Building a Polymarket repricing system with Grok Bot agents
A video shows someone using multiple Grok Bot agents to run a fair-value repricing and dynamic hedging system on Polymarket's 5- and 15-minute crypto up/down markets, claiming $207,170 in profit.
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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