Probabilistic Trading

A probabilistic-based trading system built using nautilus_trader, implementing Hidden Markov Models and Kalman Filters for market analysis and trading decisions.

Requirements

• Python 3.12 or higher
• uv (modern Python package installer)

Installation

1. Installing uv

uv is a modern Python package installer and resolver that offers significant performance improvements over traditional tools. There are several ways to install uv:

Using curl (recommended for Unix-like systems):

curl -LsSf https://astral.sh/uv/install.sh | sh

Using PowerShell (for Windows):

powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

For more detailed installation instructions and alternatives, please refer to the official uv documentation.

2. Installing Project(Development)

To install the package for development:

1. Clone the repository:

git clone https://github.com/Martingale42/probabilistic_trader.git
cd probabilistic_trading

2. Install the package in editable mode with development dependencies:

uv pip install -e ".[dev]"

3. Installing Project(Stable)

To install the latest version as a user:

uv pip install git+https://github.com/Martingale42/probabilistic_trader.git

Features

• Hidden Markov Model (HMM) based trading strategies
• Kalman Filter implementation for state estimation
• Integration with nautilus_trader for backtesting and live trading
• Support for multiple timeframes and trading pairs

Project Structure

probabilistic_trading/
├── model/
│   ├── hmm/         # Hidden Markov Model implementations
│   └── kalman/      # Kalman Filter implementations
└── strategy/        # Trading strategies

Usage

Basic example of using the HMM strategy:

from probabilistic_trading.strategy import HMMStrategy

# Example code here

Development

This project uses several development tools:

• black for code formatting
• ruff for linting
• mypy for type checking
• pytest for testing

To run the development tools:

# Format code
black .

# Run linting
ruff check .

# Run type checking
mypy .

# Run tests
pytest