thousands of entries This trader’s Polymarket account: aswfadq1555 Most profitable trades: $5,377 → $12,180 (+$6,803 +126.5%) $4,054 → $10,240 (+$6,186 +152.6%) $2,997 → $8,608 (+$5,611 +187.2%) The result comes from keeping the same system active across a large number of short windows and constantly adjusting exposure as the probabilities move

This trader used Claude to build a Quant Bot and made +$237,234 on Polymarket 18,163 predictions in 111 days with a 54% win rate How is this account bringing in about $2,137 per day? The logic is simple: 1. It focuses on short crypto “Up / Down” markets, running the same model across many consecutive windows at about 7 trades per hour 2. The system appears to combine temporal arbitrage, hedged directional exposure, and active inventory rotation 3. Instead of depending on a single oversized position, it repeats this structure across thousands of entries This trader’s Polymarket account: aswfadq1555 Most profitable trades: $5,377 → $12,180 (+$6,803 +126.5%) $4,054 → $10,240 (+$6,186 +152.6%) $2,997 → $8,608 (+$5,611 +187.2%) The result comes from keeping the same system active across a large number of short windows and constantly adjusting exposure as the probabilities move

Daniro

23,337 次观看 • 3 个月前