This project is designed to backtest and evaluate multiple trading algorithms. It allows for a competitive environment where up to 500 trading algorithms can compete based on their performance in generating correct buy/sell signals leading to profits.
Key Features
Backtest trading algorithms with historical data
Evaluate performance based on correct buy/sell signals
Manual competition triggering mechanism
Toggleable logging for data printing and optional file saving
Local deployment with Docker, scalable to Kubernetes
Project Structure
Data Fetching Service: Fetch historical market data.
Algorithm Management: Manage and execute trading algorithms.
Backtesting Engine: Run backtests on the algorithms.
Competition Controller: Manage the competitive environment for algorithms.
Logging Service: Handle logging of backtesting results.
Deployment Setup: Set up local and Kubernetes deployments.
Monitoring and Metrics: Monitor system performance and metrics.
Getting Started
Instructions to set up and run the project will be added soon.