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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

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15,582 Aufrufe • vor 5 Monaten •via X (Twitter)

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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

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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! 🦁

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TraderLion

37,480 Aufrufe • vor 1 Jahr

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

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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

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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.

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I activated a bot that market makes on Polymarket and earns passive income from the spread Main function: Market Making In simple terms: The bot automatically places buy orders LOWER and sell orders HIGHER, earning from the difference (spread) > What the bot does: 1. Analyzes the market: - Checks current prices - Calculates optimal spread - Determines order size 2. Places orders 3. Waits for execution 4. Earns from the spread > Repeats the cycle: - Constantly updates orders - Monitors price - Manages position This two markets which I used to market-making:

cryptovcdegen

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this trader turned $11 into $2,900 on a single weather bet on Polymarket in the last 60 days, this wallet has made 1,063 predictions and his PnL ~ $16,000 99% of those trades are strictly on weather markets he hunts for outcomes priced at 0.1¢ to 10¢ some of these bets go to zero, but when they hit, the ROI is astronomical his biggest wins: $11 - > $2900 $102 - > $2800 $4.5 -> $2200 by kepping vast majority of his bet sizes tiny, he can afford to lose 100 times in a row because a single win covers all losses and prints a massive profit setting up the copy-trade via PolyGun now profile:

AshenSoul

13,026 Aufrufe • vor 5 Monaten

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VALIX

17,343 Aufrufe • vor 2 Monaten

I showed my Polymarket latency bot to a quant friend. He quit his job the next week. $800 → $5,000. Pure latency arbitrage. The bot doesn’t predict outcomes. It’s simply 200 milliseconds faster than the market. The formula is simple: P = Σ(ΔOdds × Size) / Latency_gap The bigger the gap, the better the entry. What’s running under the hood: Connected via API to live sports and political data feeds Receives match results and vote counts before they appear on Polymarket Enters using the Kelly criterion milliseconds before the spread closes Exits automatically once the market converges Win rate: 73% Sharpe ratio: 2.24 About 57 trades per hour Every trade exists inside a ~200 millisecond window. Most people analyze charts. The bot analyzes latency. Charts can be misleading. Milliseconds can’t. Copy trades → you were reading this, the bot likely already closed several more positions.

I showed my Polymarket latency bot to a quant friend. He quit his job the next week. $800 → $5,000. Pure latency arbitrage. The bot doesn’t predict outcomes. It’s simply 200 milliseconds faster than the market. The formula is simple: P = Σ(ΔOdds × Size) / Latency_gap The bigger the gap, the better the entry. What’s running under the hood: Connected via API to live sports and political data feeds Receives match results and vote counts before they appear on Polymarket Enters using the Kelly criterion milliseconds before the spread closes Exits automatically once the market converges Win rate: 73% Sharpe ratio: 2.24 About 57 trades per hour Every trade exists inside a ~200 millisecond window. Most people analyze charts. The bot analyzes latency. Charts can be misleading. Milliseconds can’t. Copy trades → you were reading this, the bot likely already closed several more positions.

Discover

43,198 Aufrufe • vor 3 Monaten

training an RL agent to trade polymarket's 15-min crypto markets for fun input: binance order flow + polymarket books (18 features) output: 7 actions (hold, buy/sell × 3 sizes) learns when to trade AND how much to bet -- uses PPO on MLX, trains live, ~34 min cycles

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nikshep

282,558 Aufrufe • vor 6 Monaten

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slash1s

16,078 Aufrufe • vor 2 Monaten

Just shipped scale orders on Pacifica Scale orders are limit orders that allow you to place multiple limit orders in a predetermined range. We made it a bit different: 1. You can drag the price ranges directly on the chart. 2. You can visualize the orders and avg price for that scale order before the orders are placed. 3. We also made scale orders very easy to manage. If you want to cancel a particular scale order - instead of having to cancel them one by one, you can click on open orders -> scale orders to cancel a particular scale order.

Just shipped scale orders on Pacifica Scale orders are limit orders that allow you to place multiple limit orders in a predetermined range. We made it a bit different: 1. You can drag the price ranges directly on the chart. 2. You can visualize the orders and avg price for that scale order before the orders are placed. 3. We also made scale orders very easy to manage. If you want to cancel a particular scale order - instead of having to cancel them one by one, you can click on open orders -> scale orders to cancel a particular scale order.

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This was the single biggest surprise in all my learning about the grooming gangs. They are not GANGS - it's worse than that. Spread this far and wide - and do me a favour: take a sec to follow.

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Andrew Gold

488,871 Aufrufe • vor 1 Jahr

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Amir Odom

42,028 Aufrufe • vor 1 Jahr

Need to identify this one that hit this man in the face with his skateboard! All bets are off when they do this. Spread it around!

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Johnny Midnight ⚡️

339,291 Aufrufe • vor 8 Monaten

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Oracle Boar

40,275 Aufrufe • vor 3 Monaten

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Marlow

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The Daily Profiler

17,803 Aufrufe • vor 6 Monaten

Welcome to the pico world! 🔬 Micro-dispensing at the picoliter scale is incredible when you compare it to everyday numbers: a single raindrop is about 50 microliters, roughly 50 million times larger than a picoliter. Being able to place droplets this small without touching the surface is key for biotech, diagnostics, and micro-electronics, where tiny volumes matter. And at this scale, two basics become critical: → Accuracy = how close you are to the real value. → Precision = how repeatable each droplet is. I could watch it all day long! 🤯 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

Welcome to the pico world! 🔬 Micro-dispensing at the picoliter scale is incredible when you compare it to everyday numbers: a single raindrop is about 50 microliters, roughly 50 million times larger than a picoliter. Being able to place droplets this small without touching the surface is key for biotech, diagnostics, and micro-electronics, where tiny volumes matter. And at this scale, two basics become critical: → Accuracy = how close you are to the real value. → Precision = how repeatable each droplet is. I could watch it all day long! 🤯 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

773,456 Aufrufe • vor 6 Monaten

Welcome to the pico world! 🔬 Micro-dispensing at the picoliter scale is incredible when you compare it to everyday numbers: a single raindrop is about 50 microliters, roughly 50 million times larger than a picoliter. Being able to place droplets this small without touching the surface is key for biotech, diagnostics, and micro-electronics, where tiny volumes matter. And at this scale, two basics become critical: → Accuracy = how close you are to the real value. → Precision = how repeatable each droplet is. I could watch it all day long! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Welcome to the pico world! 🔬 Micro-dispensing at the picoliter scale is incredible when you compare it to everyday numbers: a single raindrop is about 50 microliters, roughly 50 million times larger than a picoliter. Being able to place droplets this small without touching the surface is key for biotech, diagnostics, and micro-electronics, where tiny volumes matter. And at this scale, two basics become critical: → Accuracy = how close you are to the real value. → Precision = how repeatable each droplet is. I could watch it all day long! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

70,912 Aufrufe • vor 5 Monaten