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this bot has a 92% win rate look at how this bot evaluates probability using Black-Scholes and uses the Kelly Criterion to determine position sizes

sopersone

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22,770 Aufrufe • vor 5 Monaten •via X (Twitter)

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The best Polymarket Quant bot for copy trading with a 99.3% win rate The bot doesn't take risks it uses math and statistics to consistently achieve a 99% win probability. Using this approach, it has earned +$805,000 across 29,184 predictions with 99.3% accuracy Here's a breakdown of its algorithm: 1. Price Mispricing Detection δ = actual win probability − implied probability Traders constantly overpay for cheap contracts (0.1–50¢), but the main edge is concentrated in contracts (80–99¢) that's exactly where the bot trades 2. Expected Value (EV) Calculation EV = (P_win × Payout) − (P_loss × Cost) Shows whether a bet is worth placing regardless of the outcome of any single trade 3. Kelly Criterion f* = (p × b − q) / b The most powerful position sizing formula ever discovered for trading and prediction markets Tells the algorithm what percentage of your portfolio to put into each bet to win in the long run His profile: Those who copy traded him have already made $35,000 But those who followed him and used Poly_Parlay made over $100,000 How? By simply mirroring his trades with a multiplier Instead of opening single trades, they added them all to a basket, so the odds multiplied Bot access:

sopersone

15,781 Aufrufe • vor 4 Monaten

every polymarket bot is based on this formula the kelly criterion f = (p - m) / (1 - m) p = your true probability m = current market price simple rule, but it works on distance you think edge is about picking winners but the real game is position sizing here's how it works: bot identifies edge: calculates true probability vs market price example flow: bot sees market at 50c (m), calculates real probability at 60% (p) math is simple: edge / remaining upside (0.60 - 0.50) / (1.00 - 0.50) 0.10 / 0.50 = 0.20 kelly says allocate 20% of current capital bot uses quarter kelly for safety = 5% allocation position opens automatically at optimal size as bankroll grows, position sizes scale up proportionally as bankroll shrinks, positions scale down to preserve capital bots are actually destroying manual traders humans can't make calculations instantly bots can the formula ensures maximum growth without risking ruin position sizing adjusts dynamically to current capital this is the foundation of every serious automated strategy

every polymarket bot is based on this formula the kelly criterion f = (p - m) / (1 - m) p = your true probability m = current market price simple rule, but it works on distance you think edge is about picking winners but the real game is position sizing here's how it works: bot identifies edge: calculates true probability vs market price example flow: bot sees market at 50c (m), calculates real probability at 60% (p) math is simple: edge / remaining upside (0.60 - 0.50) / (1.00 - 0.50) 0.10 / 0.50 = 0.20 kelly says allocate 20% of current capital bot uses quarter kelly for safety = 5% allocation position opens automatically at optimal size as bankroll grows, position sizes scale up proportionally as bankroll shrinks, positions scale down to preserve capital bots are actually destroying manual traders humans can't make calculations instantly bots can the formula ensures maximum growth without risking ruin position sizing adjusts dynamically to current capital this is the foundation of every serious automated strategy

ramper

68,944 Aufrufe • vor 7 Monaten

How to Build and Turn $15k into $1.1M in 20 Days Using Arbitrage Bot Claude Bot scaled a deposit up to $1.1M By trading 5-min and 15-min markets on Polymarket Bot using this strategy: - Mispricing formula - Expected value calculation - Kelly Criterion sizing mispricing found → EV calced → kelly sizing → enter > 25,123 trades > 83.9% win rate > +1.1M profit > Biggest win 33K Check this profile here: Copytrading: If you wish to do the same I have outlined exactly how to create your own bot in my article Which is also where I told the story of how Claude turned $300 into 2.4M in 4 months This week I will write an article “Why your bot isn’t working and how to fix it” So follow and save this post

AdiiX

33,954 Aufrufe • vor 5 Monaten

quant traders before: > Kelly Criterion (position sizing) > Black-Scholes-Merton (options pricing) > Sharpe / Sortino Ratio (risk-adjusted return) > CAPM (expected return) > GARCH models (volatility forecasting) > Markowitz Mean-Variance Optimization (portfolio allocation) > Monte Carlo simulations (risk scenarios) now: all of the above. one AI.

quant traders before: > Kelly Criterion (position sizing) > Black-Scholes-Merton (options pricing) > Sharpe / Sortino Ratio (risk-adjusted return) > CAPM (expected return) > GARCH models (volatility forecasting) > Markowitz Mean-Variance Optimization (portfolio allocation) > Monte Carlo simulations (risk scenarios) now: all of the above. one AI.

sopersone

72,810 Aufrufe • vor 1 Monat

It took me a month of working with Polymarket data to build this bot most bots trade everything mine rejects 80% of markets it doesn't predict btc direction it buys BOTH sides when each gets temporarily cheap > YES at 48c > NO at $45c > pair cost: $93c > one side always pays $1.00 > guaranteed 7c profit per pair but entering every market is how you blow up so the bot runs three filters before every trade > base rate: compares current odds to 2 years of historical data > Kelly criterion: calculates EV, if negative - skips > liquidity and spread: volume below $50k or spread above 3% - skips 60 days live: 847 markets scanned 156 entries 71.4% win rate +$2,847 net profit maKe your predictions -> most people lose money not because they trade badly but because they trade where they shouldn't the bot just learned to say "no"

It took me a month of working with Polymarket data to build this bot most bots trade everything mine rejects 80% of markets it doesn't predict btc direction it buys BOTH sides when each gets temporarily cheap > YES at 48c > NO at $45c > pair cost: $93c > one side always pays $1.00 > guaranteed 7c profit per pair but entering every market is how you blow up so the bot runs three filters before every trade > base rate: compares current odds to 2 years of historical data > Kelly criterion: calculates EV, if negative - skips > liquidity and spread: volume below $50k or spread above 3% - skips 60 days live: 847 markets scanned 156 entries 71.4% win rate +$2,847 net profit maKe your predictions -> most people lose money not because they trade badly but because they trade where they shouldn't the bot just learned to say "no"

sopersone

11,197 Aufrufe • vor 5 Monaten

HOW TO TURN $15K INTO $1.1 MILLION IN JUST 20 DAYS WITH A KILLER ARBITRAGE BOT A sophisticated Claude-powered bot took a starting deposit and scaled it all the way up to $1.1 million. It crushed the 5-minute and 15-min markets on Polymarket using a rock-solid strategy built on: - Mispricing detection formula. - Expected value calculation. - Kelly Criterion position sizing. The flow is simple and deadly effective: mispricing spotted -> EV calculated -> Kelly sizing applied -> position entered. Results speak louder than words: > 25,123 trades executed > 83.9% win rate > +$1.1M pure profit > Biggest single win: $33K 70% win rate, 7 wallets copytrading rn from ~500 monitored, bot never paused, never gambling, just math and profit 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 (so i can DM you)

HOW TO TURN $15K INTO $1.1 MILLION IN JUST 20 DAYS WITH A KILLER ARBITRAGE BOT A sophisticated Claude-powered bot took a starting deposit and scaled it all the way up to $1.1 million. It crushed the 5-minute and 15-min markets on Polymarket using a rock-solid strategy built on: - Mispricing detection formula. - Expected value calculation. - Kelly Criterion position sizing. The flow is simple and deadly effective: mispricing spotted -> EV calculated -> Kelly sizing applied -> position entered. Results speak louder than words: > 25,123 trades executed > 83.9% win rate > +$1.1M pure profit > Biggest single win: $33K 70% win rate, 7 wallets copytrading rn from ~500 monitored, bot never paused, never gambling, just math and profit 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 (so i can DM you)

Marry Evan

12,648 Aufrufe • vor 5 Monaten

This bot made +$21,000 in 3 weeks trading on weather markets! Account: 7,424 trades. +$1,000/day. Strategy: arbitrage on the most probable outcomes. Example: market Highest temperature in Dallas on April 12: > buys 74°F or higher Yes at 64.6¢ for $2,187 > buys 72-73°F Yes at 21.4¢ for $738 > buys 70-71°F Yes at 9.4¢ for $282 The lower the probability, the smaller the position size. Result: the second bet 72-73°F Yes hits and returns +$2,715. Net profit: $2,715 - $2,187 - $282 = +$246 From one cycle! Risks: > if a very low-probability outcome hits (e.g., 1¢) that the bot didn’t bet on > if the bot overallocates to high-probability outcomes and underallocates to low-probability ones, and the low-probability outcome wins To reduce such mistakes, the bot uses the Kelly Criterion. Capital allocation per market is proportional to outcome probability and edge over the market. Simply: > higher probability -> larger bet > lower probability -> smaller bet The expected value (EV) of this strategy is positive. This does not guarantee profit in a single cycle - only over many repetitions. I described this logic in more detail in the article. Save it.

This bot made +$21,000 in 3 weeks trading on weather markets! Account: 7,424 trades. +$1,000/day. Strategy: arbitrage on the most probable outcomes. Example: market Highest temperature in Dallas on April 12: > buys 74°F or higher Yes at 64.6¢ for $2,187 > buys 72-73°F Yes at 21.4¢ for $738 > buys 70-71°F Yes at 9.4¢ for $282 The lower the probability, the smaller the position size. Result: the second bet 72-73°F Yes hits and returns +$2,715. Net profit: $2,715 - $2,187 - $282 = +$246 From one cycle! Risks: > if a very low-probability outcome hits (e.g., 1¢) that the bot didn’t bet on > if the bot overallocates to high-probability outcomes and underallocates to low-probability ones, and the low-probability outcome wins To reduce such mistakes, the bot uses the Kelly Criterion. Capital allocation per market is proportional to outcome probability and edge over the market. Simply: > higher probability -> larger bet > lower probability -> smaller bet The expected value (EV) of this strategy is positive. This does not guarantee profit in a single cycle - only over many repetitions. I described this logic in more detail in the article. Save it.

me_cool_off

15,828 Aufrufe • vor 4 Monaten

THIS GUY CONNECTED A NASA SATELLITE TO CLAUDE AND MADE $7,778 Pointed satellite data at 6 countries, the bot found anomalies on its own and traded geopolitics on Polymarket Dropped the entire bot on GitHub, grab it and run 👇

THIS GUY CONNECTED A NASA SATELLITE TO CLAUDE AND MADE $7,778 Pointed satellite data at 6 countries, the bot found anomalies on its own and traded geopolitics on Polymarket Dropped the entire bot on GitHub, grab it and run 👇

sopersone

20,615 Aufrufe • vor 5 Monaten

HOW TO TURN $15K INTO $1.1 MILLION IN JUST 20 DAYS WITH A KILLER ARBITRAGE BOT A sophisticated Claude-powered bot took a starting deposit and scaled it all the way up to $1.1 million. It crushed the 5-minute and 15-min markets on Polymarket using a rock-solid strategy built on: - Mispricing detection formula. - Expected value calculation. - Kelly Criterion position sizing. The flow is simple and deadly effective: mispricing spotted -> EV calculated -> Kelly sizing applied -> position entered. Results speak louder than words: > 25,123 trades executed > 83.9% win rate > +$1.1M pure profit > Biggest single win: $33K You only need Claude + Device + 1 hour/day. Giving This Free for 24 hours. To get it: 1. Comment What Ever you think about it. ( Mandatory ) 2. Like and Retweet this post 3. Follow me Marry Evan (so i can DM you)

HOW TO TURN $15K INTO $1.1 MILLION IN JUST 20 DAYS WITH A KILLER ARBITRAGE BOT A sophisticated Claude-powered bot took a starting deposit and scaled it all the way up to $1.1 million. It crushed the 5-minute and 15-min markets on Polymarket using a rock-solid strategy built on: - Mispricing detection formula. - Expected value calculation. - Kelly Criterion position sizing. The flow is simple and deadly effective: mispricing spotted -> EV calculated -> Kelly sizing applied -> position entered. Results speak louder than words: > 25,123 trades executed > 83.9% win rate > +$1.1M pure profit > Biggest single win: $33K You only need Claude + Device + 1 hour/day. Giving This Free for 24 hours. To get it: 1. Comment What Ever you think about it. ( Mandatory ) 2. Like and Retweet this post 3. Follow me Marry Evan (so i can DM you)

Marry Evan

19,770 Aufrufe • vor 4 Monaten

This guy built an HFT bot on Polymarket with Claude Result: +$174,125 in 2 months His bot trades 5 and 15-minute crypto Up/Down markets using a directional strategy with a dynamic hedge: 1. Constantly calculates its own probability for Up and Down 2. Buys the side where its model sees an edge 3. When the underlying asset reverses, it doesn’t close the position. Instead, it starts accumulating the opposite outcome This is how the algorithm constantly changes its net exposure inside each market The opposite side is used as a dynamic hedge, while the remaining exposure forms the directional position > Average trade: $14.68 > Trades/active hour: 131 > Win Rate: 52% His Polymarket account: This bot constantly recalculates probabilities and adapts its position to every new market move Using this strategy, it captures a micro edge and steadily grows its capital Save this so you don’t lose it

This guy built an HFT bot on Polymarket with Claude Result: +$174,125 in 2 months His bot trades 5 and 15-minute crypto Up/Down markets using a directional strategy with a dynamic hedge: 1. Constantly calculates its own probability for Up and Down 2. Buys the side where its model sees an edge 3. When the underlying asset reverses, it doesn’t close the position. Instead, it starts accumulating the opposite outcome This is how the algorithm constantly changes its net exposure inside each market The opposite side is used as a dynamic hedge, while the remaining exposure forms the directional position > Average trade: $14.68 > Trades/active hour: 131 > Win Rate: 52% His Polymarket account: This bot constantly recalculates probabilities and adapts its position to every new market move Using this strategy, it captures a micro edge and steadily grows its capital Save this so you don’t lose it

VALIX

27,231 Aufrufe • vor 1 Monat

This guy built a trading bot with Claude and made $537,000 on Polymarket, buying markets for $14.45 His bot combines a hybrid of microstructure scalping, arbitrage, and hedging. It trades short Up/Down markets with limit orders and captures a consistent edge His strategy is simple: > Buys undervalued outcomes relative to his probability model > Builds arbitrage positions when it sees mispricing > Uses the opposite side as a hedge if the price moves against him His Polymarket account: Using this strategy, he gets a 61% win rate and continuously grows his capital

This guy built a trading bot with Claude and made $537,000 on Polymarket, buying markets for $14.45 His bot combines a hybrid of microstructure scalping, arbitrage, and hedging. It trades short Up/Down markets with limit orders and captures a consistent edge His strategy is simple: > Buys undervalued outcomes relative to his probability model > Builds arbitrage positions when it sees mispricing > Uses the opposite side as a hedge if the price moves against him His Polymarket account: Using this strategy, he gets a 61% win rate and continuously grows his capital

VALIX

30,078 Aufrufe • vor 3 Monaten

These bot make $15-50k per month on polymarket bot analyze fights in real-time and place bets before crowd reacts every punch and moment makes a big difference it uses computer vision to analyze the fight detects events and processes at 50 FPS with ~200-400 ms latency predicts outcome before market reacts example: Joshua vs Paul fight bot sees Joshua landing heavy punches while crowd hasn't reacted yet odds unchanged bot immediately buys Joshua win 10-15 seconds later when crowd reacts, it sells bot architecture: - Forecaster - evaluates event probability using visual data - Critic - identifies missed context - Trader - makes buy/sell decisions and position sizing to create such a bot you need access to direct video feed of the fight not TV broadcast, but YOLO v8/v9 for real-time detection OpenCV for video stream processing GPU acceleration is critical for low latency UFC events on Polymarket roughly 8-12 per month with that volume the bot could easily make up to $50k

These bot make $15-50k per month on polymarket bot analyze fights in real-time and place bets before crowd reacts every punch and moment makes a big difference it uses computer vision to analyze the fight detects events and processes at 50 FPS with ~200-400 ms latency predicts outcome before market reacts example: Joshua vs Paul fight bot sees Joshua landing heavy punches while crowd hasn't reacted yet odds unchanged bot immediately buys Joshua win 10-15 seconds later when crowd reacts, it sells bot architecture: - Forecaster - evaluates event probability using visual data - Critic - identifies missed context - Trader - makes buy/sell decisions and position sizing to create such a bot you need access to direct video feed of the fight not TV broadcast, but YOLO v8/v9 for real-time detection OpenCV for video stream processing GPU acceleration is critical for low latency UFC events on Polymarket roughly 8-12 per month with that volume the bot could easily make up to $50k

Archive

76,267 Aufrufe • vor 8 Monaten

HIDDEN PATTERN IN 72M POLYMARKET TRADES PRINTED +$865K ACROSS 29,000 PREDICTION No gambling-pure math, stats, strict sizing. How it works: 1. Mispricing 72M trades show: traders overpay for 0.1¢–50¢ contracts. Real edge lives in 80¢–99¢ where the bot trades most. Formula: δ = actual win rate − implied probability 2. Expected Value Tells if a trade is worth taking, regardless of any single outcome. Formula: EV = (P win × Payout) − (P lose × Cost) 3. Kelly Criterion Decides what % of portfolio to allocate for long-term growth. Formula: f* = (p·b − q) / Mispricing → EV → Kelly → trade. profile: start copy-trading the bot with Ares:

AdiiX

13,179 Aufrufe • vor 4 Monaten

I GAVE A CROW BRAIN $50 AND LET IT TRADE BY ITSELF CROWBRAIN BOT is officially live. It is an autonomous trading bot inspired by the intelligence of one of the smartest birds on the planet. It scans new and trending tokens, analyzes price, volume and liquidity, and then makes its own decision: BUY → open a position SELL → take profit or exit WAIT → skip the trade The first experiment turned $50 into $420 in just five hours, but the algorithm later lost the profit because its risk controls were not strong enough. I fixed the main problems. The bot now takes partial profits, uses a dynamic stop-loss, limits position sizes, pauses after consecutive losses and avoids re-entering after a sharp price increase. The second public experiment starts today. Starting balance: $50 Public wallet: [AD4vTDFY9RfFCdTmLPqzmoo61R6kwqskLk3BHSgXmrbf] No additional deposits and no hidden trades. Every entry, exit, profit and loss will be verifiable directly on-chain. $50. One updated algorithm. Fully public trading. Let’s see whether a digital crow brain can survive the real market.

I GAVE A CROW BRAIN $50 AND LET IT TRADE BY ITSELF CROWBRAIN BOT is officially live. It is an autonomous trading bot inspired by the intelligence of one of the smartest birds on the planet. It scans new and trending tokens, analyzes price, volume and liquidity, and then makes its own decision: BUY → open a position SELL → take profit or exit WAIT → skip the trade The first experiment turned $50 into $420 in just five hours, but the algorithm later lost the profit because its risk controls were not strong enough. I fixed the main problems. The bot now takes partial profits, uses a dynamic stop-loss, limits position sizes, pauses after consecutive losses and avoids re-entering after a sharp price increase. The second public experiment starts today. Starting balance: $50 Public wallet: [AD4vTDFY9RfFCdTmLPqzmoo61R6kwqskLk3BHSgXmrbf] No additional deposits and no hidden trades. Every entry, exit, profit and loss will be verifiable directly on-chain. $50. One updated algorithm. Fully public trading. Let’s see whether a digital crow brain can survive the real market.

sopersone

11,753 Aufrufe • vor 1 Tag

$This AI trading bot helped him turn $50 into $1,960 in 6 hours. It trades 5-minute Polymarket rounds using LMSR + Bayesian pricing, then sizes positions with fractional Kelly.$

This AI trading bot helped him turn $50 into $1,960 in 6 hours. It trades 5-minute Polymarket rounds using LMSR + Bayesian pricing, then sizes positions with fractional Kelly.

0xMarioNawfal

149,766 Aufrufe • vor 7 Monaten

HOW DOES THIS QUANT BOT PRINT $10,561 IN PROFIT PER DAY +$401,307 PnL in one month on Polymarket Only on short crypto “Up or Down” markets On Feb 16, this wallet switched to a market-making style using Bayesian + Kelly + Stoikov pricing rule P(H|D) = P(D|H) · P(H) / P(D) Bayesian is used to update the bot’s internal probability faster than the market updates its odds Wallet using this model: r = s - qγσ²(T - t) - Stoikov is used to manage quoting and inventory risk f = (bp - q) / b* - Kelly is used to size the position This is why an arbitrage bot is not just “buying both sides”. It is a stack of models that mathematically estimates edge, sizes positions, and manages risk in real time This is how these formulas work: $4,508.76 → $11,293.72 (+150.48%) $3,043.75 → $9,212.02 (+202.65%) $6,695.96 → $12,473.57 (+86.28%) Claude tells me: this is the basic set of every arbitrage strategy

HOW DOES THIS QUANT BOT PRINT $10,561 IN PROFIT PER DAY +$401,307 PnL in one month on Polymarket Only on short crypto “Up or Down” markets On Feb 16, this wallet switched to a market-making style using Bayesian + Kelly + Stoikov pricing rule P(H|D) = P(D|H) · P(H) / P(D) Bayesian is used to update the bot’s internal probability faster than the market updates its odds Wallet using this model: r = s - qγσ²(T - t) - Stoikov is used to manage quoting and inventory risk f = (bp - q) / b* - Kelly is used to size the position This is why an arbitrage bot is not just “buying both sides”. It is a stack of models that mathematically estimates edge, sizes positions, and manages risk in real time This is how these formulas work: $4,508.76 → $11,293.72 (+150.48%) $3,043.75 → $9,212.02 (+202.65%) $6,695.96 → $12,473.57 (+86.28%) Claude tells me: this is the basic set of every arbitrage strategy

Daniro

31,829 Aufrufe • vor 5 Monaten

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 Aufrufe • vor 22 Tagen

This trader used Claude to build a Quant Bot and made +$125,724 on Polymarket 14,282 predictions in 96 days with a 52% win rate How is this account bringing in about $1,310 per day? The logic is simple: 1. It runs across short crypto “Up / Down” markets at roughly 6 trades per hour 2. The bot appears to keep recalculating which outcome offers the stronger opportunity instead of treating the opening position as final 3. It can take one side first and wait for the probabilities to move before introducing the opposite outcome, giving it a chance to hedge at a more favorable moment This trader’s Polymarket account: takerner Follow this account and trade on Polymarket through this bot: Most profitable trades: $1,085 → $2,370 (+$1,285 +118.4%) $828 → $2,100 (+$1,271 +153.5%) $534 → $1,750 (+$1,216 +227.5%) The account doesn’t need an extreme win rate to stay profitable. The advantage appears to come from repeatedly changing the position as probabilities move instead of relying on a single entry

This trader used Claude to build a Quant Bot and made +$125,724 on Polymarket 14,282 predictions in 96 days with a 52% win rate How is this account bringing in about $1,310 per day? The logic is simple: 1. It runs across short crypto “Up / Down” markets at roughly 6 trades per hour 2. The bot appears to keep recalculating which outcome offers the stronger opportunity instead of treating the opening position as final 3. It can take one side first and wait for the probabilities to move before introducing the opposite outcome, giving it a chance to hedge at a more favorable moment This trader’s Polymarket account: takerner Follow this account and trade on Polymarket through this bot: Most profitable trades: $1,085 → $2,370 (+$1,285 +118.4%) $828 → $2,100 (+$1,271 +153.5%) $534 → $1,750 (+$1,216 +227.5%) The account doesn’t need an extreme win rate to stay profitable. The advantage appears to come from repeatedly changing the position as probabilities move instead of relying on a single entry

Daniro

50,712 Aufrufe • vor 28 Tagen

This trader used Claude to build a Quant Bot and made +$563,921 on Polymarket 86,044 predictions in 107 days with a 50% win rate How is this account bringing in about $5,270 per day? The logic is simple: 1. It runs through short crypto “Up / Down” markets at about 34 trades per hour 2. The strategy appears to build positions in stages rather than committing to both outcomes at the same moment 3. When probabilities shift, the model can add the other side at a different level, creating either a hedge or a more favorable combined position This trader’s Polymarket account: Most profitable trades: $4,793 → $12,273 (+$7,480 +156.1%) $10,059 → $16,683 (+$6,624 +65.9%) $2,071 → $8,679 (+$6,608 +319.1%) With a win rate sitting at exactly 50%, the performance appears to come from how the bot structures and adjusts each position

This trader used Claude to build a Quant Bot and made +$563,921 on Polymarket 86,044 predictions in 107 days with a 50% win rate How is this account bringing in about $5,270 per day? The logic is simple: 1. It runs through short crypto “Up / Down” markets at about 34 trades per hour 2. The strategy appears to build positions in stages rather than committing to both outcomes at the same moment 3. When probabilities shift, the model can add the other side at a different level, creating either a hedge or a more favorable combined position This trader’s Polymarket account: Most profitable trades: $4,793 → $12,273 (+$7,480 +156.1%) $10,059 → $16,683 (+$6,624 +65.9%) $2,071 → $8,679 (+$6,608 +319.1%) With a win rate sitting at exactly 50%, the performance appears to come from how the bot structures and adjusts each position

Daniro

45,132 Aufrufe • vor 1 Monat

HOW DOES THIS QUANT BOT PRINT $21,389 IN PROFIT PER DAY +$363,618 PnL in 17 days on Polymarket Only on short crypto “Up / Down” markets On Mar 15, this wallet switched to a high-frequency market-making style using Bayesian + Stoikov pricing rule P(H|D) = P(D|H) · P(H) / P(D) Bayesian lets the bot update its internal probability before the market fully reprices the odds This Quant Bot's wallet: Trader funded this account with $14,827 and now sits at roughly 24.5x on deposit (+2,452% ROI) f = (bp - q) / b* - Kelly determines how large the position should be r = s - qγσ²(T - t) - Stoikov handles quote placement and inventory risk An arbitrage bot is not just buying both sides. It is a mathematical engine that detects mispricing, sizes the trade, and controls risk in real time This is what that looks like in practice: $17,839 → $36,318 (+103.58%) $3,112 → $15,011 (+382.22%) $10,676 → $22,178 (+107.74%) The core logic is simple: YES + NO < 100¢

HOW DOES THIS QUANT BOT PRINT $21,389 IN PROFIT PER DAY +$363,618 PnL in 17 days on Polymarket Only on short crypto “Up / Down” markets On Mar 15, this wallet switched to a high-frequency market-making style using Bayesian + Stoikov pricing rule P(H|D) = P(D|H) · P(H) / P(D) Bayesian lets the bot update its internal probability before the market fully reprices the odds This Quant Bot's wallet: Trader funded this account with $14,827 and now sits at roughly 24.5x on deposit (+2,452% ROI) f = (bp - q) / b* - Kelly determines how large the position should be r = s - qγσ²(T - t) - Stoikov handles quote placement and inventory risk An arbitrage bot is not just buying both sides. It is a mathematical engine that detects mispricing, sizes the trade, and controls risk in real time This is what that looks like in practice: $17,839 → $36,318 (+103.58%) $3,112 → $15,011 (+382.22%) $10,676 → $22,178 (+107.74%) The core logic is simple: YES + NO < 100¢

Daniro

46,114 Aufrufe • vor 5 Monaten