Strategies52 shown

Systematic trading pipeline using Random Forest probability calibration for finding undervalued Polymarket positions.

Quantitative weather prediction model for Polymarket temperature markets using historical climate data and machine learning.

A sophisticated TypeScript bot that uses an ML ensemble (XGBoost + LightGBM) to trade BTC 15-minute binary prediction markets.

Uses an ML ensemble of LGBM, XGB, and LSTM models to predict BTC price direction every 5 minutes and trades on Polymarket.

An autonomous AI agent that finds statistical edges in prediction markets, manages risk with deterministic Kelly, and learns from settled trades

Uses a Random Forest model to estimate true probabilities of event outcomes and trades when Polymarket prices deviate from model predictions.

Trades BTC Up/Down markets using a stacked XGBoost and LightGBM ensemble to identify edge-based arbitrage across multiple timeframes.

Automatically bets the NO side of overpriced Polymarket temperature prediction markets using live weather observations and Gaussian probability model.

A machine learning ensemble bot using LGBM, XGBoost, and LSTM models to predict BTC price direction in 5-minute Polymarket markets.

ML ensemble bot (LGBM+XGB+LSTM) for BTC Up/Down 5min markets on Polymarket.

Use a Random Forest model to identify mispriced prediction market probabilities relative to historical and fundamental data.

Multi-model machine learning ensemble predicting outcomes of Polymarket BTC Up/Down 5-minute markets.

Combines Bayesian probability updates with candlestick pattern recognition and Kelly sizing to trade Polymarket events across all categories.

Train a Random Forest classifier to predict Polymarket market outcomes, calibrate its probability outputs against historical resolution data, and use the calibrated edge to drive automated paper trading.

Bet the NO side of overpriced Polymarket temperature markets by comparing live METAR observations and Open-Meteo forecasts against implied probabilities using a Gaussian probability model.

Generate fair-value World Cup match probabilities using Elo ratings and Dixon-Coles model adjusted for team form, then measure Closing Line Value to validate and improve model calibration.

Exploits arbitrage opportunities on Polymarket using A-S (Aminud-Sarkar) and OFI (Order Flow Imbalance) strategies.

Uses a Random Forest model to calibrate market probabilities and identify mispriced outcomes on Polymarket for automated trading.

Trade based on Random Forest model predictions of market movement, calibrated with backtesting and automated paper trading.

Rust trading engine for Polymarket with multiple strategy loops, shared risk arbiter, remote alpha, and manual execution API.

Bets the NO side of overpriced Polymarket temperature markets using live METAR observations and Open-Meteo forecasts with a Gaussian probability model.

Read-only adviser using Elo ratings and Dixon-Coles model for World Cup match outcomes on Polymarket, with paper trading and scheduled reports.

Systematic trading pipeline using Random Forest calibration model with backtesting framework

Systematic trading pipeline using Random Forest models to calibrate probabilities and detect mispricing on Polymarket.

Trades BTC 5m/15m/1h Up/Down markets using a stacked XGBoost + LightGBM ensemble to detect price dislocations across timeframes.

Exploits short-term mispricing between Polymarket probabilities and traditional prediction market equilibrium after unexpected news breaks, based on slow bot response times.

Trade Polymarket 'number of posts' markets (Elon, Trump) by tracking live post cadence via xtracker.polymarket.com and comparing against the market's implied pace.

Use a Random Forest model to produce calibrated probability estimates for Polymarket outcomes and trade when the model's estimate diverges significantly from market-implied prices.

Trading bot for Polymarket post-counting markets (Elon, Trump, etc.) using xtracker.polymarket.com data.

Bet the NO side of Polymarket temperature markets identified as overpriced by comparing market-implied probabilities against live METAR observations and Open-Meteo forecasts using a Gaussian probability model.

ML ensemble bot (LGBM+XGB+LSTM) for BTC Up/Down 5min markets on Polymarket with auto-training via GitHub Actions

Fade overreactions in markets where the reported bot count (8) diverges from actual on-chain bot wallet activity, exploiting misevaluations.

An unknown strategy bot, likely focused on collecting signals and intelligence from Polymarket data.

Systematic pipeline with Random Forest calibration, backtesting, and automated paper trading.

Edge sourced from systematic miscalibration of Polymarket prices, identified via a Random Forest model trained and backtested out-of-sample.

Use a machine-learning calibration model to identify Polymarket contracts where market-implied probabilities deviate from model-estimated true probabilities, then trade the mispricing.

Multi-agent AI trading bot leveraging multiple ML agents for Polymarket prediction market decisions

Uses a calibrated Random Forest model to identify mispriced probabilities in Polymarket markets, trading when model output diverges from market price.

Screen Polymarket crypto markets by computing distance-to-trigger versus live price feeds and assign resolution-confidence scores to identify mispriced binary outcomes.

Fades the overreaction of markets to short-term forecast spikes by buying NO contracts when extreme weather predictions are likely to be revised down.

Exploit systematic mispricings between Polymarket sports markets and real sportsbook odds from ESPN, with a claimed 10–17% edge on NHL markets and a reported 100% win rate on signals exceeding 5% edge.

Trade statistical arbitrage opportunities when alpha signals drop to zero, indicating mispricing.

Apply high-frequency scalping techniques to Polymarket prediction markets, capturing small, repeated price oscillations in liquid markets using a systematic dashboard-driven approach.

A Python bot leveraging Claude AI to make trading decisions on Polymarket.

Trading bot for post-counting markets on Polymarket (Elon, Trump etc) using xtracker.polymarket.com data source

Mean reversion / rubber band strategy for daily BTC Up/Down markets on Polymarket

Bots trading prediction markets based on post counts (Elon, Trump, etc.) using xtracker.polymarket.com data.

A Python trading bot with a quantitative focus, but no description provided.

AI-powered trading bot using Gemini 3.6 Flash Engine and Cloudflare Switch for prediction market decisions on Polymarket.

A quantitative bot framework that combines multiple pricing signals into an automated trading strategy.

Trading bot for Polymarket post-count markets (Elon, Trump, etc.) using xtracker.polymarket.com data

A general-purpose quantitative trading bot for Polymarket, likely using statistical models and backtesting to find market inefficiencies.