RustTrade Agentic Bot 🦀

[!WARNING] This project is not production-ready and should not be used with real money. Using this trading bot involves significant financial risks. Use it only in simulation mode (Paper Trading) or for educational purposes.

A high-performance, multi-agent algorithmic trading system built in Rust. Capable of real-time market surveillance, trend analysis, and autonomous execution. Now featuring a full Native Desktop Interface.

📸 Screenshots

🚀 Key Features

🧠 Intelligent Agents

• Multi-Agent Architecture: 6 specialized agents (Sentinel, Scanner, Analyst, Risk Manager, Order Throttler, Executor).
• Regime Detection: Automatically detects Bull, Bear, Sideways, and Volatile market regimes.
• Dynamic Scanning: Real-time discovery of "Top Movers" and volatility opportunities (Stocks & Crypto).
• System Health Monitoring: Centralized ConnectionHealthService that tracks physical connectivity and broadcasts status to all agents for safe execution.
• Advanced Observability: Full tracing instrumentation, custom Prometheus metrics (win rate, drawdown, latency), and structured logging.

🖥️ Native User Interface (New)

• High-Performance Dashboard: Built with egui (0.31) for zero-latency monitoring.
• Real-Time Visuals: Live charts, interactive metric cards, and scrolling activity feed.
• Internationalization (i18n): Fully localized in English 🇬🇧 and French 🇫🇷.
• Manual Control: "Panic Button" and manual strategy overrides directly from the UI.

📈 Trading Strategies

• Standard: Dual SMA Crossover (Golden/Death Cross).
• Advanced: Triple Filter System (SMA Trend + RSI Momentum + MACD + ADX Trend Strength).
• Dynamic: Automatically switches strategies based on Market Regime (e.g., Trend Riding vs Mean Reversion).
• Statistical: Z-Score Mean Reversion & Statistical Momentum (Regression Slope).
• Machine Learning: Random Forest Classifier trained on technical features (MLStrategy).
• Trend Riding: Long-term trend following with trailing stops.
• Mean Reversion: Contrarian strategy for overbought/oversold conditions (BB + RSI).

🛡️ Advanced Risk Management

• Correlation Filters: Prevents exposure to highly correlated assets (Pearson matrix).
• Sector Exposure Limits: Caps risk per industry sector.
• Circuit Breakers: Daily Loss Limit, Max Drawdown Halt, Composite Risk Score.
• Persistence ("No Amnesia"): Retains critical risk state (HWM, Daily Loss) across restarts.
• Panic Mode: Blind emergency liquidation during data outages.
• PDT Protection: Pattern Day Trader safeguards for accounts < $25k.
• Singleton Connectivity: Unified WebSocket architecture preventing multi-connection conflicts and 406 errors.

🔬 Backtesting & Optimization

• Historical Backtesting: Simulate strategies against past data with S&P500 benchmark comparison.
• Parallel Execution: Ultra-fast multi-symbol batched backtesting using CPU parallelization.
• Grid Search Optimizer: Systematically find best parameters (Sharpe, Sortino, Calmar optimization).
• Performance Metrics: Calculates Alpha, Beta, Win Rate, and Risk-Adjusted Returns.

🛠️ Technical Stack

Core

• Language: Rust 2024 Edition 🦀
• Runtime: tokio (Asynchronous I/O, Channels, Actors)
• Database: sqlx (SQLite 0.8) for local persistence of trades and candles
• GUI: egui 0.31 + eframe (Immediate Mode GUI)

Data & Networking

• Market Data: Alpaca API v2 (WebSocket & REST), OANDA (Forex), Polygon
• WebSockets: tokio-tungstenite
• Serialization: serde, serde_json

Intelligence & Math

• Technical Indicators: ta crate + Custom Implementations (ADX, Pivots)
• Financial Math: rust_decimal (Fixed-point arithmetic for zero precision loss)

⚙️ Configuration

The application is configured primarily via environment variables. You can set these in your shell or use a .env file in the project root.

Core & Connectivity

| Variable | Default | Description | |----------|---------|-------------| | MODE | mock | Trading mode: mock, alpaca, oanda. | | ASSET_CLASS | stock | Asset class: stock or crypto. | | ALPACA_API_KEY | - | Your Alpaca API Key. | | ALPACA_SECRET_KEY | - | Your Alpaca Secret Key. |

Risk Management

| Variable | Default | Description | |----------|---------|-------------| | RISK_APPETITE_SCORE | - | Master Override (1-9). Sets risk profile automatically. | | MAX_DAILY_LOSS_PCT | 0.02 | Max daily loss before "Kill Switch" (2%). | | MAX_DRAWDOWN_PCT | 0.1 | Max total drawdown allowed (10%). | | MAX_SECTOR_EXPOSURE_PCT | 0.30 | Max exposure to a single sector. |

Strategy Parameters

| Variable | Default | Description | |----------|---------|-------------| | STRATEGY_MODE | standard | standard, advanced, dynamic, trendriding, meanreversion. | | ADX_PERIOD | 14 | ADX smoothing period. | | ADX_THRESHOLD | 25.0 | Minimum trend strength for entry. | | RSI_THRESHOLD | 75.0 | RSI Overbought threshold. | | OBSERVABILITY_ENABLED | false | Enable Prometheus metrics server. | | OBSERVABILITY_PORT | 9090 | Port for Prometheus metrics. |

📚 Documentation

• Trading Strategies: Comprehensive guide to all 10 strategies.
• Global App Description: Full architecture details.
• Version History: Changelog.
• Walkthrough: Guide for Benchmark and Backtesting tools.

⚡ Quick Start

Prerequisites

• Rust (Cargo)
• Alpaca API Keys (Paper Trading)

Running the Desktop App

# 1. Configure Credentials
cp .env.example .env
# Edit .env with your Alpaca API keys

# 2. Launch the UI
cargo run --bin rustrade

Backtesting CLI

# Backtest a strategy
cargo run --bin benchmark -- --symbol NVDA --start 2023-01-01 --end 2023-12-31 --strategy advanced

# Parallel Mass Backtest
cargo run --bin benchmark -- --symbol AAPL,TSLA,NVDA,MSFT --start 2024-01-01 --end 2024-03-31 --parallel

# Optimize parameters
cargo run --bin optimize -- --symbol TSLA --grid-config grid.toml

# Train ML Model
cargo run --bin train_ml

🏗️ Architecture

flowchart TB
    subgraph Agents
        S[Sentinel] --> A[Analyst]
        A --> R[Risk Manager]
        R --> E[Executor]
        L[Listener] --> A
        U[User Agent] --> A
    end
    
    subgraph External
        WS[WebSocket] --> S
        REST[REST API] --> S
        NEWS[News RSS] --> L
    end
    
    subgraph Core
        A --> STR[Strategy Engine]
        STR --> SIG[Signal Generator]
        R --> VAL[Validation Pipeline]
        S -.-> CH[Connection Health]
        E -.-> CH
        CH -.-> R
    end
    
    E --> BROKER[Broker API]

🤝 Contributing

Contributions are welcome! Please see our Contributing Guide for details on:

• Development setup
• Code style guidelines (cargo fmt, cargo clippy)
• Testing requirements
• Pull request process

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.