Polymarket Trading Strategy Research

Project Overview

This project is dedicated to studying Polymarket - understanding its mechanics, trade settlement, execution processes, and developing automated trading strategies for suitable markets.

Project Goals

1. Research Phase: Understand how Polymarket works

   • Market structure and mechanics
   • Order execution and matching
   • Settlement processes
   • Fee structure
   • API capabilities

2. Data Analysis: Collect and analyze market data

   • Historical market data
   • Liquidity patterns
   • Price movements
   • Market inefficiencies

3. Strategy Development: Build trading strategies

   • Identify profitable market types
   • Develop algorithmic strategies
   • Backtest performance
   • Risk management

4. Execution: Deploy strategies on live markets

   • Automated execution
   • Monitoring and alerting
   • Performance tracking

Project Structure

├── research/           # Documentation and research notes
├── data/              # Market data and datasets
├── src/               # Source code
│   ├── api/          # Polymarket API clients
│   ├── strategies/   # Trading strategies
│   ├── backtesting/  # Backtesting framework
│   ├── execution/    # Trade execution logic
│   └── utils/        # Utility functions
├── config/            # Configuration files
├── tests/             # Unit and integration tests
├── notebooks/         # Jupyter notebooks for analysis
└── scripts/           # Utility scripts

Getting Started

Prerequisites

• Python 3.9+
• pip or poetry for package management

Installation

pip install -r requirements.txt

Configuration

Copy config/config.example.yaml to config/config.yaml and add your API credentials.

Development Status

🚧 This project is in early development phase 🚧

Currently in research and setup phase.

Resources

• Polymarket Documentation
• Polymarket API

License

TBD