AutoTrader ⟸back

AutoTrader is a personal project: a full algorithmic trading platform built on top of Interactive Brokers. It started as a way to automate some trading ideas and evolved into a serious, production-grade system.

Architecture

The platform runs as a 13-service microservices architecture orchestrated with Docker Compose:

• Laravel handles the core business logic, API, job queues, and WebSocket events
• FastAPI (Python) serves as a thin adapter to the Interactive Brokers API
• A second FastAPI service runs Bayesian optimization for algorithm parameter tuning via Optuna
• React 19 + TypeScript powers the monitoring dashboard
• PostgreSQL and Redis handle persistence and real-time event distribution

Trading algorithms

The system supports a pluggable algorithm framework. Algorithms are auto-discovered via PHP 8 attributes, and each one defines its own parameter schema. There are currently 11+ algorithms implemented, ranging from simple buy-and-hold to spectral cycle analysis (FFT), LSTM signal trading, and regime-adaptive strategies.

Backtesting and optimization

The backtesting engine replays historical data bar-by-bar with realistic fill simulation, slippage, and commission modeling. Results are tracked with snapshots and displayed in the dashboard.

For parameter optimization, the platform uses Bayesian optimization via Optuna, allowing algorithms to be tuned across large parameter spaces without brute-force grid search.

The dashboard

The React frontend provides real-time monitoring of positions, orders, and P&L through WebSocket connections. It also exposes the full algorithm library, backtest history, scan results, and optimization runs.

This project is where I push my technical boundaries. It touches distributed systems, real-time data processing, ML-adjacent optimization, financial modeling, and full-stack development all at once. It runs in paper trading mode by default, with live trading infrastructure ready to go.