GeneTrader is a Python application that optimizes trading strategy hyperparameters for Freqtrade using genetic algorithms (default) and Optuna. It runs as a CLI tool (`main.py`) or a systemd daemon, generating candidate strategies, executing Freqtrade backtests via subprocess, and scoring candidates with a multi-component fitness function designed to prevent overfitting (minimum trades, drawdown cap, profit factor requirement, complexity penalty). The architecture is modular: `genetic_algorithm/` provides generic GA operators (crossover, mutation, tournament selection, diversity maintenance), `optimization/` contains optimizer base classes and implementations, `strategy/` handles backtest execution, walk-forward validation, and a selection bar (false-discovery diagnostic), and `scripts/` includes deployment workflows and utility scripts. The repo is hybrid—it is a software application that performs data research for trading strategy optimization, with strong emphasis on statistical rigor (walk-forward, Monte Carlo robustness, selection bar). External dependencies include Freqtrade (Docker image), Binance (for pair listing and delisting data), and SSH/SCP for deployment. The codebase is well-structured with tests, but shows signs of personal project maintenance (script sprawl, hardcoded paths, potential overfitting in sample results).