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This guy used Claude Fable 5.1 to build a Quant Vortex Structure system and it made $3,475 a day on Polymarket The result is already +$319,684.59 PnL in 92 days with about $30.58 per average trade, repeating the same setup about 131.02 times per active hour across BTC Up/Down...

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VALIX

12,839 subscribers

40,787 просмотров • 6 дней назад •via X (Twitter)

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Комментарии: 15

Фото профиля Daniro
Daniro6 дней назад

You can build a trading system using Grok Bot agents, with each agent responsible for its own specific calculation base

Фото профиля VALIX
VALIX6 дней назад

The key is to give everyone the right roles and tasks

Фото профиля WallStreetX
WallStreetX5 дней назад

You can build a trading system using Grok Bot agents

Фото профиля no0x
no0x6 дней назад

Insane results! Claude-built Vortex system crushing it on Polymarket

Фото профиля VALIX
VALIX6 дней назад

The system is delivering really strong results. But there are plenty of other systems on Polymarket that perform even better. I’ll cover them soon

Фото профиля Andre Innovateur
Andre Innovateur6 дней назад

Amazing returns, beautiful dashboard, no drawdowns, no audit trail. In my line of work we call that a phishing landing page with formulas on it.

Фото профиля Holy Poly
Holy Poly6 дней назад

The dual-agent setup on Polymarket Up/Down is interesting. What’s the biggest consecutive loss streak the system has taken so far?

Фото профиля zaya
zaya6 дней назад

chop index and vortex combination actually prints

Фото профиля 离岸工具包🎒
离岸工具包🎒5 дней назад

Building a quant system with Claude Fable 5.1 is like having a secret weapon. But let's not forget, the real magic is in the strategy, not just the tool.

Фото профиля Budless
Budless6 дней назад

“131 trades an hour is the part that caught my attention. But how much of that 92-day performance is actually repeatablewhen market conditions change?”

Фото профиля CoinTalk Daily
CoinTalk Daily5 дней назад

This is insane

Фото профиля PulseAi
PulseAi5 дней назад

Interesting combo: Vortex for direction, CHOP as a regime filter. Curious about the details: what window n and CHOP threshold? And at ~131 trades/hour, how much of the edge survives spread and fees on the Up/Down books? Would love to see win rate vs. avg entry price.

Фото профиля kelv
kelv6 дней назад

This is insane

Фото профиля VALIX
VALIX6 дней назад

Thanks for your feedback. Cool, that you like it

Фото профиля V1b3
V1b36 дней назад

131 trades per hour with Vortex and CHOP? Nah. That's a latency bot beating Polymarket odds, not candle math. You have zero idea what code he runs, you just know your ?via= link pays you when we click it

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79,354 просмотров • 1 месяц назад

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11,969 просмотров • 29 дней назад

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This guy used Grok Bot to build a Quant Trend system and it made $1,519 a day on Polymarket The result is already +$268,805 PnL in 177 days with about $173 per average trade, repeating the same setup 27 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Aroon detects whether BTC is repeatedly making fresh highs or lows The bot measures how recently the strongest high and low appeared: Aroon Up = 100 × (N - Periods Since High) / N Aroon Down = 100 × (N - Periods Since Low) / N Then: Aroon Up > Aroon Down → Up bias Aroon Down > Aroon Up → Down bias A fresh high pushes Aroon Up toward 100 A fresh low does the same for Aroon Down 2. The Aroon Oscillator measures how dominant that trend actually is The system combines both readings: Aroon Oscillator = Aroon Up - Aroon Down Then: Strong positive value → stronger Up signal Strong negative value → stronger Down signal When both sides stay close together, the move has no clear control and the setup is ignored This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: PBot-6 Most profitable trades: $2,796 → $6,360 (+$3,564) $1,630 → $3,989 (+$2,359) $1,300 → $3,602 (+$2,302) The system uses Aroon to identify the active trend and the oscillator to measure how strongly one side controls it

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71,924 просмотров • 26 дней назад

This guy used Grok Bot to build a Quant ROC system and it made $2,847 a day on Polymarket The result is already +$418,551 PnL in 147 days with about $261 per average trade, repeating the same setup 27 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. ROC measures how fast BTC is moving and in which direction The bot compares the current BTC level with where it was a few moments earlier: ROC = (Sₜ - Sₜ₋ₙ) / Sₜ₋ₙ × 100 Where: Sₜ = current BTC level Sₜ₋ₙ = BTC level at the start of the window Strong positive ROC → stronger Up signal Strong negative ROC → stronger Down signal The larger the absolute ROC, the stronger the short-term move 2. ATR checks whether that move is actually large for current volatility The system then measures the normal trading range: TR = max(H - L, |H - Cprev|, |L - Cprev|) ATR = Average(TR) A signal matters only when the BTC move is large enough relative to ATR: |Move| > k × ATR This stops the bot from treating ordinary noise as momentum when volatility is already high This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: almach Most profitable trades: $860 → $3,000 (+$2,140) $618 → $2,566 (+$1,948) $1,344 → $3,131 (+$1,786) The system uses ROC to detect short-term momentum and ATR to determine whether that move is significant enough to act on
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This guy used Grok Bot to build a Quant ROC system and it made $2,847 a day on Polymarket The result is already +$418,551 PnL in 147 days with about $261 per average trade, repeating the same setup 27 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. ROC measures how fast BTC is moving and in which direction The bot compares the current BTC level with where it was a few moments earlier: ROC = (Sₜ - Sₜ₋ₙ) / Sₜ₋ₙ × 100 Where: Sₜ = current BTC level Sₜ₋ₙ = BTC level at the start of the window Strong positive ROC → stronger Up signal Strong negative ROC → stronger Down signal The larger the absolute ROC, the stronger the short-term move 2. ATR checks whether that move is actually large for current volatility The system then measures the normal trading range: TR = max(H - L, |H - Cprev|, |L - Cprev|) ATR = Average(TR) A signal matters only when the BTC move is large enough relative to ATR: |Move| > k × ATR This stops the bot from treating ordinary noise as momentum when volatility is already high This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: almach Most profitable trades: $860 → $3,000 (+$2,140) $618 → $2,566 (+$1,948) $1,344 → $3,131 (+$1,786) The system uses ROC to detect short-term momentum and ATR to determine whether that move is significant enough to act on

Daniro

50,114 просмотров • 28 дней назад

This guy used Grok Bot to build a Quant Cloud system and it made $3,985 a day on Polymarket The result is already +$530,025 PnL in 133 days with about $261 per average trade, repeating the same setup roughly 33 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Ichimoku detects when short-term BTC momentum changes direction The bot calculates two moving reference lines: Tenkan = (9-Period High + 9-Period Low) / 2 Kijun = (26-Period High + 26-Period Low) / 2 Then: Tenkan crosses above Kijun → Up signal Tenkan crosses below Kijun → Down signal This identifies shifts in short-term direction without relying on a single BTC movement 2. The Ichimoku Cloud confirms whether that direction has enough support The system calculates two projected boundaries: Span A = (Tenkan + Kijun) / 2 Span B = (52-Period High + 52-Period Low) / 2 Both spans are projected 26 periods forward to form the cloud BTC above the cloud + bullish crossover → stronger Up signal BTC below the cloud + bearish crossover → stronger Down signal If BTC remains inside the cloud, the bot treats the directional signal as less reliable This trader’s Polymarket account: Most profitable trades: $392 → $2,746 (+$2,354) $587 → $2,609 (+$2,022) $1,656 → $3,531 (+$1,875) The system uses the Ichimoku crossover to identify momentum and the cloud to confirm the current market direction
0:25

This guy used Grok Bot to build a Quant Cloud system and it made $3,985 a day on Polymarket The result is already +$530,025 PnL in 133 days with about $261 per average trade, repeating the same setup roughly 33 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Ichimoku detects when short-term BTC momentum changes direction The bot calculates two moving reference lines: Tenkan = (9-Period High + 9-Period Low) / 2 Kijun = (26-Period High + 26-Period Low) / 2 Then: Tenkan crosses above Kijun → Up signal Tenkan crosses below Kijun → Down signal This identifies shifts in short-term direction without relying on a single BTC movement 2. The Ichimoku Cloud confirms whether that direction has enough support The system calculates two projected boundaries: Span A = (Tenkan + Kijun) / 2 Span B = (52-Period High + 52-Period Low) / 2 Both spans are projected 26 periods forward to form the cloud BTC above the cloud + bullish crossover → stronger Up signal BTC below the cloud + bearish crossover → stronger Down signal If BTC remains inside the cloud, the bot treats the directional signal as less reliable This trader’s Polymarket account: Most profitable trades: $392 → $2,746 (+$2,354) $587 → $2,609 (+$2,022) $1,656 → $3,531 (+$1,875) The system uses the Ichimoku crossover to identify momentum and the cloud to confirm the current market direction

Daniro

10,995 просмотров • 14 дней назад

This guy used Grok Bot to build a Quant Reversal system and it made $1,364 a day on Polymarket The result is already +$21,826 PnL in 16 days with about $190 per average trade, repeating the same setup roughly 37 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Williams %R shows when BTC reaches an extreme inside its recent range The bot calculates: %R = (Highest High - Close) / (Highest High - Lowest Low) × -100 Then: %R near 0 → BTC is near the top of the range %R near -100 → BTC is near the bottom This lets the system identify moments when the short-term move has stretched unusually far in one direction 2. Momentum confirms whether BTC is actually turning away from that extreme The system compares the current level with an earlier one: Momentum = Sₜ - Sₜ₋ₙ For example: %R below -80 + Momentum turning positive → stronger Up reversal %R above -20 + Momentum turning negative → stronger Down reversal The bot therefore does not react to an extreme reading alone It waits until momentum begins moving away from that extreme This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: blue.birds Most profitable trades: $128 → $1,010 (+$883) $150 → $757 (+$607) $116 → $718 (+$602) The system uses Williams %R to locate the extreme and Momentum to confirm that the reversal has actually started
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This guy used Grok Bot to build a Quant Reversal system and it made $1,364 a day on Polymarket The result is already +$21,826 PnL in 16 days with about $190 per average trade, repeating the same setup roughly 37 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Williams %R shows when BTC reaches an extreme inside its recent range The bot calculates: %R = (Highest High - Close) / (Highest High - Lowest Low) × -100 Then: %R near 0 → BTC is near the top of the range %R near -100 → BTC is near the bottom This lets the system identify moments when the short-term move has stretched unusually far in one direction 2. Momentum confirms whether BTC is actually turning away from that extreme The system compares the current level with an earlier one: Momentum = Sₜ - Sₜ₋ₙ For example: %R below -80 + Momentum turning positive → stronger Up reversal %R above -20 + Momentum turning negative → stronger Down reversal The bot therefore does not react to an extreme reading alone It waits until momentum begins moving away from that extreme This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: blue.birds Most profitable trades: $128 → $1,010 (+$883) $150 → $757 (+$607) $116 → $718 (+$602) The system uses Williams %R to locate the extreme and Momentum to confirm that the reversal has actually started

Daniro

17,555 просмотров • 24 дней назад

This guy used Grok Bot to build a Quant MACD system and it made $1,891 a day on Polymarket The result is already +$304,411 PnL in 161 days with about $105 per average trade, repeating the same setup 39 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. MACD identifies changes in short term momentum MACD = EMA(12) - EMA(26) When the faster EMA moves above the slower EMA, momentum is shifting Up When it moves below, momentum is shifting Down The system uses the crossover to identify when direction is beginning to change rather than reacting to every price tick 2. Signal Line confirms whether that momentum shift is strong enough The Signal Line is a moving average of MACD itself: Signal Line = 9-period average of MACD The bot compares the two: MACD > Signal Line → Up confirmation MACD < Signal Line → Down confirmation The wider the gap between them becomes, the stronger the current momentum signal This trader’s Polymarket account: Most profitable trades: $535 → $2,860 (+$2,325) $632 → $2,896 (+$2,264) $685 → $2,602 (+$1,916) The system uses MACD to detect direction and volume to confirm whether that move is strong enough to trade
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This guy used Grok Bot to build a Quant MACD system and it made $1,891 a day on Polymarket The result is already +$304,411 PnL in 161 days with about $105 per average trade, repeating the same setup 39 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. MACD identifies changes in short term momentum MACD = EMA(12) - EMA(26) When the faster EMA moves above the slower EMA, momentum is shifting Up When it moves below, momentum is shifting Down The system uses the crossover to identify when direction is beginning to change rather than reacting to every price tick 2. Signal Line confirms whether that momentum shift is strong enough The Signal Line is a moving average of MACD itself: Signal Line = 9-period average of MACD The bot compares the two: MACD > Signal Line → Up confirmation MACD < Signal Line → Down confirmation The wider the gap between them becomes, the stronger the current momentum signal This trader’s Polymarket account: Most profitable trades: $535 → $2,860 (+$2,325) $632 → $2,896 (+$2,264) $685 → $2,602 (+$1,916) The system uses MACD to detect direction and volume to confirm whether that move is strong enough to trade

Daniro

18,125 просмотров • 1 месяц назад

This guy used Grok Bot to build a Quant Acceleration system and it made $2,304 a day on Polymarket The result is already +$59,915 PnL in 26 days with about $358 per average trade, repeating the same setup roughly 24 times every active hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Awesome Oscillator measures the momentum behind BTC movement Instead of reacting to individual ticks, the bot compares two moving averages of BTC's median level: Median = (High + Low) / 2 AO = SMA(Median, 5) - SMA(Median, 34) Then: AO above zero → Up momentum A rising AO indicates increasing upward momentum, while a falling AO indicates increasing downward momentum 2. Accelerator Oscillator detects whether that momentum is getting stronger or weaker The system calculates: AC = AO - SMA(AO, 5) Then: AO positive + AC rising → stronger Up signal - The bot therefore looks at both the current momentum and how quickly that momentum is changing - If acceleration weakens, the algorithm becomes more selective even before the underlying direction reverses This trader’s Polymarket account: Most profitable trades: $677 → $1,669 (+$992) $671 → $1,639 (+$967) $479 → $1,439 (+$960) The system uses Awesome Oscillator to identify BTC momentum and Accelerator Oscillator to detect whether the move is gaining or losing strength
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This guy used Grok Bot to build a Quant Acceleration system and it made $2,304 a day on Polymarket The result is already +$59,915 PnL in 26 days with about $358 per average trade, repeating the same setup roughly 24 times every active hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Awesome Oscillator measures the momentum behind BTC movement Instead of reacting to individual ticks, the bot compares two moving averages of BTC's median level: Median = (High + Low) / 2 AO = SMA(Median, 5) - SMA(Median, 34) Then: AO above zero → Up momentum A rising AO indicates increasing upward momentum, while a falling AO indicates increasing downward momentum 2. Accelerator Oscillator detects whether that momentum is getting stronger or weaker The system calculates: AC = AO - SMA(AO, 5) Then: AO positive + AC rising → stronger Up signal - The bot therefore looks at both the current momentum and how quickly that momentum is changing - If acceleration weakens, the algorithm becomes more selective even before the underlying direction reverses This trader’s Polymarket account: Most profitable trades: $677 → $1,669 (+$992) $671 → $1,639 (+$967) $479 → $1,439 (+$960) The system uses Awesome Oscillator to identify BTC momentum and Accelerator Oscillator to detect whether the move is gaining or losing strength

Daniro

31,968 просмотров • 3 дней назад

This guy built a Quant Resolution model and it made $2,191 a day on Polymarket The result is already +$363,748 PnL in 166 days with only $38 per average trade, repeating the same setup 10 times every hour across BTC “Up or Down” markets Several AI agents can split the workflow between probability, sizing and execution: 1. The model measures how far BTC is from the reference price A simplified version looks like: z = (S - K) / (σ√T) Where: S = current BTC price K = reference price σ = volatility T = time left That z-score is converted into the probability of BTC finishing Up or Down 2. It trades the gap between model probability and Polymarket Model Up = 64% Market Up = 54¢ Edge = 10¢ If the gap is large enough, the system enters As the market catches up to the model estimate, the edge disappears This trader’s Polymarket account: powerwinner Follow this account and trade on Polymarket through this bot: 41,268 predictions with a 51% win rate Most profitable trades: $683 → $3,420 (+$2,737) $396 → $3,040 (+$2,644) $531 → $3,040 (+$2,509) A setup like this can be coordinated with Grok Bot, while external feeds provide live BTC data and execution
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This guy built a Quant Resolution model and it made $2,191 a day on Polymarket The result is already +$363,748 PnL in 166 days with only $38 per average trade, repeating the same setup 10 times every hour across BTC “Up or Down” markets Several AI agents can split the workflow between probability, sizing and execution: 1. The model measures how far BTC is from the reference price A simplified version looks like: z = (S - K) / (σ√T) Where: S = current BTC price K = reference price σ = volatility T = time left That z-score is converted into the probability of BTC finishing Up or Down 2. It trades the gap between model probability and Polymarket Model Up = 64% Market Up = 54¢ Edge = 10¢ If the gap is large enough, the system enters As the market catches up to the model estimate, the edge disappears This trader’s Polymarket account: powerwinner Follow this account and trade on Polymarket through this bot: 41,268 predictions with a 51% win rate Most profitable trades: $683 → $3,420 (+$2,737) $396 → $3,040 (+$2,644) $531 → $3,040 (+$2,509) A setup like this can be coordinated with Grok Bot, while external feeds provide live BTC data and execution

Daniro

11,565 просмотров • 2 месяцев назад

understanding how higher timeframe candles form on lower timeframes is one of the most useful skills in trading every candle has a few possible outcomes: it can stay inside the previous range, break higher, or break lower once i have a directional bias, i use lower timeframes to understand how that candle is developing and look for entries before the higher timeframe candle closes a daily candle with a long lower wick, for example, tells you price traded lower before buyers pushed it back up learning to recognize these patterns as they develop gives you a much better understanding of price action and where to position
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understanding how higher timeframe candles form on lower timeframes is one of the most useful skills in trading every candle has a few possible outcomes: it can stay inside the previous range, break higher, or break lower once i have a directional bias, i use lower timeframes to understand how that candle is developing and look for entries before the higher timeframe candle closes a daily candle with a long lower wick, for example, tells you price traded lower before buyers pushed it back up learning to recognize these patterns as they develop gives you a much better understanding of price action and where to position

Ansem 🐂🀄️

94,479 просмотров • 11 дней назад

This guy used Grok Bot to build a Quant Pivot system and it made $1,075 a day on Polymarket The result is already +$82,803 PnL in 77 days with about $205 per market traded, repeating the same setup roughly 21 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Pivot Points calculate the key BTC levels for the next move The bot uses the previous interval’s high, low and close: Pivot = (High + Low + Close) / 3 Resistance = 2 × Pivot - Low Support = 2 × Pivot - High Above resistance → potential Up breakout Below support → potential Down breakout This gives the system fixed levels to monitor rather than reacting to random movement 2. Relative Volume confirms whether the breakout has enough participation The bot compares the latest activity with its recent baseline: RVOL = Current Volume / Average Volume RVOL > 1 → activity above normal RVOL < 1 → activity below normal Above resistance + strong RVOL → stronger Up signal Below support + strong RVOL → stronger Down signal The system ignores weaker breakouts that lack sufficient participation This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: rabadabadoo Most profitable trades: $1,226 → $2,042 (+$816) $296 → $1,092 (+$795) $1,257 → $2,004 (+$747) The bot uses Pivot Points to identify meaningful BTC levels and Relative Volume to confirm whether the movement through them is supported by real activity
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This guy used Grok Bot to build a Quant Pivot system and it made $1,075 a day on Polymarket The result is already +$82,803 PnL in 77 days with about $205 per market traded, repeating the same setup roughly 21 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. Pivot Points calculate the key BTC levels for the next move The bot uses the previous interval’s high, low and close: Pivot = (High + Low + Close) / 3 Resistance = 2 × Pivot - Low Support = 2 × Pivot - High Above resistance → potential Up breakout Below support → potential Down breakout This gives the system fixed levels to monitor rather than reacting to random movement 2. Relative Volume confirms whether the breakout has enough participation The bot compares the latest activity with its recent baseline: RVOL = Current Volume / Average Volume RVOL > 1 → activity above normal RVOL < 1 → activity below normal Above resistance + strong RVOL → stronger Up signal Below support + strong RVOL → stronger Down signal The system ignores weaker breakouts that lack sufficient participation This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: rabadabadoo Most profitable trades: $1,226 → $2,042 (+$816) $296 → $1,092 (+$795) $1,257 → $2,004 (+$747) The bot uses Pivot Points to identify meaningful BTC levels and Relative Volume to confirm whether the movement through them is supported by real activity

Daniro

14,512 просмотров • 23 дней назад

This guy used Grok Bot to build a Quant Z-Score system and it made $4,654 a day on Polymarket The result is already +$525,853 PnL in 113 days with about $1,142 per average trade, repeating the same setup 11 times every hour across BTC "Up or Down" markets Multiple AI agents work together as one algorithm: 1. Z-Score measures how unusual the current move is The bot tracks short term BTC returns and compares the latest move with recent price behavior Z = (r - μ) / σ Where: r = latest BTC return μ = average return over the recent window σ = standard deviation of those returns A large positive or negative Z tells the bot that the latest move is unusually strong relative to recent volatility It uses this as an entry filter and ignores moves that stay inside the normal range 2. Expected Value determines whether the setup is worth taking EV = P(win) × Payout - Entry Cost Positive EV means the estimated payout still exceeds the cost of taking the position As the price changes, the agents recalculate EV and stop adding once the advantage disappears Most profitable trades: $4,588 → $7,905 (+$3,316) $1,578 → $4,811 (+$3,233) $2,216 → $5,305 (+$3,090) The system uses Z-Score to filter the signal and Kelly Criterion to control how much exposure each setup receives
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This guy used Grok Bot to build a Quant Z-Score system and it made $4,654 a day on Polymarket The result is already +$525,853 PnL in 113 days with about $1,142 per average trade, repeating the same setup 11 times every hour across BTC "Up or Down" markets Multiple AI agents work together as one algorithm: 1. Z-Score measures how unusual the current move is The bot tracks short term BTC returns and compares the latest move with recent price behavior Z = (r - μ) / σ Where: r = latest BTC return μ = average return over the recent window σ = standard deviation of those returns A large positive or negative Z tells the bot that the latest move is unusually strong relative to recent volatility It uses this as an entry filter and ignores moves that stay inside the normal range 2. Expected Value determines whether the setup is worth taking EV = P(win) × Payout - Entry Cost Positive EV means the estimated payout still exceeds the cost of taking the position As the price changes, the agents recalculate EV and stop adding once the advantage disappears Most profitable trades: $4,588 → $7,905 (+$3,316) $1,578 → $4,811 (+$3,233) $2,216 → $5,305 (+$3,090) The system uses Z-Score to filter the signal and Kelly Criterion to control how much exposure each setup receives

Daniro

28,613 просмотров • 1 месяц назад

This guy used Claude Fable 5.1 to build a Quant Kalman Repricing system and it made $3,634 a day on Polymarket The result is already +$697,712.09 PnL in 192 days with about $51.10 per average trade, repeating the same setup about 88.2 times per active hour across BTC Up/Down markets Several AI agents work together as one algorithm: 1. Kalman Filter updates fair value while accounting for uncertainty in new data The first agent receives an initial Up valuation based on external BTC data, the reference price, volatility, and time remaining Then updates it: Kₜ = P⁻ₜ / (P⁻ₜ + R) F_Up,ₜ = F_Up,ₜ₋₁ + Kₜ × (zₜ − F_Up,ₜ₋₁) Where: > zₜ = new input estimate of Up’s value > P⁻ₜ = uncertainty in the estimate before the update > R = observation noise variance For the other side: F_Down = $1 − F_Up A directional residual is retained on the side whose fair value exceeds its full purchase cost 2. Ornstein-Uhlenbeck models intramarket repricing The second agent tracks the gap between the market quote and fair value: Dₜ = Mid_Up,ₜ − F_Up,ₜ During periods with stable fair value, the model describes how that gap tends to move toward zero: E[Dₜ₊ₕ | Dₜ] = Dₜ × e^(−κh) Where: > κ = estimated speed of mean reversion > h = the interval being considered After buying Up below fair value, a higher Up quote may be accompanied by a lower Down quote The model helps select the timing and price for adding the opposite side His Polymarket account: Top trades: $329.56 → $5,791.59 (+$5,462.03) $2,948.36 → $7,331.82 (+$4,383.46) $910.43 → $4,756.53 (+$3,846.10) Kalman estimates fair value for the directional residual, while Ornstein-Uhlenbeck models repricing to guide opposite-side entries and build complete sets for less than $1
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This guy used Claude Fable 5.1 to build a Quant Kalman Repricing system and it made $3,634 a day on Polymarket The result is already +$697,712.09 PnL in 192 days with about $51.10 per average trade, repeating the same setup about 88.2 times per active hour across BTC Up/Down markets Several AI agents work together as one algorithm: 1. Kalman Filter updates fair value while accounting for uncertainty in new data The first agent receives an initial Up valuation based on external BTC data, the reference price, volatility, and time remaining Then updates it: Kₜ = P⁻ₜ / (P⁻ₜ + R) F_Up,ₜ = F_Up,ₜ₋₁ + Kₜ × (zₜ − F_Up,ₜ₋₁) Where: > zₜ = new input estimate of Up’s value > P⁻ₜ = uncertainty in the estimate before the update > R = observation noise variance For the other side: F_Down = $1 − F_Up A directional residual is retained on the side whose fair value exceeds its full purchase cost 2. Ornstein-Uhlenbeck models intramarket repricing The second agent tracks the gap between the market quote and fair value: Dₜ = Mid_Up,ₜ − F_Up,ₜ During periods with stable fair value, the model describes how that gap tends to move toward zero: E[Dₜ₊ₕ | Dₜ] = Dₜ × e^(−κh) Where: > κ = estimated speed of mean reversion > h = the interval being considered After buying Up below fair value, a higher Up quote may be accompanied by a lower Down quote The model helps select the timing and price for adding the opposite side His Polymarket account: Top trades: $329.56 → $5,791.59 (+$5,462.03) $2,948.36 → $7,331.82 (+$4,383.46) $910.43 → $4,756.53 (+$3,846.10) Kalman estimates fair value for the directional residual, while Ornstein-Uhlenbeck models repricing to guide opposite-side entries and build complete sets for less than $1

VALIX

32,528 просмотров • 4 дней назад

This guy used Grok Bot to build an asynchronous arbitrage system on Polymarket Result: +$1,340,486 It makes 340 trades per active hour in crypto Up/Down markets, combining market making, pairing, and a directional residual Several Grok Bot AI agents work together as one algorithm, making $7,406 per day: 1. Buys Up and Down at different times It places BUY limit orders on both sides of the market in advance and waits for temporary price dislocations The goal is: Avg Up price + Avg Down price Up price + fees → BUY Up This trader’s Polymarket account: The system’s main edge comes from combining asynchronous pairing with short-term repricing: > It buys each side at different points as the market moves > Locks in an edge on low-cost Up + Down pairs > Keeps additional directional exposure where its model identifies mispricing
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This guy used Grok Bot to build an asynchronous arbitrage system on Polymarket Result: +$1,340,486 It makes 340 trades per active hour in crypto Up/Down markets, combining market making, pairing, and a directional residual Several Grok Bot AI agents work together as one algorithm, making $7,406 per day: 1. Buys Up and Down at different times It places BUY limit orders on both sides of the market in advance and waits for temporary price dislocations The goal is: Avg Up price + Avg Down price Up price + fees → BUY Up This trader’s Polymarket account: The system’s main edge comes from combining asynchronous pairing with short-term repricing: > It buys each side at different points as the market moves > Locks in an edge on low-cost Up + Down pairs > Keeps additional directional exposure where its model identifies mispricing

VALIX

11,581 просмотров • 16 дней назад

This guy used Grok Bot to build a Quant Momentum system and it made $1,943 a day on Polymarket The result is already +$178,739 PnL in 92 days with about $451 per average trade, repeating the same setup roughly 10 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. CCI measures how far the current BTC move has stretched from its recent baseline The bot calculates: CCI = (Typical Level - SMA) / (0.015 × Mean Deviation) Then: CCI > 0 → Up momentum CCI < 0 → Down momentum The further CCI moves from zero, the stronger the current directional pressure 2. Momentum confirms whether that move is still accelerating The system compares the current BTC level with an earlier point: Momentum = Sₜ - Sₜ₋ₙ Then: CCI positive + Momentum rising → stronger Up signal CCI negative + Momentum falling → stronger Down signal This lets the bot ignore stretched moves that have already started losing force This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: GoodFallen Most profitable trades: $707 → $2,490 (+$1,782) $974 → $2,525 (+$1,551) $665 → $2,023 (+$1,357) The system uses CCI to detect directional pressure and Momentum to confirm that the move is still accelerating
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This guy used Grok Bot to build a Quant Momentum system and it made $1,943 a day on Polymarket The result is already +$178,739 PnL in 92 days with about $451 per average trade, repeating the same setup roughly 10 times every hour across BTC "Up or Down" markets Several AI agents work together as one algorithm: 1. CCI measures how far the current BTC move has stretched from its recent baseline The bot calculates: CCI = (Typical Level - SMA) / (0.015 × Mean Deviation) Then: CCI > 0 → Up momentum CCI < 0 → Down momentum The further CCI moves from zero, the stronger the current directional pressure 2. Momentum confirms whether that move is still accelerating The system compares the current BTC level with an earlier point: Momentum = Sₜ - Sₜ₋ₙ Then: CCI positive + Momentum rising → stronger Up signal CCI negative + Momentum falling → stronger Down signal This lets the bot ignore stretched moves that have already started losing force This is the first agent that will create a trading bot strategy for you and then build it: This trader’s Polymarket account: GoodFallen Most profitable trades: $707 → $2,490 (+$1,782) $974 → $2,525 (+$1,551) $665 → $2,023 (+$1,357) The system uses CCI to detect directional pressure and Momentum to confirm that the move is still accelerating

Daniro

26,305 просмотров • 27 дней назад