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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...

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Daniro

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11,565 görüntüleme • 1 ay önce •via X (Twitter)

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Hussain Hashim | Building SundayBack profil fotoğrafı
Hussain Hashim | Building SundayBack1 ay önce

@Dan1ro0 that's impressive! I hit a wall trying to sync agents for my own thing. Crazy how small tweaks can unlock big gains.

qwinsi profil fotoğrafı
qwinsi1 ay önce

Beautiful terminal

Daniro profil fotoğrafı
Daniro1 ay önce

Thanks bro, I appreciate it. Also, this trader was able to reach a result of over 2k in a day, which is even more impressive

Korens profil fotoğrafı
Korens1 ay önce

The probability gap is where the real edge lies

yap markets profil fotoğrafı
yap markets1 ay önce

38 dollars a trade, ten times an hour, 166 days. that is just showing up

qortex profil fotoğrafı
qortex1 ay önce

Bro, it looks damn hard

Daniro profil fotoğrafı
Daniro1 ay önce

It's really hard because creating a working mathematical model that will consistently show positive results is an incredible amount of work

CHAIN profil fotoğrafı
CHAIN1 ay önce

41k trades and +$363k PnL on pure math and z-scores with zero emotions. This is why I back automation: while humans guess, AI models strip the edge from the market every single minute.

DexorynLabs profil fotoğrafı
DexorynLabs1 ay önce

Quant speed changes the game.

Lyren_o profil fotoğrafı
Lyren_o1 ay önce

the $2k/day is the bait. the actual thing is splitting probability, size and execution so one agent isn’t doing all three.

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This guy built an HFT algorithm on Polymarket with an average trade size of $60 and a 55% win rate Result: +$311,667 His bot trades short-term crypto Up/Down markets using a combination of directional trading and dynamic hedging: 1. Looks for mispricing using its model For each market, it records the reference price and uses fast spot/perp feeds to track the underlying asset Its model continuously recalculates outcome probabilities based on price relative to the reference, momentum, acceleration, volatility, time to resolution, and order flow Its signal looks like this: > Model Edge = p_model(outcome) - PM price For example: > p_model(Up) = 67c > Current Up price = 60c Model Edge = 7c As long as this gap remains, it keeps buying that side 2. Uses the opposite outcome to adjust its inventory If the market reverses and its fair probability estimate shifts toward the other side, it often buys the opposite outcome This reduces net exposure and, at favorable prices, can turn part of the position into complete sets costing less than $1 each Matched inventory acts as a hedge, while the remainder stays directional Its Polymarket account: antsaslyku The algorithm uses external price feeds to continuously update its fair probability estimates. Buying the opposite outcome lets it hedge its inventory while continuing to follow its directional signal

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This guy built a trading bot with Claude and made $193,000 on Polymarket His bot trades the microstructure of short BTC Up / Down markets through limit orders and combines a hybrid of arbitrage, market making, and hedging His strategy is simple: > Enters a position when it sees mispricing > Then buys the opposite outcome, turning part of the trade into a paired arb > The base position is hedged with the pair, while the rest remains as a directional trade This guy’s Polymarket account: Using this strategy, he captures an average edge of 2-3% and repeats it hundreds of times Consistent micro edge + clean execution = lifechange

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This guy built a trading bot on Polymarket with Claude Result: +$143,740 in 3 months His bot trades crypto Up/Down markets using a strategy built around 3 elements: 1. Compares current Polymarket prices with the underlying asset price from external sources 2. Buys the more likely outcome based on his model 3. When market conditions change, hedges the original entry by buying the opposite side His Polymarket username: antsaslyku Using this strategy and clean execution, he captures a consistent edge and repeats it thousands of times That’s how he turned $68k into $143.7k

VALIX

14,753 görüntüleme • 3 ay önce

This guy used Grok Bot to build a repricing system on Polymarket Result: +$207,170 It trades 5 and 15 minute crypto Up/Down markets, combining a fair value model with dynamic hedging Several Grok Bot AI agents work together as one algorithm: 1. Finds undervalued outcomes At the start of each market, it records the reference price S₀ and monitors spot/perp feeds for the underlying asset The model then updates fair value based on how far the price is from S₀, time to resolution, momentum, acceleration, volatility, and order flow Model Edge = p_model(outcome) - market price If the edge is large enough to cover the spread and fees, it starts buying that outcome 2. Adds the opposite outcome to its existing position when the signal reverses As its fair value estimates shift toward the other side, the trading sequence can look like this: Up → Down → Up → Down Buying the opposite outcome reduces net exposure and acts as a dynamic hedge Its Polymarket account: std0 The system’s main edge comes from how fast it updates fair value: > Tries to detect changes in fair value before market prices adjust > Increases exposure as the signal strengthens > Uses the opposite outcome to adjust its position
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This guy used Grok Bot to build a repricing system on Polymarket Result: +$207,170 It trades 5 and 15 minute crypto Up/Down markets, combining a fair value model with dynamic hedging Several Grok Bot AI agents work together as one algorithm: 1. Finds undervalued outcomes At the start of each market, it records the reference price S₀ and monitors spot/perp feeds for the underlying asset The model then updates fair value based on how far the price is from S₀, time to resolution, momentum, acceleration, volatility, and order flow Model Edge = p_model(outcome) - market price If the edge is large enough to cover the spread and fees, it starts buying that outcome 2. Adds the opposite outcome to its existing position when the signal reverses As its fair value estimates shift toward the other side, the trading sequence can look like this: Up → Down → Up → Down Buying the opposite outcome reduces net exposure and acts as a dynamic hedge Its Polymarket account: std0 The system’s main edge comes from how fast it updates fair value: > Tries to detect changes in fair value before market prices adjust > Increases exposure as the signal strengthens > Uses the opposite outcome to adjust its position

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This guy built a trading bot on Polymarket with an average trade size of $8 Result: +$251,218 His bot trades 5 and 15 minute crypto Up/Down markets using a hybrid of directional trading, latency edge, and dynamic hedging: 1. It looks for edge using its own model It tracks momentum, acceleration, order flow imbalance, and spot feeds relative to the reference price of the current market Based on this data, it constantly recalculates its own fair value for Up and Down. It enters a position when it detects mispricing 2. When the signal changes, it quickly adjusts its exposure If momentum reverses, it can reduce the existing side or start accumulating the opposite outcome In 86.2% of markets, it traded both sides. The dynamic hedge constantly adjusts net exposure based on the model’s latest signal It’s Polymarket nickname: nj23adsknml3 Follow this account and trade on Polymarket through this app: It’s stats: > Trades / active hour: 516 > Average trade: $8.13 > Win Rate: 49% The main edge of this guy’s HFT algorithm comes from speed. It tries to detect changes in fair value on external crypto markets before they are reflected in Polymarket prices It then captures the temporary mispricing and quickly adjusts its directional exposure with every new market move

VALIX

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This guy built an HFT algorithm and made +$249,869 on Polymarket His bot trades 5-minute BTC Up/Down markets using a hybrid of passive market making, complete-set accumulation, and directional residual: 1. It uses BTC price movements to build Up + Down positions for less than $1 After the first buy, it waits for the underlying asset to move and then starts accumulating the opposite side For example: > Up = 41c -> some time later Down = 54c > Up + Down = 95c -> 5c gross edge The average cost of its complete sets is 96.73c, which means the average structural edge is around 3.27c 2. It leaves a small directional residual Around 81% of its inventory in 5-minute markets consists of paired Up + Down positions. The remaining 19% stays directional If its fair-value model considers one side undervalued, it doesn’t have to fully hedge it and can keep additional exposure It’s Polymarket nickname: almach Stats: > Trades / active hour: 150 > Average trade: $33.50 > Win Rate: 49% Ultimately, the edge of this guy’s algorithm comes from buying Up and Down at different points during BTC price movements, then turning most of the inventory into complete sets that cost less than $1 It keeps a small remainder directional when it’s own fair probability still shows an edge

VALIX

46,302 görüntüleme • 2 ay önce

This guy built an HFT algorithm on Polymarket with an average trade size of $53 Result: +$129,923 His bot trades short-term BTC/ETH Up/Down markets using a hybrid of two-sided market making, complete-set accumulation, and inventory rebalancing: 1. It accumulates Up and Down at different points during the market It keeps BUY orders on both sides and uses intramarket volatility to get fills at different prices For example: > Up = 47c -> some time later Down = 52c > Up + Down = 99c -> 1c gross edge 2. It leaves a small directional residual After forming complete sets, it keeps some directional exposure when its own fair probability model sees an edge based on: > Underlying asset data from external sources > Order book depth > Momentum, acceleration, and volatility His Polymarket nickname: Polkadot-Frog Follow this account and trade on Polymarket through this bot: The main edge of his HFT algorithm comes from repeating the same cycle over and over again That’s how he captures a consistent edge and steadily grows his capital
0:25

This guy built an HFT algorithm on Polymarket with an average trade size of $53 Result: +$129,923 His bot trades short-term BTC/ETH Up/Down markets using a hybrid of two-sided market making, complete-set accumulation, and inventory rebalancing: 1. It accumulates Up and Down at different points during the market It keeps BUY orders on both sides and uses intramarket volatility to get fills at different prices For example: > Up = 47c -> some time later Down = 52c > Up + Down = 99c -> 1c gross edge 2. It leaves a small directional residual After forming complete sets, it keeps some directional exposure when its own fair probability model sees an edge based on: > Underlying asset data from external sources > Order book depth > Momentum, acceleration, and volatility His Polymarket nickname: Polkadot-Frog Follow this account and trade on Polymarket through this bot: The main edge of his HFT algorithm comes from repeating the same cycle over and over again That’s how he captures a consistent edge and steadily grows his capital

VALIX

69,430 görüntüleme • 2 ay önce

This guy built a trading bot on Polymarket with an average trade size of $9 Result: +$108,248 I analyzed its trades and found that its core strategy is based on dynamically accumulating both outcomes at different points throughout 5 minute BTC Up/Down markets It uses price swings within each market to buy each outcome when it becomes cheaper Here’s what that looks like in practice: > BTC declines sharply > Up falls to 42c, and the bot starts accumulating it > Then BTC rebounds > Down becomes cheaper, and the algorithm buys it at 55c Up + Down = 97c -> 3c edge These paired positions have an average edge of 2.7% But it does not always keep Up and Down perfectly balanced at a 1:1 ratio On top of its paired inventory, the algorithm often keeps a directional residual, which adds extra upside if that outcome wins Its Polymarket account: Jarvisen You can build your own trading bot here: (A trial is available after signing up) Stats: > Trades per active hour: 680 > Average trade size: $9.11 > Win rate: 69% The main edge of this HFT algorithm comes from volatility harvesting: it alternates between accumulating Up and Down, building paired inventory with a combined cost below $1 while keeping a small directional skew toward the cheaper side
0:28

This guy built a trading bot on Polymarket with an average trade size of $9 Result: +$108,248 I analyzed its trades and found that its core strategy is based on dynamically accumulating both outcomes at different points throughout 5 minute BTC Up/Down markets It uses price swings within each market to buy each outcome when it becomes cheaper Here’s what that looks like in practice: > BTC declines sharply > Up falls to 42c, and the bot starts accumulating it > Then BTC rebounds > Down becomes cheaper, and the algorithm buys it at 55c Up + Down = 97c -> 3c edge These paired positions have an average edge of 2.7% But it does not always keep Up and Down perfectly balanced at a 1:1 ratio On top of its paired inventory, the algorithm often keeps a directional residual, which adds extra upside if that outcome wins Its Polymarket account: Jarvisen You can build your own trading bot here: (A trial is available after signing up) Stats: > Trades per active hour: 680 > Average trade size: $9.11 > Win rate: 69% The main edge of this HFT algorithm comes from volatility harvesting: it alternates between accumulating Up and Down, building paired inventory with a combined cost below $1 while keeping a small directional skew toward the cheaper side

VALIX

22,562 görüntüleme • 1 ay önce

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
0:26

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

27,376 görüntüleme • 2 ay önce

This guy built an HFT bot on Polymarket with an average trade size of $8 Result: +$243,619 His bot trades 5- and 15-minute crypto Up/Down markets using a directional latency strategy with fast position switching: 1. It looks for latency between external crypto markets and Polymarket It gets the underlying price from external sources and tracks momentum, acceleration, order-flow imbalance, and distance from the starting price of the current window Based on this data, it constantly recalculates its own fair probability for Up and Down 2. It trades mispricing before Polymarket fully reprices If the external market has already moved, but the outcome price is still lagging, the algorithm sees an edge and starts building a position 3. It quickly changes direction and dynamically hedges the old position If the signal reverses, it can sell the old side or start accumulating the opposite outcome, constantly rebuilding its net exposure His Polymarket nickname: nj23adsknml3 You can build your own trading bot here: (A trial period will be available after registration) This guy’s edge is built on speed. The bot tries to detect changes in external market prices before they are fully reflected on Polymarket, then quickly rebuilds its position after every new signal It repeats this micro edge thousands of times and keeps growing its capital
0:30

This guy built an HFT bot on Polymarket with an average trade size of $8 Result: +$243,619 His bot trades 5- and 15-minute crypto Up/Down markets using a directional latency strategy with fast position switching: 1. It looks for latency between external crypto markets and Polymarket It gets the underlying price from external sources and tracks momentum, acceleration, order-flow imbalance, and distance from the starting price of the current window Based on this data, it constantly recalculates its own fair probability for Up and Down 2. It trades mispricing before Polymarket fully reprices If the external market has already moved, but the outcome price is still lagging, the algorithm sees an edge and starts building a position 3. It quickly changes direction and dynamically hedges the old position If the signal reverses, it can sell the old side or start accumulating the opposite outcome, constantly rebuilding its net exposure His Polymarket nickname: nj23adsknml3 You can build your own trading bot here: (A trial period will be available after registration) This guy’s edge is built on speed. The bot tries to detect changes in external market prices before they are fully reflected on Polymarket, then quickly rebuilds its position after every new signal It repeats this micro edge thousands of times and keeps growing its capital

VALIX

85,048 görüntüleme • 2 ay önce

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
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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 görüntüleme • 5 ay önce