Polymarket Ladder Social Posts Traderv0.0.3

An agent continuously monitors Polymarket for post-count range markets on public figures (e.g., CZ, Musk, Trump), groups them into distributions, and executes trades when the sum deviates from 100% or neighbor anomalies appear. This captures risk-free profits from retail mispricing.

Combine the ladder strategy with Twitter/X API v2 to fetch real-time post counts per account. The agent compares actual posting velocity against implied ranges, detecting stale bins and triggering trades before the market corrects.

During global events (e.g., crypto crashes, geopolitical escalations), the agent trades on correlated posting patterns between public figures like Khamenei and CZ. A spike in one triggers trades on adjacent persons' bins.

Build a Poisson/negative-binomial model from 90 days of historical posting data for each person. The agent compares current market prices to model-derived fair prices and trades any bin deviating more than 5%.

An agent tracks cumulative post counts halfway through a measurement period and compares them to historical weekday patterns. Bins far from the expected trajectory are considered overpriced or underpriced, triggering trades.

Deploy agents that provide liquidity on automated market makers like Polymarket, exploiting pricing inefficiencies across related markets to generate profit while reducing spreads.

Package the distribution anomaly detection and neighbor anomaly signals into a real-time API feed. Traders pay a monthly fee to access trade alerts and execution instructions.

Operate a fund that uses this strategy as its core alpha, scaling capital across multiple persons and date ranges. Returns are generated from risk-free arbitrage and statistical edge.