AI Crypto Market Maker

AI-Market-Maker is an open-source project to simulate a cryptocurrency market-making system using AI agents. It aims to provide liquidity and optimize bid-ask spreads for crypto assets like Bitcoin (BTC) and Ethereum (ETH) on exchanges such as Binance and Coinbase. This is an early-stage project for educational purposes, built with a modular agent-based architecture.

Goals

• Simulate crypto market making with AI agents.
• Fetch real-time crypto market data and place simulated orders.
• Support future features like arbitrage, sentiment analysis, and risk management. Note: This project is an experimental simulation currently in development.

Agents

• Market Scanner Agent: Scans for newly listed, to-be-delisted, and high-potential tokens with high-momentum price shifts.
• Technical Analysis Agent: Analyzes price patterns and candlestick data for actionable trading insights.
• Sentiment Analysis Agent: Processes KOL tweets and news to gauge market sentiment trends.
• Statistical Arbitrage Agent: Calculates correlations and hedge ratios to identify token pairs for arbitrage and hedging.
• Quantitative Analysis Agent: Generates trading signals by evaluating momentum and market trends.
• Valuation Agent: Assesses token value by benchmarking against similar category assets.
• Liquidity Agent: Evaluates circulating supply and on-chain liquidity for efficient trades.
• Risk Management Agent: Optimizes TP/SL and position limits using reinforcement learning on volatility.
• Portfolio Management Agent: Manages portfolio and balance for optimized order placement across DEX and CEX venues.

Setup

Prerequisites

• Python 3.11+
• uv
• Binance Testnet API keys (for paper trading, optional)
• OpenAI API key (for GPT-4o, optional)
• Twitter/X API bearer token (for sentiment, optional)
• TA-Lib C library (libta-lib) for technical indicators

Steps

• Clone the Repository:

git clone https://github.com/olaxbt/ai-market-maker.git
cd ai-market-maker

• Install Dependencies:

pip install uv
uv sync

• Install TA-Lib TA-Lib requires the C library (libta-lib) to be installed before you can install the Python wrapper. For easier installation, it is recommended to use Conda:

conda install -c conda-forge ta-lib

You can also use UV to add TA-Lib: If you encounter any issues during the installation of TA-Lib, please refer to the TA-Lib GitHub repository for assistance.

uv add ta-lib

• Set Up Environment Variables:
  Copy .env.example to .env and add API keys:

cp .env.example .env

Example .env:

BINANCE_API_KEY=your_key
BINANCE_API_SECRET=your_secret
OPENAI_API_KEY=your_openai_api_key
TWITTER_BEARER_TOKEN=your_twitter_bearer_token

Usage

Run the main script (currently a placeholder):

uv run python src/main.py --ticker BTC/USDT

Project Structure

ai-market-maker/
├── src/
│   ├── agents/
│   │   ├── market_scan.py          # Scans market and meme coins
│   │   ├── price_pattern.py        # Analyzes price patterns
│   │   ├── sentiment.py            # Analyzes sentiment
│   │   ├── stat_arb.py             # Arbitrage with cointegration
│   │   ├── quant.py                # MACD and volume signals
│   │   ├── valuation.py            # Asset valuation
│   │   ├── risk_management.py      # Position limits, stop-losses
│   │   ├── portfolio_management.py # Allocates budget and places orders
│   │   ├── liquidity_management.py # Bid-ask spread management
│   ├── tools/
│   │   ├── api.py                  # Exchange APIs
│   │   ├── technical_indicators.py # Technical analysis
│   │   ├── sentiment_tools.py      # Sentiment utilities
│   ├── main.py                     # Main entry point
├── uv.toml                         # uv configuration
├── .env.example                    # Environment variables
├── LICENSE                         # License
├── README.md                       # Documentation

License

MIT License. See LICENSE for details.